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Emails:
muhammad.siam@queensu.ca
Research Interest: Biomedical Signal Processing, Audio Signal Processing, Deep Learning, Fundamental ML, Wearable Devices for Healthcare Monitoring
Muhammad Sudipto Siam Dip is a researcher specializing in machine learning and signal processing. He is currently pursuing his MASc in the field of Artificial Intelligence in the department of Electrical and Computer Engineering (ECE) at Queen's University, Canada. He is currently working as a graduate research fellow under the supervision of Dr. Ali Etemad at the AIIM lab at Queen's. He earned his Bachelor’s degree in Electrical and Electronic Engineering (EEE) from Rajshahi University of Engineering & Technology (RUET), one of the top engineering universities in Bangladesh. During his undergrad years, he served as an undergraduate research assistant in the Signal Processing and Machine Learning (SPML) Lab at RUET.
He is currently conducting his research on fundamental machine learning with a focus on gradient adaptation methods. Previously, he has conducted research on automatic sleep stage scoring using PSG signals, with a focus on building interpretable and explainable models for human-centered AI. He also worked on sleep apnea detection using ECG signals.
His broader interests include language models, interpretable AI, and developing resource-efficient wearable ML systems. He achieved the 2nd runner-up position at the IEEE Signal Processing Cup 2024 World Finals, held at ICASSP in Seoul, South Korea. He was also featured in Mathworks' Winners Circle 2024 for his contributions to the field of signal processing.
Outside of research, he has volunteered with IEEE, served as a departmental representative, and completed an internship at Think Ltd., Bangladesh.
He is always open to discussions—whether it’s about collaborative research, technology for healthcare, or just a good cup of coffee!
Recent Activity
Mar '26 - Conducted a seminar on Higher Studies in Canada hosted by the Higher Studies Society of RUET
Jan '26 - Started as a Teaching Assistant in the faculty of Smith Engineering, Dept. of Electrical and Computer Engineering, Queen's University, Canada
Dec '25 - My recent project titled "NeuroSleepNet: An Explainable Multi-Head Attention-Based Framework With Spatial and Multi-Scale Independent Temporal Context Learning for Automatic Sleep Stage Scoring" was published in IEEE Access and is available in the IEEE Xplore library.
Sept '25 - Started as a graduate research fellow at AIIM Lab under Ingenuity Labs Research Institute at Queen's University, Canada
Sept '25 - Started my MASc in Artificial Intelligence in the dept. of Electrical and Computer Engineering at Queen's University, Canada
last update: LOL! I forgot