Tag: Machine Learning Award

Ferdib Al Islam | Computer Science | Research Excellence Award

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Mr. Ferdib Al Islam | Computer Science | Research Excellence Award

Northern University of Business and Technology Khulna | Bangladesh

Ferdib-Al-Islam is an Assistant Professor of Computer Science and Engineering at Northern University of Business and Technology Khulna, Bangladesh. He holds an M.Sc. and B.Sc. in CSE and has extensive academic and industrial experience spanning software engineering, IoT, and applied artificial intelligence. His research expertise centers on machine learning, deep learning, explainable AI, large language models, computer vision, and multimodal fusion, with a strong emphasis on trustworthy and interpretable AI for healthcare, agriculture, and smart systems. He has authored 30+ peer-reviewed journal and conference publications, including articles in Springer, IEEE, ACM, and Scopus-indexed journals, and has received multiple best paper and gold awards. An active international collaborator and reviewer for leading journals, he contributes to societal impact through AI-driven healthcare diagnostics, smart farming, and assistive technologies.

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Featured Publications

Islam, Md. Rabiul; Godder, T. K.; Ul-Ambia, A.; Ferdib Al-Islam et al. (2025).
Ensemble model-based arrhythmia classification with local interpretable model-agnostic explanations. IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 14, No. 3 • DOI: 10.11591/ijai.v14.i3.pp2012-2025

Akter, L.; Ferdib Al-Islam; Islam, Md. M.; Al-Rakhami, M. S.; Haque, Md. R. (2021).
Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques. SN Computer Science, Vol. 2, No. 3 • DOI: 10.1007/s42979-021-00551-6

Saha, P.; Sadi, M. S.; Aranya, O. F. M. R. R.; Jahan, S.; Al-Islam, F. (2021).
COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning. Informatics in Medicine Unlocked, Vol. 26 • DOI: 10.1016/j.imu.2021.100741

Rana, Md. M. R.; Adnan, Md. N.; Siddique, Md. M.; Rahman, Md. T.; Ferdib Al-Islam (2024).
Predicting Education Level of the Farmers’ Children of a Developing Country during COVID-19 Using Machine Learning. International Journal of Modern Education and Computer Science (IJMECS), Vol. 16, No. 6 • DOI: 10.5815/ijmecs.2024.06.07

Hossain, S. S.; F. Al-Islam; Islam, Md. R.; Rahman, S.; Parvej, Md. S. (2025).
Autism Spectrum Disorder Identification from Facial Images Using Fine-Tuned Pre-trained Deep Learning Models and Explainable AI Techniques. Semarak International Journal of Applied Psychology, Vol. 5, No. 1, pp. 29–53

Chengjie Li | Computer Science | Innovative Research Award

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Prof. Chengjie Li | Computer Science | Innovative Research Award

Southwest Minzu University | China

Chengjie Li is an Associate Professor and Ph.D. candidate at the School of Computer Science and Technology, Southwest Minzu University, China, and a postdoctoral researcher at the University of Electronic Science and Technology of China. He has also served as a senior visiting scholar at the University of Liverpool, UK. His research expertise lies in information security, intelligent information processing, anti-interference communications, and modern signal processing. Dr. Li has published over 50 peer-reviewed papers, with more than 40 indexed by SCI/EI, and authored two textbooks for graduate and undergraduate education. He has led or participated in multiple national and provincial projects and holds several national patents. His work has received major science and technology awards and contributes to secure communications, satellite systems, and next-generation network resilience.

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Featured Publications

 

Yijui Chiu | Deep Learning | Best Innovation Award

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Prof. Dr. Yijui Chiu | Deep Learning | Best Innovation Award

Xiamen University of Technology, China

Prof. Dr. Yijui Chiu is a distinguished professor and doctoral supervisor specializing in mechanical engineering, with research spanning vibration, rotor dynamics, digital twin technology, deep learning, biomechanics, molecular dynamics, and applications in elderly assistive devices, semiconductor wafer equipment, and renewable energy vehicles. He has demonstrated exceptional strengths in integrating theoretical, computational, and experimental approaches, evidenced by his extensive contributions to rotor system dynamics, fault detection, and coupled vibration analysis. Dr. Chiu excels in interdisciplinary research, combining machine vision, AI, and digital twin frameworks to address complex engineering challenges, including thermo-elastic rotor coupling, flexible rotor systems, and smart exoskeleton control, reflecting his deep analytical and innovative skills. His leadership in guiding 28 funded projects, both national and industry-based, has fostered cross-strait innovation collaboration and produced a prolific output of 81 publications with 723 citations and an h-index of 16, highlighting his influence in mechanical engineering and related fields. Dr. Chiu’s research skills extend to experimental mechanics, finite element analysis, intelligent system design, machine learning applications, and multi-physics modeling, enabling practical solutions for energy systems, robotics, and industrial machinery. He has also cultivated a strong record of mentorship, supervising graduate students to national awards and doctoral programs at top institutions, reflecting his commitment to academic excellence and knowledge transfer. Areas for potential growth include expanding the application of his methodologies to broader industrial digital twin implementations, integrating renewable energy systems with AI-enhanced control, and exploring more advanced human-robot interaction systems for healthcare and manufacturing. Looking forward, Dr. Chiu has significant future potential to shape smart manufacturing, predictive maintenance, and sustainable mechanical systems by leveraging his interdisciplinary expertise and collaborative networks. His innovative contributions not only advance scientific understanding but also drive practical solutions with societal, industrial, and environmental impact, making him a highly deserving candidate for awards recognizing visionary achievements in engineering research and technology development.

Profiles: Scopus | ORCID

Featured Publications

Hong, W.-B., Chiu, Y.-J., & Yang, J.-Y. (2025). Analysis of double-column stacker structure. In Smart Innovation Systems and Technologies (Vol. 363, pp. 209–218). Springer.

Yao, Y.-H., & Chiu, Y.-J. (2025). Design of lifting equipment of wafer unmanned track carrier. In Smart Innovation Systems and Technologies (Vol. 362, pp. 195–204). Springer.

Gu, Y.-X., Chiu, Y.-J., & Li, M. (2025). Mechanism design of short-distance food transmission robot. In Smart Innovation Systems and Technologies (Vol. 362, pp. 171–182). Springer.

Chiu, Y.-J., Gu, Y.-X., Yang, C.-H., Jian, S.-R., & Chen, D. (2025). Numerical investigation of thermoelastically coupled vibrations of a rapidly rotating rigid-disk rotor system with a blade crack. Journal of Mechanical Science and Technology, 39, 1–14.

Chiu, Y.-J., Yao, Y.-H., Lin, C.-M., Dimitrov, D. Z., Juang, J.-Y., & Jian, S.-R. (2025, October). Unveiling the deformation behaviors of single-crystal LuVO4 using nanoindentation and finite element analysis. Results in Engineering, 18, 107668.

Prof. Dr. Yijui Chiu’s work integrates advanced rotor dynamics, digital twin technology, and AI-driven control systems to revolutionize mechanical engineering, enabling smarter, safer, and more efficient industrial machinery. His research advances scientific understanding while delivering practical solutions for energy, healthcare, and manufacturing industries, fostering global innovation and societal benefit.

Mohamad Abu Seman | AI and Robotic System | Best Researcher Award

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Dr. Mohamad Abu Seman | AI and Robotic System | Best Researcher Award

Senior Lecturer from University Sains Malaysia | Malaysia 

Dr. Mohamad Tarmizi Abu Seman is a Senior Lecturer at Universiti Sains Malaysia (USM), widely recognized for his pioneering work in mechanical engineering and intelligent systems integration. With an academic and research career rooted in innovation and community impact, Dr. Abu Seman has consistently contributed to the advancement of engineering solutions that intersect with artificial intelligence, smart healthcare systems, and sustainable technologies. His extensive research has produced practical tools and systems, from smart rehabilitation gloves and diabetic insoles to IoT-based agriculture and intelligent parking solutions. He has been instrumental in supervising numerous undergraduate and postgraduate students, leading them in cutting-edge research that addresses real-world challenges. Dr. Abu Seman has received multiple national and international accolades for his innovations and continues to serve on key research projects funded by Malaysian research councils and ministries. His involvement in applied engineering and technology-based community solutions demonstrates his commitment to both academic excellence and social betterment. As a member of professional networks like IEEE, he maintains strong academic connections and continually expands his interdisciplinary scope. His contributions place him at the forefront of Malaysian engineering innovation, with increasing global visibility in science, health, and technology domains.

