Tag: AI Excellence Prize

Sami Ullah Khan | Artificial Intelligence | Best Faculty Award

Published on by World Science Awards

Dr. Sami Ullah Khan | Artificial Intelligence | Best Faculty Award

Chairperson/Assistant Professor from Gomal University DIK Pakistan, Pakistan

Dr. Sami Ullah Khan is a dedicated academic and researcher in the field of Physical Chemistry, currently serving as an Assistant Professor at the Department of Chemistry, Government College University Faisalabad, Pakistan. With a Ph.D. in Physical Chemistry from Quaid-i-Azam University, Islamabad, Dr. Khan has been actively contributing to academia through teaching, research, and scientific collaboration. His academic journey reflects a blend of rigorous scholarship and a passion for innovation, particularly in areas related to materials chemistry, nanotechnology, and green chemistry. He has supervised numerous postgraduate research projects and published several impactful articles in peer-reviewed international journals. Dr. Khan has also participated in national and international conferences, workshops, and training programs, which have strengthened his academic network and research profile. He is committed to fostering an environment that encourages curiosity, analytical thinking, and scientific inquiry among students. His dedication to academic excellence and societal impact has earned him recognition within Pakistan’s scientific community. As a forward-looking scholar, Dr. Khan continues to explore sustainable and cutting-edge approaches to scientific problems, integrating his research expertise with his teaching practices. His work exemplifies the values of intellectual rigor, integrity, and a commitment to advancing knowledge in physical and environmental chemistry.

Professional Profile

Education

Dr. Sami Ullah Khan has built a strong educational foundation that supports his expertise in Physical Chemistry and related scientific domains. He earned his Ph.D. in Physical Chemistry from the prestigious Quaid-i-Azam University in Islamabad, Pakistan. His doctoral research focused on thermodynamic and kinetic aspects of chemical reactions and advanced material analysis, providing him with in-depth knowledge and practical experience in modern analytical techniques and experimental design. Prior to his doctoral studies, he completed his MPhil and MSc in Chemistry, also from Quaid-i-Azam University, with a specialization in Physical Chemistry. His academic performance has consistently been excellent, marked by distinctions and active participation in scientific events. Throughout his educational journey, Dr. Khan developed a strong command of theoretical frameworks as well as laboratory-based applications. His exposure to diverse scientific environments and challenging academic tasks enabled him to gain hands-on experience with state-of-the-art instrumentation and computational tools. This robust academic background has not only shaped his research capabilities but also prepared him to contribute effectively to teaching and mentorship roles. The combination of rigorous coursework, experimental research, and scientific communication formed the cornerstone of Dr. Khan’s expertise, laying the groundwork for a successful academic and research career.

Professional Experience

Dr. Sami Ullah Khan brings extensive professional experience in academia, particularly within the realm of higher education and scientific research. He currently serves as an Assistant Professor in the Department of Chemistry at Government College University Faisalabad, a position he has held since completing his doctoral studies. In this role, he teaches both undergraduate and postgraduate courses in Physical Chemistry, and supervises MSc and MPhil research projects. Dr. Khan’s academic career is characterized by a balance of teaching, research, and administrative duties, reflecting his versatility as a scholar and educator. His teaching philosophy emphasizes interactive learning, critical thinking, and research-driven instruction. Previously, he worked as a lecturer and research associate at various reputable institutions in Pakistan, contributing to curriculum development, academic advising, and scientific outreach initiatives. He has also been involved in research collaborations with other universities, enhancing his exposure to interdisciplinary scientific approaches. Dr. Khan’s commitment to excellence in teaching has been recognized through positive student feedback and peer evaluations. Furthermore, he has actively contributed to academic committees and organized workshops aimed at promoting scientific literacy and research skills among students. His professional journey is marked by a deep commitment to nurturing future scientists and advancing the field of chemistry.

Research Interest

Dr. Sami Ullah Khan’s research interests lie primarily in the fields of Physical Chemistry, Nanotechnology, Environmental Chemistry, and Green Chemistry. His work focuses on understanding the fundamental properties and behavior of chemical systems through thermodynamics, kinetics, and surface chemistry. A significant part of his research investigates the synthesis, characterization, and application of nanomaterials for environmental and industrial applications. Dr. Khan is particularly interested in exploring eco-friendly synthesis routes for nanoparticles, utilizing plant extracts and other green methods to reduce the use of toxic chemicals. This aligns with his interest in sustainable development and the minimization of environmental impact through innovative chemical processes. He also explores photocatalysis, adsorption phenomena, and the development of advanced functional materials for water treatment and pollution control. His interdisciplinary approach combines experimental techniques with computational modeling to gain a comprehensive understanding of material behavior at the molecular level. Dr. Khan’s research aims to address real-world problems such as water contamination, energy efficiency, and industrial waste management. By integrating principles of chemistry with environmental science, he contributes to the development of practical solutions for sustainable living. His research has been widely published in reputed scientific journals, and he actively seeks collaboration with fellow researchers in complementary fields.

