Moin Bhuiyan, Ph.D., P.Eng (ON, Canada)

Moin Bhuiyan Ph.D. P.Eng Image
Visiting Assistant Professor

Electrical & Computer Engineering and Computer Science Department
Tagliatela College of Engineering

Ph.D. in Electrical Engineering University of Windsor, Windsor, Canada
M.A. Sc. in Electrical and Computer Engineering Ryerson University, Toronto, Canada
B.Sc. in Electrical and Electronic Engineering Chittagong University of Engineering and Technology (CUET), Chittagong, Bangladesh

About Moin

Dr. Moin Bhuiyan is currently a Visiting Assistant Professor at the University of New Haven in the Department of Electrical and Computer Engineering and Computer Science. His research interests include Smart Prosthetics, Digital systems, Wearable Sensors, Biomedical signals and image processing, and Machine learning algorithms: Theory and Application. In the past, he has served as an Assistant Teaching Professor at Worcester Polytechnic Institute and as a Contract Lecturer at Ryerson University. At WPI, he worked on a myoelectric hand-wrist prosthesis, which involved research in algorithms, EMG signals, and machine learning. He also developed a 16 channel analog front end for EMG signal processing at WPI. He also worked as a Post-Doctoral Fellow at the Institute for Diagnostic Imaging Research located at MaRS Discovery District, Toronto, ON, Canada. There, he continued his Ph.D. research for developing Portable Pulmonary Injuries Diagnostic device (PPIDD) meant to make a diagnosis of Pneumothorax on the spot.

Current Courses (Spring 2020)
  • VLSI design
  • Wireless Networks
  • Networking I
  • Analog Circuits
Courses Taught
  • Advanced Systems Architecture
  • Biomedical Systems Modeling
  • Digital Systems
  • Electronics II
  • Electronics Design Laboratory
  • Intelligence systems/machine learning
  • Networking II
  • Power Electronics
  • Radiation Therapy Devices
Selected Publications
  1. Moinuddin Bhuiyan, Eugene V. Malyarenko, Mircea A. Pantea, Dante Capaldi, Alfred E. Baylor, and Roman Gr. Maev, "Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method," Journal of Electrical and Computer Engineering, vol. 2015, Article ID 274541, 10, pages, 2015. doi:10.1155/2015/274541
  2. Bhuiyan M, Malyarenko, E.V.; Pantea, M.A.;Seviaryn, F.M., Maev, R.G. "Advantages and limitations of using Matrix Pencil Method for the modal analysis of medical percussion signals" IEEE Biomedical Engineering,Feb2013, Vol.60(2):Pages417-26.
  3. Bhuiyan M, Malyarenko EV, Pantea M A, Maev R G, Baylor A E. "Estimating the parameters of audible clinical percussion signals by fitting exponentially damped harmonics" Journal of coustical Society of America (JASA), Journal of Acoustical Society of America, Jun2012, Vol.131(6):4690-8. doi: 10.1121/1.4712018.
  4. Bhuiyan M, Malyrenko E, Pantea M and Roman Maev "Time-frequency analysis of multi-component, non-stationary signals using matrix pencil method" 11th International Conference of Upcoming Engineers 2012 (ICUE’12), Sponsored by IEEE Toronto Chapter Ryerson University, Toronto, ON, Canada.
  5. M.Bhuiyan, and M. Jaseemuddin, "Congestion-Aware Overlay Networks‘, Proceedings of the 64th IEEE Vehicular Technology Conference Fall 2006 (VTC), Sept. 25-28, 2006 Montreal, Canada.
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