Sandeep Kumar Dasa | Computer Science | Best Innovator Award

Mr. Sandeep Kumar Dasa | Computer Science | Best Innovator Award

Sr Engineer, Enterprise Data Privacy & Data Protection from Raymond James & Associates, United States

Mr. Sandeep Kumar Dasa is an accomplished technology professional with nearly nine years of experience in the IT sector. He specializes in Enterprise Data Privacy, Data Protection, and Artificial Intelligence (AI) and Machine Learning (ML). As a Senior Engineer, he plays a pivotal role in designing and implementing cutting-edge solutions that enhance data security and drive innovation. His expertise extends to thought leadership, with a strong intellectual property portfolio, including two patents. Additionally, he is an author and researcher, having published a book on AI/ML and multiple journal articles on deep learning and neural networks. Mr. Dasa is deeply invested in academic research and industry advancements, with a keen interest in reviewing papers on emerging technologies. His contributions to the field reflect his commitment to innovation and excellence, making him a valuable asset in both industry and academia.

Professional Profile

Education

Mr. Sandeep Kumar Dasa has a strong academic background that forms the foundation of his expertise in AI, ML, and data privacy. He holds a degree in Computer Science or a related field, equipping him with the necessary technical and analytical skills to excel in his profession. His education has provided him with a deep understanding of algorithm development, software engineering, and data security. Additionally, he has pursued continuous learning through certifications and specialized courses in AI, ML, and data privacy to stay at the forefront of technological advancements. His academic journey has been instrumental in shaping his innovative approach to problem-solving and research, further reinforcing his ability to contribute effectively to the field.

Professional Experience

With nearly a decade of experience in the IT industry, Mr. Sandeep Kumar Dasa has established himself as a leading expert in data privacy and AI/ML. As a Senior Engineer, he has been instrumental in designing and deploying enterprise-level solutions that enhance data protection and security. His expertise spans AI-driven automation, compliance frameworks, and advanced encryption techniques. His role involves consulting organizations on integrating AI/ML technologies to optimize efficiency and security. His professional journey includes collaborating with cross-functional teams, leading research-driven projects, and implementing patented innovations. His ability to merge theoretical knowledge with practical applications has enabled him to make a significant impact in the field.

Research Interest

Mr. Sandeep Kumar Dasa is deeply passionate about research in AI, ML, and data privacy. His primary focus lies in developing advanced AI models that enhance data security while ensuring regulatory compliance. He is particularly interested in deep learning, neural networks, and their applications in data protection. His research explores ways to leverage AI for secure data handling, risk mitigation, and automation. Additionally, he is keen on understanding the ethical implications of AI and ensuring responsible AI deployment. His commitment to research is reflected in his publications, patents, and active involvement in scholarly discussions. He seeks to contribute to the field by exploring novel AI-driven solutions for industry challenges.

Research Skills

Mr. Sandeep Kumar Dasa possesses a robust set of research skills that make him an effective innovator and thought leader in AI, ML, and data privacy. His expertise includes AI model development, deep learning, statistical analysis, and algorithm optimization. He is proficient in data protection methodologies, cryptographic techniques, and regulatory compliance standards. His technical skills encompass programming in Python, R, and other AI-focused languages, along with experience in cloud computing and big data analytics. Additionally, his ability to critically analyze emerging trends and apply research methodologies enables him to contribute valuable insights to the industry. His strong research acumen allows him to bridge the gap between theoretical advancements and practical applications.

Awards and Honors

Mr. Sandeep Kumar Dasa’s contributions to AI, ML, and data privacy have earned him notable recognition. He holds two patents that highlight his innovative capabilities in technology development. His book on AI/ML and multiple journal publications have established him as a thought leader in the field. He has been invited to review research papers on emerging technologies, demonstrating his expertise and credibility. Throughout his career, he has received accolades for his impactful work, including industry awards and acknowledgments for excellence in innovation. His dedication to research and technology has positioned him as a respected professional in his domain.

Conclusion

Mr. Sandeep Kumar Dasa is a distinguished professional with a strong background in AI, ML, and data privacy. His extensive experience, combined with his research contributions and innovative mindset, make him a valuable leader in the technology industry. His patents, publications, and professional expertise showcase his commitment to advancing the field. While he has already achieved significant milestones, continued collaboration, real-world implementation of his innovations, and further recognition in the industry could enhance his impact. His passion for research, dedication to knowledge-sharing, and technical proficiency make him a deserving candidate for awards and honors in technology and innovation.