Research Skills

Dr. Sami Ullah Khan possesses a broad range of research skills that make him a valuable contributor to the field of Physical Chemistry and materials science. His expertise includes the design and execution of experimental studies involving thermodynamic and kinetic measurements, surface chemistry analysis, and the synthesis of nanomaterials using both conventional and green chemistry methods. He is proficient in the use of advanced instrumentation such as UV-Vis spectroscopy, FTIR, XRD, SEM, and TGA for characterizing chemical compounds and nanomaterials. Dr. Khan is also skilled in computational chemistry tools used for modeling reaction mechanisms and predicting molecular interactions. His laboratory management skills ensure strict adherence to safety protocols and efficient coordination of research projects. Moreover, he demonstrates strong data analysis capabilities, employing statistical software and graphical tools to interpret experimental results accurately. Dr. Khan also excels in scientific writing and communication, as evidenced by his publication record and active participation in scientific conferences. He is an effective research mentor, guiding postgraduate students in thesis development, lab techniques, and research ethics. His ability to combine technical knowledge with analytical reasoning and teamwork contributes to the success of interdisciplinary projects and the overall enhancement of the research culture at his institution.

Awards and Honors

Throughout his academic journey, Dr. Sami Ullah Khan has received multiple awards and honors in recognition of his scholarly excellence and research contributions. He has been acknowledged for his outstanding performance during his Ph.D. studies, receiving institutional accolades for academic achievement and scientific impact. Dr. Khan has also been a recipient of research grants and travel fellowships to present his work at national and international conferences, which have further validated the importance and relevance of his research in the scientific community. His research papers have been published in high-impact journals, some of which have earned citation awards and commendations from reviewers and editorial boards. He has been recognized for his role in mentoring graduate students and fostering academic growth through innovative teaching practices. Moreover, Dr. Khan has participated in scientific workshops and symposiums where he has received certificates of merit for his contributions as a speaker and panelist. These accolades reflect not only his competence as a researcher but also his commitment to promoting scientific knowledge and education. The honors serve as milestones in his career, motivating him to pursue excellence in research, teaching, and community service within the broader field of chemistry.

Conclusion

Dr. Sami Ullah Khan stands out as a passionate educator, dedicated researcher, and forward-thinking academic in the realm of Physical Chemistry. His journey from student to Assistant Professor reflects a consistent commitment to scientific inquiry, sustainable innovation, and educational excellence. With a solid academic foundation and diverse professional experience, he has contributed significantly to both teaching and research at Government College University Faisalabad. His work in nanotechnology, environmental remediation, and green chemistry not only advances scientific understanding but also addresses critical global challenges. Through his teaching, Dr. Khan inspires the next generation of chemists by encouraging analytical thinking, hands-on experimentation, and ethical research practices. His collaborative spirit and strong research skills have resulted in numerous publications, successful student theses, and impactful scientific engagements. Recognized through various awards and honors, Dr. Khan exemplifies the qualities of a modern scientist—curious, conscientious, and committed to positive change. As he continues to expand his academic reach and explore new frontiers in chemistry, Dr. Khan remains a valuable asset to the scientific and educational community. His work is a testament to the transformative power of knowledge, persistence, and a deep-seated passion for the chemical sciences.

Publications Top Notes

  1. Oblique stagnation point flow of nanofluids over stretching/shrinking sheet with Cattaneo–Christov heat flux model: existence of dual solution

    • Authors: X. Li, A.U. Khan, M.R. Khan, S. Nadeem, S.U. Khan

    • Year: 2019

    • Citations: 96

  2. Common fixed point results for new Ciric-type rational multivalued F-contraction with an application

    • Authors: T. Rasham, A. Shoaib, N. Hussain, M. Arshad, S.U. Khan

    • Year: 2018

    • Citations: 64

  3. Common fixed points for multivalued mappings in G-metric spaces with applications

    • Authors: Z. Mustafa, M. Arshad, S.U. Khan, J. Ahmad, M.M.M. Jaradat

    • Year: 2017

    • Citations: 44

  4. Fixed point results for F-contractions involving some new rational expressions

    • Authors: M. Arshad, S.U. Khan, J. Ahmad

    • Year: 2016

    • Citations: 44

  5. Complex T-spherical fuzzy relations with their applications in economic relationships and international trades

    • Authors: A. Nasir, N. Jan, M.S. Yang, S.U. Khan

    • Year: 2021

    • Citations: 41

  6. Two new types of fixed point theorems for F-contraction

    • Authors: S.U. Khan, M. Arshad, A. Hussain, M. Nazam

    • Year: 2016

    • Citations: 36

  7. Investigation of cyber-security and cyber-crimes in oil and gas sectors using the innovative structures of complex intuitionistic fuzzy relations

    • Authors: N. Jan, A. Nasir, M.S. Alhilal, S.U. Khan, D. Pamucar, A. Alothaim

    • Year: 2021

    • Citations: 34

  8. Medical diagnosis and life span of sufferer using interval valued complex fuzzy relations

    • Authors: A. Nasir, N. Jan, A. Gumaei, S.U. Khan

    • Year: 2021

    • Citations: 30

  9. Cybersecurity against the loopholes in industrial control systems using interval-valued complex intuitionistic fuzzy relations

    • Authors: A. Nasir, N. Jan, A. Gumaei, S.U. Khan, F.R. Albogamy

    • Year: 2021

    • Citations: 29

  10. τ− Generalization of fixed point results for F− contraction

  • Authors: A. Hussain, M. Arshad, S.U. Khan

  • Year: 2015

  • Citations: 29

 

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Published on by World Science Awards

Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178