Mohammod Abdul Motin
Rajshahi University of Engineering and Technology, The University of Melbourne
Research areas: Medicine · Cardiology and Cardiovascular Medicine · Non-Invasive Vital Sign Monitoring · Heart Rate Variability and Autonomic Control · ECG Monitoring and Analysis
0000-0003-1618-3772
About
Dr. Mohammod Abdul Motin is currently working as an Associate Professor in the Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Bangladesh. He completed his Ph.D. degree with the Department of Electrical and Electronic Engineering at the University of Melbourne, Australia, in 2020. Prior to that, he received his M.Sc. Eng. and B.Sc. Eng. degrees in electrical & electronic engineering from the Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh, in 2014 and 2011, respectively. His research interests include biomedical signal processing and machine learning, time series analysis, deep learning, monitoring neurological disorders, and sensor devices for wearable health care monitoring. Dr. Motin is the recipient of several awards and prizes, including the IEEE Upsilon Pi Epsilon Award, IEEE Lance Stafford Larson Award, IEEE Richard E. Merwin Scholarship, W. E. and C. H. H. Cook Memorial Award, ISSNIP Travel Grant, Melbourne Abroad Travelling Scholarship (MATS), ANZSCON 2017 Travel Grant, IEEE R10 SAC Best Paper Award (PG Level), IEEE Australia Council Student Paper Award (Post-graduate), Best Paper Award in ICEEE 2021, Best Paper Award in ICEEICT 2024, and the University of Melbourne MIRS and MIFRS Scholarships.
Employment
-
Rajshahi University of Engineering and Technology Associate Professor2025 - Present
-
Rajshahi University of Engineering and Technology Assistant Professor2021 - 2025
- 2012 - 2021
Education
-
University of Melbourne Doctor of Philosophy2015 - 2020
-
Rajshahi University of Engineering and Technology M.Sc. in Engineering2012 - 2014
-
Rajshahi University of Engineering and Technology B.Sc. in Engineering2007 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (50)
- An explainable transformer-driven network for electrocardiogram-based stress monitoring for resource-constrained devices Save
- TinyHAR-Net: Design and Implementation of a TinyML-Based Human Activity Recognition Framework on STM32 Save
- Detection of Mental Stress From Photoplethysmography for Under- Resourced Healthcare Systems Save
- A Hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory Approach for PPG-Based Stress Monitoring from Wrist Worn Wearables Save
- An Attention Driven Deep Learning Architecture for Stress Monitoring Using Single Channel Electrocardiogram Signal Save
- NeuroSleepNet: An Explainable Multi-Head Attention-Based Framework With Spatial and Multi-Scale Independent Temporal Context Learning for Automatic Sleep Stage Scoring Save
- TEANet: A Transpose-Enhanced Autoencoder Network for Stress Monitoring on Resource-Constrained Wearable Device Save
- TinyArtifactNet: A Resource-Efficient Deep Learning Model for On-Device Motion Artifact Detection in PPG Save
- A multi-modal wearable dataset for cognitive attention and task-based stress analysis Save
- Poincaré Image Analysis of Short-Term Electrocardiogram for Detecting Atrial Fibrillation Save
- DeepApneaNet: A Multistage CNN-Bi-LSTM Hybrid Model for Sleep Apnea Detection From Single-Lead ECG Signal Save
- Electrocardiogram Signal Quality Assessment Using Deep Learning Model Save
- ReTeNet: A Residual Encoder and Transformer Encoders Network for Stress Monitoring From Wearable Device Save
- Difference Poincaré Image Feature-Based Persistent Atrial Fibrillation Classification Using Short-Term Electrocardiograms Save
- NeuroDiag: Software for Automated Diagnosis of Parkinson’s Disease Using Handwriting Save
- Wearable Accelerometer and Gyroscope Sensors for Estimating the Severity of Essential Tremor Save
- Performance of a Convolutional Neural Network Derived From PPG Signal in Classifying Sleep Stages Save
- Multi-stage sleep classification using photoplethysmographic sensor Save
- Can Thermal Imaging Technique be Used to Predict the Healing Status of a Venous Leg Ulcer? Save
- Convolutional neural network ensemble for Parkinson's disease detection from voice recordings Save