Dr. M. Sohel Rahman is a Professor of the CSE department of BUET. He had worked as a Visiting Research Fellow of King’s College London, UK during 2008-2011 and again as a Visiting Senior Research Fellow there during 2014-15. He is a Senior Member of both IEEE and ACM; member of American Mathematical Society (AMS) and London Mathematical Society (LMS). He is also a Peer-review Associate College Member of EPSRC, UK.
Dr. Rahman received different scholarships and fellowships including Commonwealth Scholarship, Commonwealth Fellowship, ACU Titular Fellowship, University College London-Big Data Institute visiting grant, London Mathematical Society Visiting Grant etc. He is also a recipient of the Bangladesh Academy of Sciences Gold Medal and UGC Award. He has led research and development projects funded by British Council, UGC-World Bank, ICT Division, Government of Bangladesh and BUET. He has so far published 86 peer-reviewed international journal papers. Among his notable results are the work on high dimensional Knapscak problems, sequence alignment problems, data structures and string combinatorics, sufficient conditions for Hamiltoninicity, Machine Learning based predictors in Bioinformatics, and metaheuristics solutions for hard problems.
He is an Academic Editor of PLOS One, Associate Editor of BMC Research Notes and had edited special issues as guest editors in Theoretical Computer Science, Journal of Graph Algorithms and Applications, Journal of Discrete Algorithms, Fundamenta Informaticae etc. He has also served as Program Committee members in a number of conference series’ of international repute. Dr. Rahman regularly writes reviews at Mathematical Review and ACM Computing Review.
He is a Senior Member of ACM since 2017. He was the founding Vice Chairman of BUET ACM Chapter and the incumbent Chairman thereof. He regularly writes reviews at ACM Computing Review.
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Prediction based on biological sequences (where Machine Learning meets Life Sciences)
Due to the rapid development of fast sequencing technologies, we now have tremendous amount data on different biological sequences. For example, the number of sequence-known proteins has...
- String Inference and (non)Lexicographic OrderingIn this lecture we will discuss two interesting but possibly less studied topics from string combinatorics. We will divide the talk into two parts. In the first part, we will briefly present...
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- String Inference and (non)Lexicographic Ordering