Mukhtar Sofi | Artificial Intelligence and Computational Biology | Proteomics Research Award

Dr. Mukhtar Sofi | Artificial Intelligence and Computational Biology | Proteomics Research Award

Assistant Professor at VIT Vellore, India

Dr. Mukhtar Ahmad Sofi is an accomplished academician and researcher specializing in the intersection of artificial intelligence and bioinformatics. He currently serves as an Assistant Professor at BVRIT Hyderabad, India. With a robust foundation in computer science, Dr. Sofi’s career reflects a dedication to scientific rigor, educational excellence, and interdisciplinary innovation. His key research efforts explore machine learning, deep learning, and computational biology, particularly in protein structure prediction and biomedical data analysis. Dr. Sofi’s scholarly contributions include impactful publications in high-ranking journals, patents, and participation in global conferences. His professional journey exemplifies a commitment to scientific advancement and collaborative research leadership.

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Education

Dr. Sofi earned his Ph.D. in Computer Science and Engineering from the University of Kashmir between 2019 and 2023, awarded officially in 2024. Prior to his doctoral work, he completed an M.Tech in Computer Science and Engineering (2015–2017) from Pondicherry Central University with a CGPA of 8.72. He also holds a Master’s in Computer Applications (2011–2014) from the same university, graduating with a CGPA of 8.51. His undergraduate degree, a BCA in Computer Science, was obtained from the University of Kashmir (2008–2011) with 62% marks. These academic milestones have equipped him with a rigorous theoretical and applied understanding of computer science and its emerging domains.

Experience

Dr. Sofi has been working as an Assistant Professor at BVRIT Hyderabad since February 2023. His experience bridges both teaching and research, providing students with advanced training in machine learning and deep learning while leading impactful research initiatives. Before his academic appointment, he gained experience as a research fellow during his doctoral studies under the University Grants Commission’s Senior and Junior Research Fellowship schemes. Additionally, Dr. Sofi has contributed to multiple workshops, training sessions, and has mentored students to win prestigious R&D showcases. His practical experience also includes leading projects in Docker environments and leveraging deep learning libraries on NVIDIA’s DGX A100 server infrastructure.

Research Interest

Dr. Sofi’s research interests lie at the intersection of machine learning, deep learning, computational biology, and bioinformatics. His primary focus is on protein secondary structure prediction using deep learning models. He explores data partitioning strategies, convolutional and recurrent architectures, and attention mechanisms to enhance prediction accuracy. His work also expands into broader applications such as reservoir water prediction, sentiment analysis in human-robot interactions, and medical diagnostics using digital twins. Through his research, Dr. Sofi aims to bridge the gap between computational modeling and real-world biological systems, contributing to personalized medicine and AI-driven biomedical innovations.

Awards

Among Dr. Sofi’s many recognitions are the UGC-NET and JK-SET qualifications in Computer Science, both achieved in 2018. He was awarded Senior and Junior Research Fellowships by UGC for his Ph.D. studies. He received a grant of ₹3.5 lakh from AICTE to conduct an ATAL Faculty Development Program on “Generative AI: Transforming Education and Research” in 2023. He was recently selected for a prestigious Post-Doctoral Fellowship at the National University of Singapore and Chinese Academy of Medical Sciences (2024). Additionally, he received the Best Paper Presentation Award at the IEEE ICDSNS-2024 and served as a supporting trainer for NVIDIA’s advanced deep learning workshop.

Publications

Dr. Sofi’s impactful scholarly work includes the following publications:

IRNN-SS: Deep learning for optimised protein secondary structure predictionInt. J. Bioinformatics Research and Applications, 2024. Cited by: 2.

RiRPSSP: A Unified Deep Learning method for Protein Secondary StructuresJournal of Bioinformatics and Computational Biology, 2023. Cited by: 8.

Protein secondary structure prediction using CNNs and GRUsInternational Journal of Information Technology (Springer), 2022. Cited by: 14.

Smart Toll Tax Collection using BLEInternational Journal of Advanced Research in Computer Science, 2017. Cited by: 5.

Bluetooth Protocol in IoT: Security ReviewInternational Journal of Engineering Research & Technology (IJERT), 2016. Cited by: 11.

Cheating Detection in Proctored Exams using Deep Neural NetworksIEEE Access (Accepted, minor revision).

Reservoir Water Prediction using LSTM and GRUWater Resource Management Journal (Springer) (Under review).

These publications highlight Dr. Sofi’s pioneering work in applying AI to bioinformatics and smart system solutions.

Conclusion

Dr. Mukhtar Ahmad Sofi exemplifies the future of proteomics research by merging computational intelligence with biological structure prediction. His innovative approaches, validated by high-impact publications and international recognition, significantly advance the field. Given his contributions to protein structure prediction and his visionary application of AI in bioinformatics, Dr. Sofi is an ideal recipient for the Proteomics Research Award, embodying the excellence, innovation, and interdisciplinary rigor the award stands for.

Abdelrahman Elgohr | Bioinformatics | Best Researcher Award

Dr.Abdelrahman Elgohr | Bioinformatics | Best Research Article Award

Mechatronics engineering department, faculty of engineering at Horus University Egypt, Egypt.