Professional Profile

Scopus Profile | ORCID Profile | Google Scholar

Education

Dr. Mohamad Abu Seman holds a Doctor of Philosophy (Ph.D.) in Mechanical Engineering, marking the culmination of years of rigorous academic training and specialized research. His academic foundation is rooted in applied mechanical engineering, where he focused on areas such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and mechanical system optimization. His doctoral research explored aerodynamic performances, smart sensor systems, and heat energy applications, combining computational and experimental methodologies to advance engineering practices. Throughout his academic journey, Dr. Abu Seman developed expertise in simulation software such as ANSYS and MATLAB, allowing him to translate complex engineering theories into practical, problem-solving innovations. His academic credentials are complemented by his continued learning through research-based teaching and national innovation competitions. His education laid a strong foundation for his future research endeavors in smart embedded systems, energy-efficient devices, and AI-integrated mechanical systems. The application of his doctoral studies is evident in the range of projects he has undertaken, including robotics, sensor technologies, and sustainable engineering solutions. Dr. Abu Seman’s academic journey has not only shaped his technical competencies but also positioned him as a thought leader in intelligent mechanical systems both in Malaysia and the wider ASEAN research community.

Experience

As a Senior Lecturer at Universiti Sains Malaysia (USM), Dr. Mohamad Abu Seman has demonstrated multifaceted professional excellence in teaching, research, and applied innovation. He has led and contributed to a wide range of university-community partnership projects, focusing on smart agriculture, robotic rehabilitation, and inclusive design for differently-abled individuals. His current and past grant-funded research initiatives include the development of intelligent glove systems, IoT-powered irrigation, and robotic mechanisms, amounting to over RM 700,000 in research funding. Dr. Abu Seman has played an integral role in supervising undergraduate and postgraduate students, many of whom have produced award-winning capstone projects and published academic papers under his guidance. His engineering expertise spans smart mechanical systems, AI-driven embedded applications, and biomedical design. Additionally, he has represented his institution at national and international engineering competitions and innovation exhibitions, further solidifying his professional credibility. Dr. Abu Seman’s experience is deeply rooted in both academic mentorship and real-world problem-solving, often bridging the gap between engineering theory and tangible community impact. He continues to contribute as a principal investigator in active research projects, and his career trajectory exemplifies sustained leadership in research, innovation, and collaborative knowledge exchange.

Research Interests

Dr. Abu Seman’s research interests lie at the intersection of mechanical engineering, smart systems, and artificial intelligence, with a focus on real-world applications in healthcare, agriculture, and industrial automation. He is particularly passionate about the design and simulation of intelligent assistive devices, such as smart diabetic insoles and rehabilitation gloves, which utilize embedded systems, IoT, and sensor-based feedback for enhanced performance and usability. Another major area of his research focuses on energy-efficient systems and robotic mechanisms that aid in automation for improved human well-being and sustainability. Projects like the development of a universal robotic gripper, IoT-enabled irrigation systems, and embedded traffic systems showcase his interdisciplinary and application-driven approach. He has also delved into predictive analytics using AI for transportation systems, biomedical applications, and real-time industrial monitoring. These interests are driven by a commitment to integrating AI and mechanical structures to create smarter, safer, and more adaptive engineering systems. Dr. Abu Seman also engages in bio-inspired system design and fuzzy logic control applications for automation and autonomous vehicles. His ongoing research continuously aligns with evolving industry needs and national development priorities, making him a prominent contributor to Malaysia’s vision for innovation-led engineering development.

Research Skills

Dr. Abu Seman possesses a robust arsenal of technical skills that enable him to deliver impactful and solution-oriented research in mechanical engineering. He is proficient in Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA), leveraging software like ANSYS, MATLAB, and SolidWorks for simulation and modeling purposes. His work incorporates embedded technology, robotic automation, smart sensors, and artificial intelligence frameworks, showcasing his multi-disciplinary fluency. Dr. Abu Seman has also demonstrated competence in design thinking and prototyping, guiding student-led innovations from ideation to final implementation. He is highly skilled in using Raspberry Pi and Arduino systems for building smart devices in healthcare and IoT agriculture. His experience in leading grant-funded research has sharpened his skills in project formulation, technical reporting, and data visualization. With knowledge of deep learning, fuzzy control systems, and adaptive algorithms, he applies computational intelligence to mechanical systems with practical relevance. His skill set also includes academic writing, having published in high-impact Scopus and WoS-indexed journals. Moreover, his guidance of undergraduate and postgraduate students reveals his mentoring capacity and commitment to skill transfer. Dr. Abu Seman continues to refine his skills to align with emerging trends in smart engineering, robotics, and AI integration.

Awards and Honors

Dr. Mohamad Abu Seman has been the recipient of numerous national and international awards that recognize both his innovation and social impact. He earned the Silver and Special Awards at the Asia International Innovation Exhibition (AIINex) for his automated door system developed in response to COVID-19 SOP compliance. His leadership in student innovation led to his team winning Champion in the “OKU Smart Parking Lot System” project during the Engineering Innovative Design Competition (ENGINNOVATE) at USM. He was also awarded The People’s Choice Award at the Malaysian Innovative Healthcare Symposium (MIHS) for the Smart Diabetic Insole project. These recognitions reflect his commitment to technological inclusivity, especially projects that support marginalized communities like the elderly and the disabled. Dr. Abu Seman’s research has also been showcased at international IEEE conferences and Springer’s Lecture Notes series, underlining his global academic reach. His recognition goes beyond technical merit; it also underscores his ability to align innovation with public health and community development goals. These awards have positioned him as a leading innovator in Malaysia’s academic engineering landscape, reaffirming his capability to translate research into socially responsible engineering solutions.

Publication Top Notes

  • Smart water-quality monitoring system based on enabled real-time internet of things – 2020, 57 citations

  • Monitoring temperature, humidity and controlling system in industrial fixed room storage based on IoT – 2020, 19 citations

  • Embedded operating system and industrial applications: a review – 2021, 13 citations

  • Internet of things based automated agriculture system for irrigating soil – 2022, 11 citations

  • Application of deep learning in iron ore sintering process: a review – 2024, 7 citations

  • Intelligent pressure and temperature sensor algorithm for diabetic patient monitoring: An IoT approach – 2024, 7 citations

  • A MAC protocol for energy efficient wireless communication leveraging wake-up estimations on sender data – 2020, 7 citations

Conclusion

Dr. Mohamad Tarmizi Abu Seman exemplifies the qualities of an outstanding researcher, educator, and innovator. His multidisciplinary contributions in mechanical engineering, particularly in the integration of AI, embedded systems, and community-focused technologies, have made a tangible impact on both the academic community and Malaysian society. With a proven track record of student mentorship, successful research funding, impactful publications, and award-winning innovations, Dr. Abu Seman continues to raise the standards of engineering education and research excellence. His projects not only advance scientific knowledge but also directly contribute to societal welfare by addressing issues in healthcare accessibility, smart infrastructure, and inclusive technology. As he expands his research through international collaborations and aims for higher-tier publications, his potential as a future leader in smart engineering systems and AI-driven innovation remains strong. His work stands as a model of applied science for societal good, and his nomination is a testament to his dedication to transforming challenges into impactful solutions.

Kah Ong Michael Goh | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Kah Ong Michael Goh | Computer Science | Best Researcher Award

Associate Professor from Multimedia University | Malaysia

Assoc. Prof. Ts. Dr. Goh Kah Ong Michael is a prominent academician and innovator in the field of Artificial Intelligence, particularly known for his contributions to biometrics, computer vision, image processing, and smart city systems. He is currently serving as an Associate Professor at the Faculty of Information Science and Technology (FIST), Multimedia University (MMU), Malaysia. His professional journey spans over two decades, beginning as a tutor and progressively advancing to senior academic roles, including a tenure as Deputy Dean for Student Affairs and Alumni. Dr. Goh’s work focuses on practical, high-impact research that integrates AI into real-world applications such as traffic management, intelligent authentication, and urban system automation. A hands-on technologist, he has built strong industry ties and led collaborative research projects involving government and private sectors. His accomplishments include numerous international awards and publications, reflecting his ability to merge theoretical depth with applied innovation. Dr. Goh’s contributions extend beyond academia through leadership roles, student mentoring, and his involvement in technology exhibitions and innovation showcases. With an ever-evolving research agenda, he continues to be a valuable contributor to Malaysia’s technological advancement and is a role model for aspiring researchers in AI and computer science.

