Ph.D. (Electrical and Computer Engineering), New Mexico State University, USA
MSc (Electrical and Computer Engineering), New Mexico State University, USA
BSc (Electrical & Electronic Engineering), Islamic University of Technology (IUT), Bangladesh
STMW 09:00 am – 09:30 am
MW 01:00 am – 02:30 pm
ST 11:20 am – 2:30 pm
Biography
Dr. Riasat Khan is an Associate Professor in the Department of Electrical and Computer Engineering at North South University, Dhaka, Bangladesh. He received his B.Sc. in Electrical and Electronic Engineering from the Islamic University of Technology (IUT), Bangladesh, and began his academic career as a Lecturer at Green University of Bangladesh. He later earned his M.Sc. and Ph.D. in Electrical and Computer Engineering from New Mexico State University, USA, where he also served as a Graduate Teaching Assistant and received the Outstanding Teaching Assistant Award. At NSU, he served as the Undergraduate Program Coordinator (EEE/ETE) from 2023 to 2024. He is actively involved in the BAETE accreditation process and has completed BAETE Evaluator Training (Tier-1). His research interests include Artificial Intelligence, Smart Systems and IoT.
Research Areas
Research Interests
Data Science, Artificial Intelligence, Smart Systems and IoT
Teaching
- CSE 445 Machine Learning
- CSE 465 Pattern Recognition and Neural Network
- EEE 111/ ETE 111 Analog Electronics-I
- EEE241/ETE241 Electrical Circuits II
- EEE 141 Electrical Circuits I
- CSE 542 Advanced VLSI Design
- CSE499A/EEE499A/ETE499A – Senior Design I
- CSE499B/EEE499B/ETE499B – Senior Design II
- EEE 312 Power Electronics
- EEE311/ ETE311 Analog Electronics II
- CSE 596 Special Course I: Recent advances in CSE
- CSE 597 Special Course 2: Seminar Topics
Selected Publications
Journals
- Riasat Khan and Kwong T Ng, “DMD-Galerkin Model Order Reduction for Cardiac Propagation Modeling,” Applied Computational Electromagnetics Society Journal, 2018
- N. A. Mimma, T. Rahman, S. Ahmed and R. Khan, “Fruits Classification and Detection Application Using Deep Learning,” Scientific Reports, 2022
- M. N. I. Suvon, S. C. Siam, M. Ferdous, M. Alam and R. Khan, “MS and PhD Admission Prediction of Bangladeshi Students into Different Classes of Universities,” IAES International Journal of Artificial Intelligence, 2022
- M. T. Islam, S. T. Mashfu, A. Faisal, S. C. Siam, I. T. Naheen and R. Khan, “Deep Learning Based Glaucoma Detection with Cropped Optic Cup and Disc and Blood Vessel Segmentation,” IEEE Access, 2022
- N. H. Tasnim, S. Afrin, B. Biswas, A. A. Anye and R. Khan, “Automatic Classification of Textile Visual Pollutants using Deep Learning Networks,” Alexandria Engineering Journal, 2022
- AZ Apurba, MFS Titu, MA Pavel, IT Naheen, R Khan, “Fusion of Image Filtering and Knowledge-Distilled YOLO Models for Root Canal Failure Diagnosis,” IEEE Access, 2025
- A. Hossain, M. J. Anee, R. Faruqui, S. Bushra, P. Rahman and R. Khan, “A GPS Based Unmanned Drone Technology for Detecting and Analyzing Air Pollutants,” IEEE Instrumentation & Measurement Magazine, 2022
- I. Tasin, T. U. Nabil, S. Islam and Riasat Khan, “Diabetes prediction using machine learning and explainable AI techniques,” Healthcare Technology Letters, 2022
- M. M. Ratul, K. A. Rahman, J. Fazal, N. R. Abanto and R. Khan, “Face Mask and Social Distance Monitoring via Computer Vision and Deployable System Architecture,” Intelligent Automation & Soft Computing, 2023
- A. Rahman, M. B. H. Hriday and R. Khan, “Computer vision-based approach to detect fatigue driving and face mask for edge computing device,” Heliyon, 2022
- R. B. Islam, S. Akhter, F. Iqbal, M. S. U. Rahman and R. Khan, “Deep Learning Based Object Detection and Surrounding Environment Description for Visually Impaired People,” Heliyon, 2023
- S. Siddique, S. Islam, E. E. Neon, T. Sabbir, I. T. Naheen, and R. Khan, “Deep Learning-based Bangla Sign Language Detection with an Edge Device,” Intelligent Systems with Applications, 2023
- S. Solayman, S. A. Aumi, C. S. Mery, M. Mubassir and R. Khan, “Automatic COVID-19 Prediction Using Explainable Machine Learning Techniques,” International Journal of Cognitive Computing in Engineering, 2023
Conference Papers
- Riasat Khan and Kwong T Ng, “Model Order Reduction for Finite Difference Modeling of Cardiac Propagation using DMD Modes,” IEEE International Applied Computational Electromagnetics Society Symposium, Denver, CO, 2018
- Riasat Khan and Kwong T Ng, “Model Order Reduction of Finite Difference Bidomain Modeling of Cardiac Propagation,” Biomedical Engineering Society Annual Meeting, Phoenix, AZ, 2018
- Riasat Khan and Kwong T Ng, “Higher Order Finite Difference Modeling of Cardiac Propagation,” IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017
Research Projects & Grants
- Automatic Smartphone-based Glaucoma and Diabetic Retinopathy Detection System Using Deep Learning Approaches,” North South University Research Grant, 2021.
- “Investigation of Antenna Design Parameters with Machine Learning Techniques,” North South University Research Grant, 2022.
- Robot Dexterity Intelligence (RDI)- A Reinforcement Learning Framework for Dual Robotic Arms with Blockchain-Enabled AI Skill Marketplace”, UIU-IAR Grant, 2024.
Professional Activity
- Faculty Advisor, IEEE Industry Applications Society (IAS)
- BAETE Evaluator Training (Tier-1)