Dr. Abdelrahman Tarek Elgohr is an Assistant Lecturer in Mechatronics Engineering at Horus University, Egypt, with a strong research focus on robotics, artificial intelligence, and brain-computer interfaces. He holds an MSc from Zagazig University and is currently pursuing his PhD at Mansoura University. Dr. Elgohr has published extensively in top-tier journals, contributed to cutting-edge work on robotic arm optimization and EEG signal analysis, and is a certified Huawei AI instructor. His blend of academic leadership, technical expertise, and innovative research makes him a rising figure in applied mechatronics and intelligent systems.

🎓 Academic Background:

Dr. Abdelrahman Tarek Elgohr is a distinguished Mechatronics Engineer and academic, currently serving as an Assistant Lecturer at the Faculty of Engineering, Horus University, Egypt. He holds a Master of Science in Mechatronics Engineering from Zagazig University, where he conducted advanced research on brain-controlled robotic systems. Currently, he is pursuing a Ph.D. in Mechatronics Engineering at Mansoura University, having achieved excellence in courses covering nonlinear control systems, intelligent technologies, and advanced robotics.

Profile:

📚 Research Expertise:

Dr. Elgohr’s research lies at the dynamic intersection of robotics, artificial intelligence, and biomedical systems. His master’s thesis focused on the development of a brain-controlled robotic arm using deep learning and optimization algorithms, demonstrating innovation in both AI application and mechanical control. He has authored over 13 peer-reviewed publications in internationally indexed journals such as Elsevier, Wiley, IEEE Xplore, and the Journal of Engineering Research, covering diverse topics from EEG signal classification to sustainable energy systems and robotic path planning.

🧠 Teaching and Academic Contributions:

With over six years of teaching experience at Horus University, Dr. Elgohr has played a vital role in shaping the academic journey of future engineers. He teaches a broad range of courses, including Robotics Engineering, Motion Control, CAD Design, and Electrical Circuits. He also serves as the Head of the Robotics Laboratory and contributes to quality assurance, student advising, and curriculum development—particularly in the university’s Artificial Intelligence program.

🛠️ Technical Skills and Certifications:

Dr. Elgohr possesses strong technical proficiency across several platforms and tools. He is skilled in programming languages such as C, Python, and MATLAB, and has hands-on experience with TensorFlow and SolidWorks. His certifications include Huawei HCIA AI Instructor, SolidWorks Associate, Siemens PLC Programming, and multiple professional development courses offered by DAAD Egypt, including proposal writing and fundraising.

🌟 Achievements and Roles:

Beyond research and teaching, Dr. Elgohr is actively engaged in academic service. He has advised over 80 students, served on examination and academic scheduling committees, and is an IEEE Horus Student Branch monitor. Notably, he is the first Huawei AI Certified Instructor at Horus University. His academic leadership and organizational skills continue to strengthen the university’s robotics and AI ecosystem.

Publications:

  1. A Comprehensive Review on Hybridization in Sustainable Desalination Systems
    Membranes, 2025.

  2. Path Planning for a 6 DoF Robotic Arm Based on Whale Optimization Algorithm and Genetic Algorithm
    Journal of Engineering Research, 2023.

  3. Trajectory Optimization for a 6 DOF Robotic Arm Based on Reachability Time
    Annals of Emerging Technologies in Computing, 2024.

  4. Enhancing Conical Solar Stills with Aluminum Ball Energy Storage: Optimal Distance for Improved Performance
    Journal of Energy Storage, 2024.

  5. Multi-Classification Model for Brain Tumor Early Prediction Based on Deep Learning Techniques
    Journal of Engineering Research, 2024.

  6. A Novel Hybrid Deep Neural Network Classifier for EEG Emotional Brain Signals
    International Journal of Advanced Computer Science and Applications, 2024.

  7. Whale-Based Trajectory Optimization Algorithm for 6 DOF Robotic Arm
    Annals of Emerging Technologies in Computing, 2024.

  8. Modeling of Heat Transfer and Airflow Inside Evacuated Tube Collector with Heat Storage Media: Experimental Validation Powered by Artificial Neural Network
    Heat Transfer, 2025.

  9. Performance Evaluation of a Standalone Solar-Powered Irrigation System in Desert Regions Using PVsyst: A Comprehensive Analysis
    25th International Middle East Power System Conference (MEPCON), 2024.

  10. Comparative Analysis for Accurate Multi-Classification of Brain Tumor Based on Significant Deep Learning Models
    Computers in Biology and Medicine, 2025.

  11. Advancements in Photovoltaic Technology: A Comprehensive Review of Recent Advances and Future Prospects
    Energy Conversion and Management: X, 2025.

  12. Trajectory Optimization for 6 DOF Robotic Arm Using WOA, GA, and Novel WGA Techniques
    Results in Engineering, 2025.

  13. Innovative Electrode Design and Catalytic Enhancement for High-Efficiency Hydrogen Production in Renewable Energy Systems
    Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2025.

  14. Early Lung Cancer Detection with a Fusion of Inception V3 and Vision Transformers: A Binary Classification Study
    International Conference on Future Telecommunications and Artificial Intelligence (FutureTech), 2024.

  15. Enhancing Urban Park Connectivity and User Experience Through Space Syntax Analysis with Environmental Performance Analysis: A Case Study in New Damietta City, Egypt
    Urban Studies – Egypt, 2024.