Professional Profile

Scopus Profile | ORCID Profile | Google Scholar

Education

Dr. Michael Goh pursued all his higher education at Multimedia University (MMU), Malaysia, reflecting a strong and continuous academic association with the institution. He earned his Bachelor of Information Technology (Hons.), majoring in Software Engineering. This undergraduate foundation in software development provided him with a firm grounding in computational thinking and programming. He then obtained his Master of Science in Information Technology by Research, where he began to delve into research-oriented activities, focusing on emerging areas in digital systems and human-computer interaction. His academic progression culminated in the completion of his Doctor of Philosophy (Ph.D.) in Information Technology by Research. His doctoral work emphasized advanced topics in biometrics and contactless identity recognition, a theme that would continue to define his professional research identity. Throughout his academic journey, Dr. Goh has demonstrated exceptional scholarly dedication and subject mastery, which laid the groundwork for his teaching, supervision, and innovative research contributions at MMU. His educational background, centered on a research-intensive model, reflects the synthesis of academic theory and practical innovation that characterizes his work today.

Experience

Assoc. Prof. Dr. Goh Kah Ong Michael has a well-established professional history with Multimedia University, Malaysia, spanning over two decades. He began his career as a Tutor at the Faculty of Information Science & Technology (FIST). He was appointed as a Lecturer and elevated to Senior Lecturer. He served as Deputy Dean of Student Affairs and Alumni, where he provided strategic leadership in academic administration and student engagement. He also had an industrial attachment with Heathmetrics Sdn Bhd, fostering industry-academic collaboration and applying academic research to practical applications. This rich blend of academic and industry experience has honed his capabilities in academic governance, curriculum development, student mentorship, and real-world technology deployment. His ongoing role as Associate Professor continues to leverage his expertise in AI, biometrics, and software development. Through his involvement in university committees, innovation competitions, and cross-institutional collaboration, Dr. Goh demonstrates a commitment to excellence in teaching, research, and societal impact, making him a vital contributor to both MMU and Malaysia’s wider research ecosystem.

Research Interest

Dr. Goh’s research interests encompass a wide spectrum of areas within Artificial Intelligence and digital systems engineering. A significant portion of his work is dedicated to contactless biometric technologies, especially those using palm vein, palm print, and finger vein recognition. These technologies are integral to secure authentication systems and form the core of his early and ongoing research. He has also extensively explored video analytics, pattern recognition, image processing, and data classification for security, healthcare, and smart city applications. One of his signature projects, the “Smart Traffic Impact Assessment System”, represents a major advancement in urban AI, combining real-time data analysis with predictive modeling. Another domain of interest is gait recognition and spatiotemporal feature extraction, applied to age-based classification systems using AI algorithms. His interdisciplinary approach blends software engineering with signal processing and machine learning, leading to innovative tools with societal benefits. Additionally, he is actively engaged in research around reinforcement learning for dynamic pricing systems, integrating AI with economics. Dr. Goh’s projects reflect a strong application-driven research philosophy, pushing boundaries in how AI can be embedded into everyday environments for efficiency, safety, and sustainability.

Research Skills

Dr. Goh possesses a diverse and advanced set of research skills that have been instrumental in developing intelligent digital solutions. His core technical proficiencies include AI modeling, deep learning, video analytics, and multimodal data fusion, particularly in biometric systems. He is highly skilled in software and application development, with extensive experience in developing both academic prototypes and deployable commercial systems. His expertise also extends to database design and management, essential for handling large-scale biometric and visual data. He has a strong command over object recognition and pattern classification techniques using AI and machine learning frameworks. Dr. Goh is also experienced in reinforcement learning algorithms, used in his dynamic pricing and smart city projects. On the academic side, he is adept at writing research proposals, publishing in high-impact journals, and presenting findings at international conferences. His collaborative skills are evidenced by successful multi-author book chapters and interdisciplinary project leadership. Moreover, he excels in mentoring postgraduate students and coordinating innovation competitions. With this unique combination of programming, analytical, leadership, and project management skills, Dr. Goh consistently delivers impactful, high-quality research.

Awards and Honors

Dr. Goh has received numerous awards and recognitions at national and international levels, affirming his excellence in research and innovation. Most notably, he was awarded the ITEX SPECIAL MINDS Thematic Award 2024 and a Gold Medal for his “Smart Traffic Impact Assessment System” at the International Invention, Innovation, Technology Exhibition (ITEX). He also earned multiple accolades for “CloudPark – The Smart City Parking Solution,” including gold medals and top placements in PROCOM and Infineon competitions. His consistent success in innovation is further illustrated  for biometric systems, video puzzle learning tools, and intelligent scanning devices. he received the Outstanding Research Award from Multimedia University, a testament to his sustained scholarly contribution. Earlier recognitions, including the Silver Medal at ITEX for “Palm’n Go – A Touchless Biometric System”, mark the beginning of his decorated research journey. Dr. Goh’s portfolio of over 18 innovation awards highlights his commitment to creating solutions that are both technically robust and socially impactful. These accolades validate his role as a thought leader in biometric AI and smart systems research.

Publication Top Notes

  • “An automated palmprint recognition system”, Image and Vision Computing, 2005 – Cited 396.

  • “PalmHashing: a novel approach for cancelable biometrics”, Information Processing Letters, 2005 – Cited 255.

  • “Touch-less palm print biometrics: Novel design and implementation”, Image and Vision Computing, 2008 – Cited 245.

  • “Facial expression recognition using a hybrid CNN–SIFT aggregator”, International Workshop on Multi-disciplinary Trends in Artificial Intelligence, 2017 – Cited 198.

  • “Palmprint recognition with PCA and ICA”, Proc. Image and Vision Computing New Zealand, 2003 – Cited 163.

Conclusion

Assoc. Prof. Ts. Dr. Goh Kah Ong Michael stands as a shining example of how academic rigor, technological innovation, and community engagement can converge to make a lasting impact. His career is marked by groundbreaking contributions in AI-driven biometrics and smart city solutions, with practical outputs recognized at the highest levels through international innovation awards. As a mentor, educator, and innovator, he continues to shape the future of information technology and digital systems in Malaysia and beyond. His research not only addresses complex technical challenges but also offers scalable solutions that benefit society, including urban traffic management and secure identification technologies. With his impressive publication record, long-term academic service, and forward-looking research agenda, Dr. Goh is well-positioned to assume future leadership roles in research policy, international collaboration, and higher education development. His contributions exemplify excellence in research translation and academic leadership, making him a deserving candidate for international recognition and continued advancement in the global research landscape.

Nadeem Khanday | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Nadeem Khanday | Computer Science | Best Researcher Award

Assistant Professor from National Institute of Technology Srinagar, India

Dr. Nadeem Yousuf Khanday is an accomplished academic and researcher in Computer Science & Engineering, currently serving as an Assistant Professor at the School of Computer Science, UPES, Dehradun, India. With a strong academic foundation and a passion for advanced computing technologies, he has contributed extensively to the fields of artificial intelligence, machine learning, and deep visual learning. His research outputs include high-impact journal publications, international conference presentations, patents, and book chapters with globally recognized publishers. Dr. Khanday is deeply involved in exploring innovative AI techniques that address real-world challenges, including healthcare diagnostics, crop disease detection, cloud computing, and smart environments. He is also a certified GATE, UGC-NET, and JK-SET qualifier, emphasizing his academic excellence. Throughout his career, he has taught a variety of technical subjects and mentored students in core areas of computer science. He brings a balanced combination of research, teaching, and applied innovation to the academic domain. With a growing body of interdisciplinary work, Dr. Khanday continues to build his reputation as a future-oriented researcher contributing to both academia and industry. His deep commitment to scholarly excellence and emerging technologies positions him as a deserving candidate for recognition in prestigious research awards.

