Research
My research focuses on matrix factorization, machine learning,
signal processing, and privacy-preserving data analysis.
I am particularly interested in low-rank models, decentralized learning,
and robust data recovery methods.
Research-Related Coursework
- EE 6230 – High-Dimensional Probability and Linear Algebra for Machine Learning
- EE 5230 – Random Processes for Communications and Signal Processing
- MATH 5100 – Linear Algebra
- EE 5710 – Convex Optimization
- EE 5250 – Machine Learning: A Signal Processing Perspective
Journal Papers
Privacy-Preserving Non-negative Matrix Factorization for Decentralized Data Using Correlated Noise
Hafiz Imtiaz, Tusher Karmakar, Protoye Kumar Mohanata
Signal, Image and Video Processing, 2024
Conference Papers
Bidirectional Cross-Dataset Transfer Learning for Human Activity Recognition with Dataset-Specific Adapters and EWC
Sandipa Chowdhury, Mohtasim Billah, Sudipto Pramanik, Shaikh Anowarul Fattah, Tusher Karmakar
11th IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering, 2025 (Accepted)