Publications Top Notes

  • Optimizing Object Detection in Dynamic Environments With Low-Visibility Conditions

    • Authors: S. Belidhe, S.K. Dasa, S. Jaini

    • Citations: 3

  • Explainable AI and Deep Neural Networks for Continuous PCI DSS Compliance Monitoring

    • Authors: S.K.D. Sandeep Belidhe, Phani Monogya Katikireddi

    • Year: 2024

  • Proactive Database Health Management with Machine Learning-Based Predictive Maintenance

    • Authors: S.K. Dasa

    • Year: 2023

  • Graph-Based Deep Learning and NLP for Proactive Cybersecurity Risk Analysis

    • Authors: S.K. Dasa

    • Year: 2022

  • Securing Database Integrity: Anomaly Detection in Transactional Data Using Autoencoders

    • Authors: S.K. Dasa

    • Year: 2022

  • Autonomous Robot Control through Adaptive Deep Reinforcement Learning

    • Authors: S.K. Dasa

    • Year: 2022

  • Using Deep Reinforcement Learning to Defend Conversational AI Against Adversarial Threats

    • Authors: S.K.D. Phani Monogya Katikireddi, Sandeep Belidhe

    • Year: 2021

  • Machine Learning Approaches for Optimal Resource Allocation in Kubernetes Environments

    • Authors: S.B. Sandeep Kumar Dasa, Phani Monogya Katikireddi

    • Year: 2021

  • Intelligent Cybersecurity: Enhancing Threat Detection through Hybrid Anomaly Detection Techniques

    • Authors: S.B. Phani Monogya Katikireddi, Sandeep Kumar Dasa

    • Year: 2021

 

 

 

 

 

 

Akmalbek Abdusalomov | Computer Science | Best Researcher Award

Assist Prof Dr. Akmalbek Abdusalomov | Computer Science | Best Researcher Award

Assistant Professor Computer Engineering Department of Gachon University, South Korea.

Dr. Abdusalomov Akmalbek Bobomirzaevich is an Assistant Professor at Gachon University, South Korea, with a specialization in computer vision and artificial intelligence. He holds a PhD in Computer Engineering from Gachon University, where his research focused on moving shadow detection using texture and geometry features. His work encompasses digital image processing, machine learning, and AI, with notable projects in moving object detection, virtual reality for blindness, and AI-based healthcare device development. Dr. Abdusalomov has published extensively, with a Google Scholar h-index of 23 and a Scopus h-index of 19. His academic and research contributions are complemented by his roles as a part-time instructor, postdoctoral researcher, and associate professor at Tashkent State University of Economics.

Professional Profiles:

Education

Abdusalomov Akmalbek Bobomirzaevich earned his Bachelor’s degree in Software Engineering from Tashkent University of Information Technology, Uzbekistan, with a GPA of 93%. His thesis focused on developing an online chemist application for Android. He then pursued a Master’s degree in IT Convergence Engineering at Gachon University, South Korea, achieving a GPA of 4.28 out of 4.50. His master’s thesis, under the guidance of Taeg Keun Whangbo, was on improving foreground recognition methods using shadow removal techniques. Continuing at Gachon University, Akmalbek completed his PhD in Computer Engineering, with a GPA of 4.17 out of 4.50. His doctoral research, also supervised by Taeg Keun Whangbo, explored moving shadow detection using texture and geometry features for indoor environments.

Professional Experience

Abdusalomov Akmalbek Bobomirzaevich has accumulated extensive experience in academia and industry. He began his career as an intern at Bulungur College of National Handicraft in 2013, followed by a role as an Assistant Engineer at Tashkent Electronic Research Center, where he handled billing systems and customer support. In 2015, he worked as an Administrator at Ipak Yuli Bank, focusing on network configuration and troubleshooting. From 2015 to 2017, he served as a Research Assistant at Gachon University’s Content Technologies Laboratory, where he managed lab devices and collaborated on projects. He then taught IT subjects as a Full-Time Instructor at Tashkent University of Information Technology. Akmalbek returned to Gachon University as a Researcher, later becoming a Postdoctoral Researcher in AI Engineering. Since 2022, he has been an Assistant Professor at Gachon University, focusing on deep learning and image processing, and an Associate Professor at Tashkent State University of Economics.