Professional Profile

Education

Dr. Nadeem Yousuf Khanday has pursued a rigorous academic trajectory in Computer Science & Engineering. He earned his Doctor of Philosophy (Ph.D.) from the prestigious National Institute of Technology (NIT), Srinagar, focusing on advanced computing technologies and artificial intelligence. Prior to his doctorate, he completed his Master of Technology (M.Tech) from Vivekananda Global University, Jaipur, where he achieved an outstanding CGPA of 9.69 in Computer Science & Engineering, demonstrating his academic strength and subject mastery. His undergraduate studies were conducted at Visvesvaraya Technological University (VTU), Belgaum, where he obtained a Bachelor of Engineering (B.E.) degree in Computer Science & Engineering with a commendable academic record. Dr. Khanday has also qualified national-level competitive exams including the Graduate Aptitude Test in Engineering (GATE) and University Grants Commission National Eligibility Test (UGC-NET), as well as JK-SET, qualifying him for Assistant Professorship roles in Indian universities. These qualifications reflect his high-level proficiency in the domain and commitment to continued academic growth. His academic background provides a strong foundation for his research endeavors, enabling him to tackle complex computing problems and advance the frontier of knowledge in artificial intelligence, machine learning, and computer vision.

Professional Experience

Dr. Nadeem Yousuf Khanday possesses diverse and dynamic professional experience across some of India’s reputed institutions. He is currently employed as a Regular Assistant Professor at the School of Computer Science (SoCS), UPES Dehradun since June 2023. Before this, he served as a Lecturer at the University of Kashmir, J&K, where he taught undergraduate and postgraduate computer science courses from March to June 2023. His earlier appointments include his tenure as an Assistant Professor (Contract) at NIT Srinagar from April 2017 to July 2018, and later as a Teaching Assistant (Research Scholar) from July 2018 to February 2023 at the same institute. These roles have helped him accumulate extensive experience in teaching core computer science courses such as Artificial Intelligence, Operating Systems, Data Structures, and Computer Architecture. Throughout his career, Dr. Khanday has skillfully blended teaching with hands-on research, working on projects related to visual learning, deep learning, and intelligent systems. His progressive journey from contract roles to full-time professorship demonstrates his steady academic development and increasing responsibilities. With significant academic leadership and research roles, he is well-positioned to lead innovative educational and research initiatives in AI and computing.

Research Interests

Dr. Nadeem Yousuf Khanday’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Computer Vision, with a particular focus on deep visual learning and few-shot learning models. He explores innovative solutions to computational challenges involving limited data samples, aiming to improve learning accuracy and cross-domain generalization. His research extends into practical domains such as healthcare diagnostics, agricultural disease prevention, cloud computing optimization, and smart IoT-based systems. Dr. Khanday has investigated topics including convolutional neural networks for COVID-19 prognosis, metric learning models for classification, and AI-driven smart farming using 5G networks. His recent work has integrated Large Language Models (LLMs) and Generative AI to enhance decision-making systems in medical and industrial contexts. His interdisciplinary approach combines theoretical models with real-world applications, contributing to sustainable development through intelligent computing. Dr. Khanday’s research aims not only to push academic boundaries but also to provide practical, scalable solutions for modern societal challenges. His continuous engagement with cutting-edge technologies and publication in top-tier journals solidify his status as a thought leader in visual intelligence and machine learning systems.

Research Skills

Dr. Nadeem Yousuf Khanday possesses a strong portfolio of research skills that span multiple domains in computing. He is proficient in developing machine learning algorithms, deep learning architectures, and advanced image processing models for varied applications. His expertise includes designing few-shot learning frameworks, enhancing cross-domain classification performance, and deploying convolutional neural networks for medical image analysis and smart diagnostics. He has hands-on experience with AI-based anomaly detection, visual segmentation systems, and cloud environment optimization using hybrid fuzzy and swarm intelligence methods. Dr. Khanday is also skilled in patent writing, having developed innovative systems for crop disease detection and motorcycle safety. His publication record reflects his ability to effectively communicate complex methodologies, backed by data-driven validation and practical implementation. Additionally, his collaboration in multi-author projects and book chapters indicates strong academic teamwork and interdisciplinary engagement. His teaching and research experiences across different institutions have also honed his ability to mentor students and lead academic discussions. Equipped with technical, analytical, and conceptual research skills, Dr. Khanday continues to contribute impactful and scalable innovations across emerging fields like generative AI, IoT systems, and smart computing.

Awards and Honors

Dr. Nadeem Yousuf Khanday has received various forms of recognition for his scholarly achievements and research excellence. Notably, he has qualified multiple national-level eligibility exams, such as GATE, UGC-NET, and JK-SET, highlighting his academic distinction and competency to teach at the university level. In 2023, he was awarded recognition for his impactful contributions to AI-driven visual understanding and applications, as reflected in his high-impact publications and patents. His patent work, including an apparatus for auto-detection of crop diseases and motorcycle safety systems, has been acknowledged for its potential technological and societal value. Dr. Khanday’s research has also gained visibility through SCOPUS- and SCI-indexed publications with top journals like Computer Science Review and Neural Computing and Applications. His invited book chapters published by Taylor and Francis, Springer Nature, and Cambridge University Press underline his reputation among international academic publishers. Furthermore, he has presented at international conferences in Europe and Asia, receiving acclaim for his work on machine vision, fuzzy systems, and cloud intelligence. These accolades reflect both his individual excellence and collaborative impact within the research community.

Conclusion

Dr. Nadeem Yousuf Khanday exemplifies the profile of a high-caliber academician and innovative researcher with notable achievements in the fields of artificial intelligence, deep learning, and computer vision. Through a strong foundation in computer science education and a wealth of research experience, he has consistently contributed to advancing both theory and practice. His multidisciplinary research in healthcare, smart agriculture, and intelligent systems, along with a growing list of high-impact publications, patents, and book contributions, sets him apart as a forward-thinking scholar. His teaching experience across reputed Indian institutions and his ability to combine pedagogy with practical applications further enhance his value to academia. Dr. Khanday’s commitment to solving real-world problems using machine learning and AI tools not only enhances academic discourse but also promotes sustainable innovation. His emerging collaborations, international conference participation, and national recognitions affirm his credibility and future potential. In light of his qualifications, scholarly output, and research relevance, he stands as a highly deserving candidate for the Best Researcher Award, with the capacity to influence the global research community and contribute significantly to technological advancement

  1. Covariance-based Metric Model for Cross-domain Few-shot Classification and Learning-to-generalization
    📘 Journal: Applied Intelligence, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  2. Learned Gaussian ProtoNet for Improved Cross-domain Few-shot Classification and Generalization
    📘 Journal: Neural Computing and Applications, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  3. Deep Insight: Convolutional Neural Network and Its Applications for COVID-19 Prognosis
    📘 Journal: Biomedical Signal Processing and Control, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  4. Taxonomy, State-of-the-art, Challenges and Applications of Visual Understanding: A Review
    📘 Journal: Computer Science Review, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

Supraja Ballari | Computer Science | Best Researcher Award

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Mrs. Supraja Ballari | Computer Science | Best Researcher Award

Assistant Professor from Guru Nanak Institutions Technical Campus, India

Smt. B. Supraja is an experienced academician and researcher in the field of Computer Science and Engineering. With over 15 years of teaching experience at various reputed technical institutions in India, she has consistently contributed to both pedagogy and applied research. Currently serving as an Assistant Professor at Guru Nanak Institutions Technical Campus, Telangana, she is also pursuing her Ph.D. in Computer Science from Dravidian University, Kuppam. Her academic journey is marked by a strong foundation in computer applications and engineering, with a focus on emerging areas such as machine learning, cybersecurity, blockchain, and data mining. She has authored several research papers in reputed journals and holds multiple patents reflecting her commitment to innovation. Her work spans interdisciplinary applications of computing in logistics, vehicular networks, and employee management systems. Known for her diligence and academic integrity, Smt. Supraja combines her teaching skills with active research, mentorship, and curriculum development. Her ability to blend theory with practical applications makes her a valuable asset in academia. Her academic contributions have positioned her as a researcher with great potential for national recognition, including eligibility for research excellence awards.

Professional Profile

Education

Smt. B. Supraja holds a rich academic background that lays the foundation for her current research pursuits. She is presently pursuing a Ph.D. in Computer Science from Dravidian University, Kuppam, with a focus on contemporary issues in cybersecurity, data analytics, and intelligent systems. She completed her M.Tech in Computer Science and Engineering from PBR Visvodaya Engineering College, Kavali (affiliated to JNTUA) between 2011 and 2014, where she deepened her technical knowledge in core computer engineering disciplines. Her postgraduate studies began with a Master of Computer Applications (M.C.A.) from Geethanjali College of PG Studies under Sri Venkateswara University, Nellore (2002–2005). Her academic credentials are well aligned with the technological demands of today’s dynamic research landscape. Her education spans foundational programming, software engineering principles, and advanced technologies, making her a capable researcher and instructor. Throughout her academic journey, she has remained focused on interdisciplinary applications of computer science in real-world contexts. Her continuous academic progression—culminating in her doctoral studies—underscores her lifelong commitment to education and research excellence.

