About Me

Profile Summary

Dr. Mohsin Furkh Dar is currently serving as an Assistant Professor in the School of Computer Science at UPES Dehradun. His academic and research work focuses on deep learning, medical image analysis, and the design of efficient and generalizable neural architectures. His doctoral contributions include EfficientU-Net, UMA-Net, fuzzy–rough set based loss functions, and SGAN frameworks for medical image segmentation and classification. He has published in SCIE-indexed journals and presented at international conferences. He also maintains an academic profile at mohsinfurkh.github.io.

In addition to his research pursuits, Dr. Dar has significant teaching experience at both undergraduate and postgraduate levels, delivering courses in computer science, artificial intelligence, and data-driven technologies with a strong emphasis on hands-on learning. He combines theoretical model development with practical system implementation and has built AI-driven applications such as ShifaAI. He also supervises student projects in computer vision, deep learning, and applied machine learning.

Work Experience

Research Interests

Teaching Philosophy

Dr. Dar follows a learner-centric teaching philosophy that blends strong theoretical foundations with hands-on, experiential learning. He actively incorporates collaborative learning techniques such as Think-Pair-Share, Jigsaw, structured problem-solving, and peer instruction to promote deeper understanding and student engagement.

His approach emphasizes conceptual clarity, reproducible experimentation, and real-world applications using authentic datasets. He integrates continuous feedback, incremental projects, and reflective learning practices to help students develop analytical thinking, practical engineering skills, and independent research capability.

Courses Taught

Education

Awards and Grants

Scholarly Activities

Dr. Dar has contributed to peer-reviewed research in medical image analysis, deep learning, and fuzzy–rough set based learning methods. His work includes SCIE and Scopus-indexed journal publications on neural network architectures, ensemble-based classification, and evolutionary feature selection. He has presented his findings at international conferences, including ICCCNet, and has attended multiple specialized workshops on MRI, EEG, and NLP research. He has also mentored graduate and undergraduate research projects involving deep learning, image processing, and applied machine learning.

Research IDs

Skills