Research Interest

Abdusalomov Akmalbek’s research interests lie in the fields of digital image processing, computer vision, and artificial intelligence. His work primarily focuses on developing advanced techniques in machine and deep learning to enhance object detection and recognition. He has explored moving shadow detection using texture and geometry features for indoor environments, aiming to improve foreground recognition methods. His research also includes contributions to the development of smart technology for enhanced safety and accessibility, such as smart suits and virtual reality games for individuals with visual impairments. Akmalbek is dedicated to advancing the capabilities of AI and computer vision through innovative methodologies and practical applications.

Award and Honors

Abdusalomov Akmalbek has received several prestigious awards acknowledging his outstanding contributions to computer vision and artificial intelligence. He was honored with the Best Paper Award at the International Conference on Computer Vision and Pattern Recognition (CVPR) for his innovative research on moving object detection. Additionally, he earned the Outstanding Researcher Award from Gachon University for his significant advancements in deep learning models and image processing techniques. His work on virtual reality games for the visually impaired and the commercialization of mobile Braille pads garnered him the Innovative Research Award from the Commercialization Research Agency. Furthermore, Akmalbek was recognized with the Excellence in Teaching Award at Tashkent State University of Economics for his impactful instruction in artificial intelligence and related fields.

 Research Skills

Abdusalomov Akmalbek possesses a diverse set of research skills essential for advancing the fields of computer vision and artificial intelligence. He is proficient in digital image processing, machine and deep learning, and artificial intelligence. His expertise includes utilizing Python and C++ for programming, with a strong focus on OpenCV for computer vision tasks. Akmalbek has significant experience in moving object detection and foreground recognition, particularly in indoor environments. He excels in developing and applying deep learning models, including shadow removal techniques and texture and geometry-based feature detection. His skills extend to image stitching, virtual reality development, and medical big data analysis. Additionally, he has contributed to ICT element technology development and AI-based healthcare device development, showcasing his ability to work on complex, cutting-edge research projects.

Publications
  1. “An improvement of the fire detection and classification method using YOLOv3 for surveillance systems”
    • Authors: A Abdusalomov, N Baratov, A Kutlimuratov, TK Whangbo
    • Year: 2021
    • Citations: 87
  2. “Automatic Speaker Recognition Using Mel-Frequency Cepstral Coefficients Through Machine Learning”
    • Authors: U Ayvaz, H Gürüler, F Khan, N Ahmed, T Whangbo, AA Bobomirzaevich
    • Year: 2022
    • Citations: 85
  3. “Automatic fire and smoke detection method for surveillance systems based on dilated CNNs”
    • Authors: Y Valikhujaev, A Abdusalomov, YI Cho
    • Year: 2020
    • Citations: 69
  4. “Brain tumor detection based on deep learning approaches and magnetic resonance imaging”
    • Authors: AB Abdusalomov, M Mukhiddinov, TK Whangbo
    • Year: 2023
    • Citations: 63
  5. “An improved forest fire detection method based on the detectron2 model and a deep learning approach”
    • Authors: AB Abdusalomov, BMDS Islam, R Nasimov, M Mukhiddinov, TK Whangbo
    • Year: 2023
    • Citations: 62
  6. “Automatic fire detection and notification system based on improved YOLOv4 for the blind and visually impaired”
    • Authors: M Mukhiddinov, AB Abdusalomov, J Cho
    • Year: 2022
    • Citations: 56
  7. “LDA-based topic modeling sentiment analysis using topic/document/sentence (TDS) model”
    • Authors: A Farkhod, A Abdusalomov, F Makhmudov, YI Cho
    • Year: 2021
    • Citations: 53
  8. “Improved real-time fire warning system based on advanced technologies for visually impaired people”
    • Authors: AB Abdusalomov, M Mukhiddinov, A Kutlimuratov, TK Whangbo
    • Year: 2022
    • Citations: 52
  9. “Attention 3D U-Net with Multiple Skip Connections for Segmentation of Brain Tumor Images”
    • Authors: J Nodirov, AB Abdusalomov, TK Whangbo
    • Year: 2022
    • Citations: 50