Professional Experience

Smt. Supraja’s professional journey spans nearly two decades in the higher education sector, where she has served in various teaching capacities. She is currently employed as an Assistant Professor at Guru Nanak Institutions Technical Campus, Telangana (since February 2023), where she teaches undergraduate and postgraduate courses in Computer Science. Prior to this, she held the same role at Narayana Engineering College, Nellore from July 2021 to January 2023, and at Krishna Chaitanya Educational Institutions from December 2014 to July 2021, teaching a mix of B.Sc., BCA, and M.Sc. students. Her earlier roles included positions at S. Chaavan Institute of Science & Technology and S.V. Arts & Science College, Gudur, where she taught various computer science subjects to both undergraduate and postgraduate students. In each of these positions, she has contributed to academic instruction, student mentoring, and curriculum development. Her experience reflects a deep engagement with the academic process, ranging from foundational teaching to more research-oriented mentorship. This long-standing teaching career demonstrates not only her pedagogical strengths but also her dedication to shaping the next generation of computer scientists.

Research Interests

Smt. B. Supraja’s research interests span a wide range of cutting-edge domains in computer science. Her primary focus areas include machine learning, cybersecurity, blockchain applications, data mining and data warehousing, fog computing, and cloud-based control systems. Her work reflects a deep interest in the intersection of artificial intelligence with societal and industrial applications. She has conducted research on anomaly detection in software-defined networks, data sharing in vehicular social networks using blockchain, and logistics optimization through structural equation modeling. She also explores areas such as sentiment analysis using Naïve Bayes classifiers, encrypted control systems, and cyberattack prediction through machine learning techniques. These interests align closely with today’s technological priorities such as data protection, automation, and intelligent decision-making. Her work seeks to bridge the gap between academic research and industrial applicability. The diverse yet cohesive nature of her research interests indicates her adaptability and eagerness to explore interdisciplinary applications. These interests not only reflect technical competence but also her sensitivity to real-world challenges that require intelligent, scalable, and secure technological solutions.

Research Skills

Smt. B. Supraja brings a robust set of research skills honed through academic work, project collaborations, and innovation initiatives. She is proficient in programming languages such as Java, C, and C++, and has practical experience with databases like Oracle and MS Access, as well as web technologies like HTML, JavaScript, and XML. Her expertise includes operating within different development environments using tools like Eclipse and Editplus. These technical proficiencies support her capability in implementing machine learning models, simulation systems, and data analysis applications. She has successfully authored and co-authored peer-reviewed publications and book chapters, showing familiarity with scientific writing, research methodology, and collaborative scholarship. In addition, she has contributed to the innovation space through patent filings in areas such as employee churn prediction and cyberattack prevention systems using machine learning algorithms. Her ability to apply theoretical knowledge into practical systems design and her experience in real-world problem solving mark her as a capable and results-oriented researcher. Her academic and technological skills are further strengthened by her consistent teaching of core subjects, which reinforces her depth in fundamental computer science concepts.

Awards and Honors

While a formal list of awards and honors is not provided in her academic profile, Smt. B. Supraja’s achievements in publishing, patenting, and contributing to book chapters reflect strong professional recognition. Her patents—three of which are published between 2022 and 2024—indicate acknowledgment of her work’s novelty and utility in applied computer science. Her scholarly contributions to journals such as the Journal of Engineering Sciences and Design Engineering, alongside collaborative book chapters on contemporary issues like COVID-19’s digital impact, have been positively received in academic circles. These publications are indicative of her growing visibility in the research community. Furthermore, her inclusion in multidisciplinary anthologies and collaborations with senior academicians from diverse fields show a level of trust and professional respect. Although specific awards or titles are not yet documented, her research outputs and innovation track record position her as a strong candidate for future academic honors and distinctions. Her work is gaining momentum, and with further institutional and international engagement, she is well poised for formal recognition through research awards and academic fellowships.

Conclusion

In conclusion, Smt. B. Supraja is a dedicated academic professional and an emerging researcher in the field of computer science. Her profile reflects a balanced integration of long-standing teaching experience and active research engagement. She has demonstrated capability in producing impactful scholarly work through journal publications, book chapters, and patents. Her expertise spans across machine learning, blockchain, cloud systems, and cybersecurity—fields that are not only technologically significant but also socially relevant. While she is still progressing in her doctoral research, her current contributions are commendable and indicate strong future potential. Areas for growth include enhancing research impact through increased citation metrics, obtaining funded projects, and expanding global collaborations. However, the depth and diversity of her current academic efforts strongly support her candidacy for research awards. Smt. Supraja exemplifies the qualities of a modern researcher—technically skilled, pedagogically sound, and oriented towards practical applications. With continued dedication and strategic academic outreach, she is well-positioned to become a recognized contributor to India’s research and innovation landscape.

Publications Top Notes

  1. A vital neurodegenerative disorder detection using speech cues
    BS Jahnavi, BS Supraja, S Lalitha
    2020

  2. Simplified framework for diagnosis brain disease using functional connectivity
    T Swarnalatha, B Supraja, A Akula, R Alubady, K Saikumar, …
    2024

  3. DARL: Effectual deep adaptive reinforcement learning model enabled security and energy-efficient healthcare system in Internet of Things with the aid of modified manta ray
    B Supraja, V Kiran Kumar, N Krishna Kumar
    2025

  4. IoT based effective wearable healthcare monitoring system for remote areas
    S Tiwari, N Jain, N Devi, B Supraja, NT Chitra, A Sharma
    2024

  5. Securing IoT networks in healthcare for enhanced privacy in wearable patient monitoring devices
    V Tiwari, N Jharbade, P Chourasiya, B Supraja, PS Wani, R Maurya
    2024

  6. Machine learning-based prediction of cardiovascular diseases using Flask
    V Sagar Reddy, B Supraja, M Vamshi Kumar, C Krishna Chaitanya
    2023

  7. Real time complexities of research on machine learning algorithm: A descriptive research design
    GP Dr. N. Krishna Kumar, B. Supraja, B.S. Hemanth Kumar, U. Thirupalu
    2022

  8. IT employee job satisfaction survey during Covid-19
    GVMR Dr. N. Krishna Kumar, B. Supraja
    2022

  9. Covid-19 and digital era
    GVMR Dr. N. Krishna Kumar, B. Supraja
    2022

  10. Forwarding detection and identification anomaly in software defined network
    DNKK B. Supraja, A. Venkateswatlu
    2022

  11. Machine learning structural equation modeling algorithm on logistics and supply chain management
    UT B. Supraja, Dr. N. Krishna Kumar, B.S. Hemanth Kumar, B. Saranya, G …
    2022

  12. Sentiment analysis of customer feedback on restaurants using Naïve Bayes classifier
    DNKK A. Venkateswatlu, B. Supraja
    2021

  13. Design and implementation of fog-based encrypted control system in public clouds
    DNKK B. Supraja, A. Venkateswatlu
    2021

  14. Enhancing one to many data sharing using blockchain in vehicular social networks
    DNKK B. Supraja, A. Venkateswatlu
    2021

Ling Qin | Computer Science | Best Researcher Award

Published on by WSA Awards

Ms. Ling Qin | Computer Science | Best Researcher Award

Professor from Inner Mongolia University of Science &Technology, China

Dr. Ling Qin is a dedicated and accomplished professor in the Department of Information Engineering at Inner Mongolia University of Science and Technology, China. Born in August 1979, she has established a strong academic and research background in optical communication, particularly in the areas of visible light communication (VLC), indoor positioning systems, and atmospheric laser communication. Over more than two decades of academic service at her home institution, she has progressed from teaching assistant to professor, showcasing a steady and determined career development. Dr. Qin’s research has significantly contributed to the understanding and enhancement of VLC systems in complex environments, such as intelligent transportation systems and indoor positioning applications using LED lighting. Her publication record is extensive, with numerous articles published in well-recognized journals indexed in SCI and EI. She has also successfully led multiple nationally funded research projects and holds a Chinese patent related to optical signal reception. With her expertise, innovation, and dedication, Dr. Qin exemplifies the qualities of a leading academic researcher. Her work bridges the gap between theory and practical application, making her a suitable and promising candidate for recognition in advanced communication engineering fields.

