Md Santo Ali

About

Ali is currently working as a Graduate Research Assistant with the Signal Processing and Machine Learning Lab, Department of EEE, RUET. He has completed his Bachelor of Science degree in Electrical and Electronic Engineering at Rajshahi University of Engineering & Technology (RUET), Rajshahi-6204, Bangladesh. He completed his Higher Secondary Certificate (HSC) in 2019 and his Secondary School Certificate (SSC) in 2017 under the Rajshahi Education Board.
A highly motivated researcher, he is dedicated to advancing biomedical signal processing, with a focus on developing cost-effective, real-time healthcare monitoring solutions using wearable devices. His research interests encompass AI-driven applications in biomedical engineering, deep learning, image processing, and biomedical signal processing. He is an active student member of the Institute of Electrical and Electronics Engineers (IEEE). He is currently serving as a peer reviewer for IEEE Access, IEEE Sensors Letters, IEEE Sensors Journal and served as a peer reviewer for 5th MusIML Workshop co-located with 39th NeurIPS. Reflecting his growing impact in the research community, he has also received the 2025 WI-IAT | TCII Best Paper Award.

Employment

• Rajshahi University of Engineering and Technology Research Assistant, Signal Processing and Machine Learning Lab
  2025 - Present
• Rajshahi University of Engineering and Technology Student
  2020 - 2025

Education

• Rajshahi University of Engineering and Technology Bachelor of Science
  2020 - 2025

Projects & Funding

Projects & funding information is unavailable.

Publications (12)

• Detection of Mental Stress From Photoplethysmography for Under- Resourced Healthcare Systems
  IEEE Sensors Journal 2026 DOI: 10.1109/JSEN.2025.3649586
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• A Hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory Approach for PPG-Based Stress Monitoring from Wrist Worn Wearables
  2026 DOI: 10.1007/978-981-95-4384-7_33
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• An Attention Driven Deep Learning Architecture for Stress Monitoring Using Single Channel Electrocardiogram Signal
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3705373
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• TEANet: A Transpose-Enhanced Autoencoder Network for Stress Monitoring on Resource-Constrained Wearable Device
  IEEE Access 2026 DOI: 10.1109/ACCESS.2025.3644400
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• A multi-modal wearable dataset for cognitive attention and task-based stress analysis
  Data in Brief 2025 DOI: 10.1016/j.dib.2025.112295
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• A Dual Path Hybrid Convolutional Neural Network and Bidirectional Long-Short Term Memory Approach for PPG-Based Stress Monitoring
  4th Muslims in ML Workshop co-located with ICML 2025 2025 DOI: 10.22541/AU.175329643.35949288/V1
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• A Dual-Branch Convolutional Neural Network with Gated Recurrent Units Network for Enhanced Multimodal Stress Monitoring from Wearable Physiological Signals
  5th Muslims in ML Workshop co-located with NeurIPS 2025 2025
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• Federated Learning for Autism Spectrum Disorder Detection
  2025 DOI: 10.1007/978-981-96-2721-9_10
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• ReTeNet: A Residual Encoder and Transformer Encoders Network for Stress Monitoring From Wearable Device
  IEEE Signal Processing Letters 2025 DOI: 10.1109/LSP.2025.3607767
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• StressBVPNet: An Explainable Deep Learning Model for Stress Monitoring from BVP Signals
  Unpublished 2025 DOI: 10.13140/RG.2.2.24480.55044
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