S M Abdulla Al Mamun

Role at ISH and current research direction

S M Abdulla Al Mamun is the Principal Investigator of Intelligent Systems for Health (ISH), a nonprofit research group based in Bangladesh. He leads research on the implementation and evaluation of health technologies within Bangladesh's health and public-service systems.

His current direction at ISH examines urban and rural implementation, workforce capacity, training, adoption and workflow integration, equitable access, infrastructure readiness, resource requirements, and operational feasibility. Sustained performance, scalability, effects on services and health outcomes, and cost-effectiveness where evidence permits are questions for investigation.

Technical background and previous research

A Commonwealth Scholar with an artificial intelligence background at the University of Manchester, his technical work spans machine learning, medical-image research, simulation, and research software in Python. His wider interests include how AI changes the ways people communicate, learn, and cooperate, and research tools that make those questions testable.

The sections below document his technical expertise and previous research, alongside his academic and professional record.

Academic background

• MSc Artificial Intelligence — University of Manchester.
• MSc Computer Science and Engineering — BRAC University.
• BSc Computer Science and Engineering — BRAC University.

Awards and scholarships

• National Science and Technology (NST) Fellowship, Ministry of Science and Technology, Government of Bangladesh — 2026.
• Commonwealth Master's Scholarship, United Kingdom — 2025.
• Science and Technology Fellowship (MS abroad), Science and Technology Fellowship Trust, Ministry of Science and Technology, Bangladesh — 2024.
• Merit Based Scholarship, BRAC University — 2018.
• Secondary School Certificate Scholarship, Dhaka — 2014.
• Junior School Certificate Scholarship, Dhaka — 2011.

Publication

Shakib Mahmud Dipto, Mehafuza Islam, S.M Abdulla Al Mamun, Md. Kaviul Hossain, A M Esfar-E-Alam, and Md. Ashraful Alam. An Interpretable Transformer-Based Approach to Classify Malaria from Blood Cell Images. 2024 International Conference on Sustainable Technology and Engineering (i-COSTE), IEEE, Perth, Australia, pp. 1–6. Read the paper.

The publisher-supplied Crossref record lists his author name as S.M Abdulla Al Mamun and his affiliation for this publication as BRAC University's Department of Computer Science and Engineering. The paper also appears on coauthor Md. Kaviul Hossain's ULAB faculty publication page.

Technical research and software

Medical imaging and interpretable AI

Research on transformer-based classification of malaria from blood-cell images, comparing vision transformers, Swin transformers, and convolutional models. The work combines medical-image processing, model evaluation, and visual explanations using Grad-CAM.

TrafficTwin: intelligent transportation and edge computing

An auditable research platform for dynamic resource management in vehicular edge computing. TrafficTwin combines SUMO traffic simulation with experiments on task offloading, scheduling, admission, and placement across roadside infrastructure. The research examines reinforcement learning and deterministic policies using reproducible accounting of latency, deadlines, and rejected tasks.

TrafficTwin on GitHub.

Livestock and environmental health

Vision-transformer research on transboundary disease detection and waste management in Bangladesh's livestock farming systems, using multi-task and transfer learning.

PaperStack: research software and literature workflows

A literature research platform for querying and reasoning over research papers. The work combines document ingestion, hybrid semantic and keyword retrieval, reranking, and graph-based exploration of research relationships.

MasalaEngine: retrieval-augmented generation

An academic project exploring retrieval-augmented generation over a culinary corpus. It combines dense retrieval, BM25, cross-encoder reranking, and comparative evaluation of chunking strategies and grounded responses.

MasalaEngine on GitHub.

SkillSight UK: skills analysis with NLP

A research pipeline for extracting a 13-category skills taxonomy from UK data and business analyst job postings. The project studies lexical baselines and evaluation methods using an annotated corpus, nested cross-validation, and bootstrap analysis.

SkillSight UK on GitHub.

Biomedical and bioinformatics studies

Research projects include reference augmentation for fish DNA barcoding in Bangladesh, thalassemia and HbE referral from complete blood counts, and selective review of qPCR amplification curves.

Research experience

• Information Management Group, University of Manchester — Researcher, 2026. Intelligent transportation systems and vehicular edge computing; supervised by Dr Sandra Sampaio.
• Computer Vision and Intelligent Systems (CVIS) Lab, BRAC University — Research Assistant, 2021–2023. Medical-image analysis, deep learning, explainable AI, and malaria-classification research.
• Intelligent Systems for Health — Researcher, 2023–2025. Research on healthcare systems in Bangladesh and development of an AI-integrated dialectical behavior therapy application.

Teaching and industry experience

• Lecturer, Department of ICT — Selim Reza Habib Degree College, June–December 2023. Taught ICT and developed learning materials for higher secondary students.
• Machine Learning Engineer — ByteWave, 2023–2025. Demand forecasting, supply-chain prediction, and recommendation systems.
• Backend Software Engineer — ByteWave, 2022–2023. Python and FastAPI services for e-commerce operations and pricing.
• Java Backend Developer — Lumina Global, 2019–2020. Java and Spring Boot services, database integration, and software testing.

Technical skills

Python, Java, JavaScript, PyTorch, TensorFlow, scikit-learn, FastAPI, Spring Boot, React, SQL, Pandas, NumPy, simulation, retrieval-augmented generation, and reproducible evaluation.

Community and mentoring

Member of BRAC University's Mongol Tori robotics team and Mathematics and Natural Sciences Club, 2018–2022; programming mentor with the BRAC University Computer Club; and community teaching experience.

Wider technical research interests

AI for health; interpretable machine learning; reproducible evaluation; human–AI interaction; communication, cooperation, cognition, and learning.

Explore research software on GitHub.