Professional Profile

Education

Dr. Ling Qin holds an impressive academic background in engineering and communication technologies. She began her higher education journey in 1997, earning a Bachelor of Engineering in Communication Engineering from Chengdu University of Information Technology in 2001. She continued to deepen her specialization in optical communication by pursuing a Master’s degree in Engineering at Xi’an University of Technology, where she studied from 2004 to 2007. Demonstrating a strong commitment to academic growth and expertise, Dr. Qin earned her Ph.D. in Engineering from Chang’an University in Xi’an between 2011 and 2018. Her doctoral research aligned closely with her professional focus, examining advanced communication theories and systems including visible light and laser-based communication. The comprehensive progression of her academic qualifications reflects her long-standing dedication to mastering both the theoretical and technical aspects of her field. These qualifications have formed a solid foundation for her research career, allowing her to contribute meaningfully to high-impact areas such as LED-based indoor positioning systems and signal processing in complex environments. Her education has not only equipped her with the necessary knowledge but has also driven her to pursue innovation and advanced research in optical communication technologies.

Professional Experience

Dr. Ling Qin has built a robust academic and professional career spanning over two decades at Inner Mongolia University of Science and Technology in Baotou, China. She began her professional journey in 2001 as a teaching assistant and steadily rose through academic ranks due to her contributions to teaching and research. Between 2007 and 2012, she served as a lecturer, where she began to engage more actively in research and curriculum development. From 2012 to 2018, she was promoted to associate professor, during which she established her research presence in visible light communication and indoor positioning systems. Since 2019, Dr. Qin has held the title of full professor, where she continues to lead research initiatives and mentor students in cutting-edge communication technologies. Throughout her career, she has taught various specialized courses, including visible light communication theory, positioning systems, and atmospheric laser communications. Her long-term affiliation with a single institution reflects both stability and deep institutional commitment, while her advancement through all faculty ranks highlights her professional development. As a professor, she plays a vital role in advancing research, guiding graduate students, and contributing to scientific innovation through her projects and publications.

Research Interests

Dr. Ling Qin’s research interests focus on key innovations in the field of optical wireless communication, particularly visible light communication (VLC), indoor positioning systems, and atmospheric laser communications. One of her primary areas of study is the development and optimization of visible light communication systems, where she explores theoretical models and practical designs to enhance LED-based communication in complex traffic and indoor environments. Her work addresses challenges such as background light interference, signal modulation, and system performance under real-world conditions. Another important focus of her research is indoor positioning technologies using LED lighting. She investigates the integration of machine learning techniques, such as convolutional and recurrent neural networks, into positioning algorithms to improve accuracy and reliability. Additionally, Dr. Qin is engaged in the research of atmospheric laser communication systems, where she works on coding theory, modulation/demodulation methods, and performance enhancement strategies for data transmission in free-space environments. Her research is interdisciplinary, often overlapping with applications in intelligent transportation, aerospace signal processing, and biomedical engineering. These interests not only reflect her command over complex engineering concepts but also demonstrate her forward-thinking approach in developing communication technologies that serve modern infrastructure and industry demands.

Research Skills

Dr. Ling Qin possesses advanced research skills that make her a leading expert in optical communication and system development. Her technical expertise includes the modeling and implementation of visible light communication (VLC) systems in challenging environments, particularly for intelligent transportation and indoor positioning. She is proficient in applying modulation and demodulation techniques, signal coding, beamforming, and error suppression in complex signal environments. Her research integrates machine learning algorithms—including convolutional neural networks (CNNs), gated recurrent units (GRUs), and transformer-based models—into communication and positioning systems to enhance accuracy and system performance. Dr. Qin is also skilled in developing system architectures using hardware components like FPGA (Field Programmable Gate Arrays), contributing to the practical realization of her theoretical models. Additionally, she has experience with spread spectrum technologies and power inversion techniques for background light suppression. Her research has also extended into interdisciplinary domains, such as carbon nanoparticle applications in medical systems and satellite navigation under plasma interference. These wide-ranging skills have been applied in various research projects funded by national and regional science foundations, demonstrating her ability to execute complex research plans and produce tangible outcomes. Her scientific rigor and technical versatility position her as a valuable asset in the field.

Awards and Honors

While Dr. Ling Qin’s profile does not list specific individual awards or honors, her consistent track record of securing competitive research funding from prestigious agencies reflects significant academic recognition. She has been awarded multiple research grants by the National Natural Science Foundation of China, supporting her projects on visible light communication, satellite navigation under plasma conditions, and laser communication systems. These grants indicate high confidence from the scientific community in the relevance and impact of her research. Additionally, she has contributed to the development of a nationally recognized patent for an optical signal receiving system, which further showcases her innovation and contribution to applied research. Her position as a full professor at Inner Mongolia University of Science and Technology is itself a recognition of her professional achievements and academic standing. Her numerous publications in high-impact journals and conferences indexed by SCI and EI are further testament to her contributions. While formal honors such as best paper or teaching awards are not noted, the cumulative evidence of her leadership in research, ability to secure funding, and innovation through patents suggests she has achieved considerable peer recognition in her field.

Conclusion

Dr. Ling Qin stands out as a strong and capable academic professional with notable contributions to the field of optical communication. Her career reflects a steady ascent through academic ranks, backed by a solid foundation in education and a deep commitment to research excellence. With a focused interest in visible light communication, indoor positioning systems, and laser-based communication technologies, she has contributed significantly to both theoretical advancements and real-world applications. Her skills in modeling complex communication systems, integrating artificial intelligence techniques, and implementing hardware-based solutions place her at the intersection of innovation and practicality. Although not heavily decorated with formal awards, her success in securing national-level research grants and her involvement in patent development speak volumes about her scientific impact. She has authored an extensive list of peer-reviewed publications that enhance her reputation and contribute to global scientific knowledge. Overall, Dr. Qin exemplifies the qualities of a modern researcher—technically skilled, innovative, and committed to advancing engineering solutions for real-world problems. Her profile makes her a highly suitable candidate for the Best Researcher Award, and recognition of her work would be well-deserved within the scientific community.

Publications Top Notes

  1. Title: CirnetamorNet: An ultrasonic temperature measurement network for microwave hyperthermia based on deep learning
    Authors: F. Cui, Y. Du, L. Qin, C. Li, X. Meng
    Year: 2025

  2. Title: Visible light channel modeling and application in underground mines based on transformer point clouds optimization
    Authors: J. Yu, X. Hu, Q. Wang, F. Wang, X. Kou
    Year: 2025

  3. Title: Fractional OAM Vortex SAR Imaging Based on Chirp Scaling Algorithm
    Authors: L. Yu, D. Yongxing Du, L. Baoshan Li, L. Qin, L. Chenlu Li
    Year: 2025

  4. Title: Indoor visible light positioning system based on memristive convolutional neural network
    Authors: Q. Chen, F. Wang, B. Deng, L. Qin, X. Hu
    Year: 2025
    Citations: 2

  5. Title: Visible light visual indoor positioning system for based on residual convolutional networks and image restoration
    Authors: D. Chen, L. Qin, L. Cui, Y. Du
    Year: 2025

Said Boumaraf | Computer Science | Environmental Engineering Impact Award

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Dr. Said Boumaraf | Computer Science | Environmental Engineering Impact Award

Researcher and AI scientist from Khalifa University, UAE

Dr. Said Boumaraf is a distinguished researcher specializing in artificial intelligence (AI), computer vision, and medical imaging. Currently serving as a Postdoctoral Fellow at Khalifa University, his work primarily focuses on developing advanced AI methodologies to address complex challenges in visual recognition and healthcare diagnostics. Dr. Boumaraf has contributed significantly to the field through his involvement in projects that enhance remote sensing of gas flares and improve face parsing techniques under occlusion conditions. His research has been published in reputable journals and conferences, reflecting his commitment to advancing technological solutions for real-world problems. Collaborating with international teams, he continues to push the boundaries of AI applications, particularly in areas that intersect with environmental monitoring and medical diagnostics. Dr. Boumaraf’s dedication to research excellence positions him as a leading figure in the integration of AI technologies into practical applications.

