Syed Mohtashim Abbas Bokhari, PhD

Assistant Professor

Dr. Syed Mohtashim Abbas Bokhari serves as an Assistant Professor of Computer Science and Artificial Intelligence at Canisius University in New York, USA. He holds a Ph.D. Degree in Engineering and Computer Science, an M.S. in Software Engineering, and a B.S. in Computer Science. With over a decade of teaching, industry, and research experience in international settings, Dr. Bokhari has previously been affiliated with Columbia University in New York City, Oldenburg University in Germany, and Linköping University in Sweden. His research in Germany was funded by the prestigious German Research Foundation (DFG). 

Dr. Bokhari has worked and lived in diverse cultural environments across Europe, Asia, and North America. He has received numerous scholarships and was offered several positions at leading universities in the USA, Germany, Australia, Sweden, Spain, and South Korea. He has presented and published his academic work in leading conferences, prestigious journals, and notable book chapters. His research interests encompass Artificial Intelligence, Machine Learning, Distributed Systems, Data Analytics, and Biomedical Informatics. Beyond his academic achievements, Dr. Bokhari is an accomplished sportsman, having represented Linköping Cricket Club in Sweden and Oldenburg Cricket Club in Germany. He is also skilled in combat sports and holds a black belt in martial arts.

Publications

1.        S. M. A. Bokhari, K. Krstovski, J. Withall, R. Lee, P. Dykes, M. Tran, S. Rossetti, K. Cato, Heuristic-Based Extraction and Unigram Analysis of Nursing Free Text Data Residing in Large EHR Clinical Notes, In the Proceedings of the 17th EAI International Conference on Pervasive Computing Technologies for Healthcare, Malmö, Sweden (2023).
https://link.springer.com/chapter/10.1007/978-3-031-59717-6_9 

2.        S. M. A. Bokhari, O. Theel, A Flexible Hybrid Approach to Data Replication in Distributed Systems, Computing Conference (SAI), Springer Book Chapter: Advances in Intelligent Systems and Computing (AISC), Vol. 1(1228), pp. 196-207, London, UK (2020).
https://link.springer.com/chapter/10.1007/978-3-030-52249-0_13

3.        S. M. A. Bokhari, O. Theel, A Genetic Programming-based Multi-objective Optimization Approach to Data Replication Strategies for Distributed Systems, In the Proceedings of the IEEE Congress on Evolutionary Computation (IEEE CEC, WCCI), pp. 1-9, Glasgow, Scotland (2020).
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9185598 

4.        S. M. A. Bokhari, O. Theel, Introducing Novel Crossover and Mutation Operators into Data Replication Strategies for Distributed Systems, In the Proceedings of the 25th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC) 2020, pp. 21-30, held jointly with PRDC 2021 from 01-04 December 2021 in Perth, Australia.
https://ieeexplore.ieee.org/abstract/document/9320430 

5.        S. M. A. Bokhari, S. A. Khan, Applying Supervised and Unsupervised Learning Techniques on Dental Patients’ Records, Springer Book Chapter: Emerging Trends and Advanced Technologies for Computational Intelligence, Studies in Computational Intelligence, Vol. 647, pp. 83-102, ISSN: 1860-949X (2016).
https://www.springerprofessional.de/en/applying-supervised-and-unsupervised-learning-techniques-on-dent/10248298