0000-0003-3409-8467 About
Dr. Soharab Hossain Shaikh is a Professor at the Department of Computer Science and Engineering, BML Munjal University, India. He has received the PhD degree from University of Calcutta in 2014. Earlier he has worked as a Research Associate at Ca’ Foscari, University of Venice, Italy. Dr. Shaikh is also a certified Data Scientist. He has over 18 years of professional experience in academics and research. Along with teaching undergraduate and post-graduate students at the university, he has also been involved as a faculty/mentor to the industry professionals on subjects like Artificial Intelligence, Machine Learning, Deep Learning for Computer Vision and Natural Language Processing. Dr. Shaikh has designed and developed professional degree programmes on AI/Deep Learning for a leading edtech company in India. His research interests include solving problems involving Computer Vision, Image Processing, Natural Language Processing and applied Deep Learning. Dr. Shaikh has published over 40+ research papers in refereed journals/conferences of repute. He has also published two books with Springer-Verlag on various aspects related to Image Processing, published US-patent in his domain of expertise, contributed many book chapters. He has also served as the guest editor for Springer journal on Transactions on Computational Science, acted as the reviewers for many international journals/conferences and delivered lectures in many conferences and invited talks. He has successfully supervised three doctoral students and undergoing research activities with the existing scholars. Dr. Shaikh has been involved as a consultant with AI-based companies on projects related to Computer Vision and Deep Learning.
Employment
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BML Munjal University Professor
Education
Education history is unavailable.
Projects & Funding
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Publications (46)
- A Neural ODE and Transformer-based Model for Temporal Understanding and Dense Video Captioning Save
- Likelihood corpus distribution: an efficient topic modelling scheme for Bengali document class identification Save
- A 2-Tier Bengali Dataset for Evaluation of Hard and Soft Classification Approaches Save
- A dataset for evaluating Bengali word sense disambiguation techniques Save
- A dictionary based model for bengali document classification Save
- Fundus image classification for diabetic retinopathy using deep learning Save
- Lexeme connexion measure of cohesive lexical ambiguity revealing factor: a robust approach for word sense disambiguation of Bengali text Save
- Context based NLP framework of textual tagging for low resource language Save
- Context similarity based hybrid approach for extracting hindi multiword expressions Save
- Quantum image edge extraction based on classical robinson operator Save