Professional Profile

Education

Dr. Boumaraf’s academic journey is marked by a strong foundation in computer science and engineering. He earned his Ph.D. in Computer Science, where his research focused on the development of AI algorithms for medical image analysis. His doctoral studies provided him with in-depth knowledge of machine learning, deep learning, and their applications in healthcare. Prior to his Ph.D., Dr. Boumaraf completed his Master’s degree in Computer Engineering, during which he explored various aspects of computer vision and pattern recognition. His academic pursuits have equipped him with a robust skill set that bridges theoretical understanding and practical implementation of AI technologies. Throughout his education, Dr. Boumaraf has demonstrated a commitment to interdisciplinary research, integrating principles from computer science, engineering, and healthcare to develop innovative solutions. His educational background lays the groundwork for his ongoing contributions to the field of AI and its applications in critical domains.

Professional Experience

Dr. Boumaraf’s professional experience encompasses a range of roles that highlight his expertise in AI and its applications. As a Postdoctoral Fellow at Khalifa University, he has been instrumental in leading research projects that apply deep learning techniques to environmental and medical challenges. His work includes developing AI-enhanced methods for remote sensing of gas flares and creating robust face parsing algorithms capable of handling occlusions. Prior to his current role, Dr. Boumaraf collaborated with various research institutions and industry partners, contributing to projects that required the integration of AI into practical solutions. His experience extends to developing computer-aided diagnosis systems for breast cancer detection, showcasing his ability to apply AI in critical healthcare settings. Dr. Boumaraf’s professional journey reflects a consistent focus on leveraging AI to address real-world problems, underscoring his role as a key contributor to the advancement of intelligent systems in diverse applications.

Research Interests

Dr. Boumaraf’s research interests lie at the intersection of artificial intelligence, computer vision, and medical imaging. He is particularly focused on developing deep learning models that enhance the accuracy and efficiency of image analysis in complex scenarios. His work on occlusion-aware face parsing addresses challenges in visual recognition where parts of the face are obscured, improving the reliability of facial analysis systems. In the medical domain, Dr. Boumaraf has contributed to creating AI-driven diagnostic tools that assist in the early detection of diseases such as breast cancer. His research also explores the application of AI in environmental monitoring, specifically in the remote sensing of gas flares, which has implications for energy management and environmental protection. Dr. Boumaraf’s interdisciplinary approach combines theoretical research with practical applications, aiming to develop AI solutions that can be effectively integrated into various sectors.

Research Skills

Dr. Boumaraf possesses a comprehensive set of research skills that enable him to tackle complex problems in AI and its applications. His proficiency in deep learning frameworks such as TensorFlow and PyTorch allows him to design and implement sophisticated neural network architectures. He is skilled in image processing techniques, including segmentation, feature extraction, and classification, which are essential for medical image analysis and computer vision tasks. Dr. Boumaraf is adept at handling large datasets, employing data augmentation and preprocessing methods to enhance model performance. His experience with algorithm optimization and model evaluation ensures the development of efficient and accurate AI systems. Additionally, his collaborative work with multidisciplinary teams demonstrates his ability to integrate AI solutions into broader technological and scientific contexts. Dr. Boumaraf’s research skills are instrumental in advancing AI applications across various domains.

Awards and Honors

Throughout his career, Dr. Boumaraf has received recognition for his contributions to the field of artificial intelligence. His research publications in esteemed journals and conferences have garnered attention from the academic community, reflecting the impact of his work. While specific awards and honors are not detailed in the available information, his role as a Postdoctoral Fellow at a leading institution like Khalifa University signifies a level of esteem and acknowledgment of his expertise. Dr. Boumaraf’s ongoing collaborations and research endeavors continue to position him as a respected figure in the AI research community.

Conclusion

Dr. Said Boumaraf stands out as a dedicated researcher whose work bridges the gap between artificial intelligence theory and practical application. His contributions to computer vision and medical imaging demonstrate a commitment to developing AI solutions that address real-world challenges. Through his role at Khalifa University, Dr. Boumaraf continues to engage in cutting-edge research, collaborating with international teams to push the boundaries of what AI can achieve. His interdisciplinary approach and robust research skills make him a valuable asset to the scientific community, and his work holds promise for significant advancements in both environmental monitoring and healthcare diagnostics. As AI continues to evolve, researchers like Dr. Boumaraf play a crucial role in ensuring that these technologies are harnessed effectively for the betterment of society.

Publications Top Notes

  • Title: A new transfer learning based approach to magnification dependent and independent classification of breast cancer in histopathological images
    Authors: S. Boumaraf, X. Liu, Z. Zheng, X. Ma, C. Ferkous
    Year: 2021
    Citations: 169

  • Title: Conventional machine learning versus deep learning for magnification dependent histopathological breast cancer image classification: A comparative study with visual explanation
    Authors: S. Boumaraf, X. Liu, Y. Wan, Z. Zheng, C. Ferkous, X. Ma, Z. Li, D. Bardou
    Year: 2021
    Citations: 83

  • Title: A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms
    Authors: S. Boumaraf, X. Liu, C. Ferkous, X. Ma
    Year: 2020
    Citations: 80

  • Title: A new three-stage curriculum learning approach for deep network based liver tumor segmentation
    Authors: H. Li, X. Liu, S. Boumaraf, W. Liu, X. Gong, X. Ma
    Year: 2020
    Citations: 12

  • Title: Deep distance map regression network with shape-aware loss for imbalanced medical image segmentation
    Authors: H. Li, X. Liu, S. Boumaraf, X. Gong, D. Liao, X. Ma
    Year: 2020
    Citations: 11

  • Title: A multi-scale and multi-level fusion approach for deep learning-based liver lesion diagnosis in magnetic resonance images with visual explanation
    Authors: Y. Wan, Z. Zheng, R. Liu, Z. Zhu, H. Zhou, X. Zhang, S. Boumaraf
    Year: 2021
    Citations: 10

  • Title: AI-enhanced gas flares remote sensing and visual inspection: Trends and challenges
    Authors: M. Al Radi, P. Li, S. Boumaraf, J. Dias, N. Werghi, H. Karki, S. Javed
    Year: 2024
    Citations: 6

  • Title: Web3-enabled metaverse: the internet of digital twins in a decentralised metaverse
    Authors: N. Aung, S. Dhelim, H. Ning, A. Kerrache, S. Boumaraf, L. Chen, M.T. Kechadi
    Year: 2024
    Citations: 6

  • Title: U-SDRC: a novel deep learning-based method for lesion enhancement in liver CT images
    Authors: Z. Zheng, L. Ma, S. Yang, S. Boumaraf, X. Liu, X. Ma
    Year: 2021
    Citations: 5

  • Title: Bi-Directional LSTM Model For Classification Of Vegetation From Satellite Time Series
    Authors: K. Bakhti, M.E.A. Arabi, S. Chaib, K. Djerriri, M.S. Karoui, S. Boumaraf
    Year: 2020
    Citations: 5

Elavarasi Kesavan | Computer Science | Best Industrial Research Award

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Mrs. Elavarasi Kesavan | Computer Science | Best Industrial Research Award

Full-Stack QA Architect from Cognizant, India

Mrs. Elavarasi Kesavan is an accomplished Full Stack QA Architect with over 18 years of extensive experience in software quality assurance and automation testing. She has built a robust career with a strong specialization in Salesforce platforms, web-based applications, and various automated testing tools and methodologies. Her in-depth knowledge spans end-to-end software testing processes, mobile and web service testing, ETL validation, and automation using industry-standard tools like Selenium WebDriver, TestNG, Rest Assured, and Tricentis TOSCA. She is particularly proficient in test management, having implemented seamless integrations between tools like Jira and QTest. Elavarasi has consistently demonstrated excellence in designing testing frameworks, managing offshore teams, and ensuring quality compliance throughout the Software Development Life Cycle (SDLC). Additionally, she is well-versed in Agile, Waterfall, and V-Model methodologies and excels in accessibility testing using tools like JAWS Reader. She brings technical expertise in Java, JavaScript, and Ruby to her QA automation efforts. Through her leadership roles at Cognizant and other firms, she has led teams to deliver high-quality software solutions with a focus on automation, innovation, and efficiency. Her strong communication and client engagement skills have further enhanced her value in the industrial and research sectors.

Professional Profile

Education

Mrs. Elavarasi Kesavan holds a Bachelor of Technology (B.Tech) degree in Information Technology from Anjali Ammal Mahalingam Engineering College, affiliated with Anna University, which she completed in 2006. To complement her technical foundation, she pursued and successfully earned a Master of Business Administration (MBA) in General Management from SRM Easwari Engineering College, Anna University in 2011. Her academic journey reflects a unique blend of technical proficiency and managerial acumen, which has significantly contributed to her effectiveness in leading QA initiatives and managing cross-functional teams. Her academic training in Information Technology provided a solid grounding in programming languages, databases, and web technologies, while her MBA developed her capabilities in project management, strategic planning, and team leadership. This combination has been instrumental in her ability to bridge technical expertise with business-oriented decision-making. Additionally, her continuous pursuit of professional development through various certifications in AI testing, cloud technologies, and test automation tools demonstrates her commitment to lifelong learning and staying ahead in the rapidly evolving tech industry. Her education has laid the foundation for her successful career and her capacity to contribute meaningfully to industrial research and QA architecture.

Professional Experience

Mrs. Elavarasi Kesavan brings over 18 years of progressive experience in the IT industry, primarily focusing on software quality assurance, automation, and test architecture. She currently serves as an Engineer Manager and Full Stack QA Architect at Cognizant, a role she has held since November 2022. Prior to this, she worked at Concentrix as a Technology Lead for Full Stack QA Engineering from October 2021 to November 2022. Her earlier tenure at Cognizant (2010–2021) as a Senior Associate included responsibilities such as developing and maintaining automated test frameworks, integrating QA tools with defect tracking systems, and leading cross-functional teams. She began her professional journey as a Software Developer at IBM, followed by a stint at Vayana India Pvt Ltd. Elavarasi’s hands-on experience with a variety of test management and automation tools such as Selenium, TOSCA, Postman, Jira, and QTest highlights her adaptability and technical depth. She has effectively driven the QA strategy in complex project environments, aligning quality goals with business objectives. She is recognized for her innovative solutions, strong client interactions, and mentoring capabilities. Her ability to handle diverse tools, technologies, and methodologies has cemented her as a valuable leader in the QA domain across multiple industries.

Research Interests

Mrs. Elavarasi Kesavan’s research interests lie at the intersection of software quality assurance, automation engineering, AI-driven testing, and compliance-focused application validation. She is particularly focused on developing frameworks and methodologies for efficient and scalable automation testing of web, mobile, and enterprise applications, including CRM platforms like Salesforce. Her work emphasizes scriptless automation using tools like Tricentis TOSCA and integration of AI-based testing approaches to enhance test coverage, reliability, and efficiency. She is keenly interested in security and compliance testing, aligning quality assurance practices with international standards such as GDPR, HIPAA, and PCI-DSS. Elavarasi’s exploration of testing tools that support DevOps and Agile frameworks demonstrates her commitment to continuous delivery and integration practices. Moreover, she is enthusiastic about advancing quality engineering through research on defect prediction models, test data management, and automation in cloud-native environments. Her engagement in multidisciplinary forums and conferences reveals a strong inclination toward applied industrial research. She aspires to contribute to the future of QA through intelligent automation frameworks, optimization of test cycles using AI, and expanding automation in AI/ML-based systems. These interests align with the goals of the Best Industrial Research Award by showcasing innovation and impact on real-world software engineering challenges.

Research Skills

Mrs. Elavarasi Kesavan is equipped with a comprehensive set of research and technical skills that support her contributions to industrial software testing and automation research. She is adept in using a wide array of automation tools such as Selenium WebDriver, Tricentis TOSCA, Postman, and SOAP UI. Her proficiency in developing and implementing test strategies spans data-driven and behavior-driven frameworks, including TestNG, Cucumber, Jasmine, and Rest Assured. Elavarasi has advanced capabilities in API testing, cross-browser testing, accessibility validation (JAWS), and end-to-end test management using tools like Jira and QTest. Her programming expertise includes Java, JavaScript, and Ruby, which she employs for custom test scripts and automation logic. She is skilled in web service validation, database verification (SQL, Oracle, MySQL), and cloud environment testing, complemented by hands-on experience in CI/CD tools like Jenkins and Maven. Her analytical and documentation capabilities are evident in her creation of test plans, traceability matrices, and compliance validation reports. In AI testing, she applies certified methodologies for testing machine learning models and intelligent systems. Her research-oriented approach, combined with practical application and tool proficiency, positions her as a technically strong candidate capable of innovating in industrial software quality research.

Awards and Honors

Mrs. Elavarasi Kesavan has received numerous prestigious awards and honors that reflect her excellence in technology innovation, industrial research, and leadership in software quality assurance. Notably, she was the recipient of the Distinguished Technology Award at the Dubai Dynamic Ultimate Business & Academic Iconic Awards in 2025. Her innovative contributions to IoT were recognized through the Best Patent Award for the design and development of an IoT-based multifunction agriculture robot, presented by the Scientific International Publishing House. Elavarasi also received the Best Paper Award for her work on cloud computing in Industry 4.0 at the UAE International Conference on Multidisciplinary Research and Innovation (ICMRI-2025). Additionally, she was honored with the Best Woman Researcher Award at the International Conference on Computational Science, Engineering & Technology (ICCSET-2025). Her editorial contributions were acknowledged with a Certificate of Excellence for her role as Chief Editor in Contemporary Research in Engineering, Management, and Science. Furthermore, she was recognized with a Digital Excellence Award by the CAPE Forum and a Certificate of Emerging Leader in Technology Innovation by RCS International Awards. These accolades not only highlight her technical prowess but also her impact on industrial innovation and collaborative research.

Conclusion

Mrs. Elavarasi Kesavan presents a strong and compelling case for the Best Industrial Research Award. With nearly two decades of experience in software quality assurance and a consistent record of innovation in test automation and QA strategy, she stands out as a leader who bridges technical execution with strategic foresight. Her deep expertise in automation tools, QA methodologies, compliance testing, and AI testing frameworks positions her at the forefront of industrial QA research. The recognition she has received through multiple awards and her contributions in patent development and conference presentations further reinforce her role as a pioneering professional in the field. Elavarasi’s research-oriented mindset, hands-on technical proficiency, and proven ability to lead teams and deliver enterprise-grade solutions make her a strong candidate whose work aligns with the goals of industrial research excellence. While she could benefit from further academic publications in peer-reviewed journals to bolster her academic research credentials, her real-world impact, technical acumen, and award-winning innovations clearly demonstrate her merit. Overall, Mrs. Elavarasi Kesavan exemplifies the ideal qualities of an industrial researcher whose work drives both technological advancement and practical value in the software engineering domain.

Publication Top Notes

  • Title: The Impact of Cloud Computing on Software Development: A Review
    Author: E. Kesavan
    Journal: International Journal of Innovations in Science, Engineering and Management
    Year: 2025
    Citations: 3

  • Title: AI Adapt Digital Learning in Education
    Author: E. Kesavan
    Conference: International Conference Proceeding on Innovation and Sustainable Strategies
    Year: 2025

  • Title: Explore How Digital Infrastructure Has Shaped Startup Growth
    Author: E. Kesavan
    Conference: International Conference on the Role of Innovation Policies
    Year: 2025

  • Title: Artificial Intelligence in Commerce: How Businesses Can Leverage Artificial Intelligence to Gain a Competitive Edge in the Global Marketplace
    Author: E. Kesavan
    Publication: Thiagarajar College of Preceptors, Edu Spectra
    Year: 2025

  • Title: The Evolution of Software Design Patterns: An In-Depth Review
    Author: E. Kesavan
    Journal: International Journal of Innovations in Science, Engineering and Management
    Year: 2025

  • Title: Impact of Artificial Intelligence on Software Development Processes
    Authors: SMSA Cuddapah Anitha, Nirmal Kumar Gupta, Balaji Chintala, Daniel Pilli, E. Kesavan
    Journal: Journal of Information Systems Engineering and Management
    Volume/Issue: 10 (25s), Pages 431–437
    Year: 2025

  • Title: Information and Communication Technology Development in Emerging Countries
    Author: E. Kesavan
    Journal: Journal on Electronic and Automation Engineering
    Volume/Issue: 3 (1), Pages 60–68
    Year: 2024

  • Title: Comprehensive Evaluation of Electric Motorcycle Models: A Data-Driven Analysis
    Author: E. Kesavan
    Journal: REST Journal on Data Analytics and Artificial Intelligence
    Year: 2023
    ISSN: 2583-… (incomplete in original text)

  • Title: Assessing Laptop Performance: A Comprehensive Evaluation and Analysis
    Author: E. Kesavan
    Journal: Recent Trends in Management and Commerce
    Volume: 4, Pages 175–185
    Year: 2023