Prospective PhD candidate, 2027 · Research Intern, XIoT Lab, MMU · Applied machine learning · Digital health · Energy systems · Measurement design
Research Intern at the XIoT Lab, Faculty of Computing and Informatics, Multimedia University. I study how people, machines and systems actually behave, and design the instruments that measure it, across digital healthcare and telemedicine, AI-powered motion detection, hydroelectric power, healthcare device design and generative AI. Electrical and electronic engineer with six and a half years in applied engineering. Seeking a funded doctoral position starting 2027.
Applied engineering
6.5
years
Now a Research Intern, XIoT Lab, MMU
Peer-reviewed output
5
papers
4 published · 1 presented Sept 2026 · +1 in preparation
MSc ICT · CGPA
3.81
/ 4.00
Earned in full-time employment
Primary data collected
35
interviews
Under institutional ethics approval
Profile
I am a Research Intern at the XIoT Lab, Faculty of Computing and Informatics, Multimedia University, and an electrical and electronic engineer who builds what he studies. My work spans digital healthcare and telemedicine, AI-powered motion detection, hydroelectric power, healthcare device design and generative AI, held together by one aim: recording behaviour as it happens, not reconstructing it afterwards.
My MSc thesis detected over-speeding and lane changes in naturalistic traffic footage; my BSc thesis scheduled hydroelectric dispatch to cut load shedding in Bangladesh. My 2021 telemedicine study rests on 35 in-depth interviews under ethics approval, and my recent co-authored work applies machine learning to dengue, air quality and model interpretability.
Since 2019 I have also run controlled experiments inside large advertising systems across five markets, with randomisation and outcomes pre-specified before the data is seen. MSc in ICT, CGPA 3.81 / 4.00. Four peer-reviewed papers, a fifth presented in September 2026, one in preparation.
Doctoral interests
Each interest below grows out of something already in my record: a thesis, a paper, or years of hands-on work with the systems involved. I am open to a supervisor shaping any of them into a doctoral project.
Does moving to an electric vehicle change how the same person drives, plans trips and takes risks? Instant torque, silent running and range anxiety all suggest it should, but within-driver evidence is thin.
Builds on: MSc thesis: deep-learning detection of speeding and lane changes
Whether the environmental gains promised for electric mobility show up in measured air quality, battery life cycles and material use, rather than only in projections.
Builds on: Machine-learning work on air-quality prediction
What actually drives people to adopt, or reject, electric vehicles: the reasons they state before buying versus the behaviour observed afterwards, and how persuasion systems shape the choice.
Builds on: Six years of controlled experiments on consumer response
How patients and clinicians come to trust remote care, what makes adoption last beyond a crisis, and where AI triage helps or harms the consultation.
Builds on: Interview study of 35 clinicians, patients and platform staff
Forecasting and early-warning systems built on open data, so public-health teams can act before an outbreak rather than after it.
Builds on: Co-authored work on dengue outbreak forecasting
Connected sensing devices that record behaviour and health signals as they happen, designed for the people who will wear or use them.
Builds on: Healthcare device design; Research Intern, XIoT Lab
Making model decisions readable to the people who depend on them, and choosing the right interpretability method for the task.
Builds on: Published comparison of LIME, SHAP and feature importance
The ethical and occupational effects of generative AI on creative and professional work, measured through the people living with it.
Builds on: Survey of creative professionals, presented September 2026
Experimental design and controlled A/B testing at population scale · randomisation, power and pre-specification of outcomes · survey instrument design · in-depth interviewing, purposive sampling, thematic analysis · research ethics procedure · healthcare device design · supervised machine learning, benchmarking and validation · explainable AI (LIME, SHAP, feature importance) · deep learning for computer vision · Python.
Publications
ORCID 0009-0009-8360-9690. Author name in bold. Full texts on request. View the CV or download the PDF.
7th Multimedia University Engineering Conference (MECON2026 / DIFCon 2026), Multimedia University, Malaysia, 5–7 May 2026
A predictive framework built on open-source meteorological data to forecast dengue outbreak trends across Malaysia, aimed at early warning and public-health preparedness. Affiliations: Multimedia University, Malaysia; Miraiyo, Bangladesh; Centre for Electric Energy and High Voltage Engineering.
7th Multimedia University Engineering Conference (MECON2026 / DIFCon 2026), Multimedia University, Malaysia, 5–7 May 2026. Also presented at the 8th ASEAN–UEC Workshop, September 2026
Benchmarks Random Forest, XGBoost and Support Vector Regression for daily AQI prediction in Dhaka, adding a binary brick-kiln-season feature (November to March) under seasonally stratified evaluation. Brick kilns are a dominant winter source that generic pollution models routinely omit.
The 8th ASEAN–UEC Workshop on Informatics and Engineering, held with the 13th UEC Seminar in ASEAN 2026, UEC ASEAN Research and Education Center, University of Electro-Communications, Japan, at Multimedia University, Cyberjaya, 5–6 September 2026
A survey of creative professionals on the occupational and ethical consequences of generative AI in Malaysia’s digital-art sector. Primary data collected by questionnaire. Presented on 6 September 2026.
International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), 13(3), March 2024. DOI 10.17148/IJARCCE.2024.13301. ISSN 2278-1021 (online), 2319-5940 (print)
Compares LIME, SHAP and conventional feature importance on a decision-tree classifier. Finds high local precision and recall for LIME, a local–global balance for SHAP, and sets out practical selection criteria for interpretability frameworks. Published as Abdullah-Al Mahmood, Bangladesh University of Professionals.
Asian Journal of Multidisciplinary Research & Review (AJMRR), 2(2), 592–621, April–May 2021. ISSN 2582-8088. The Law Brigade Publishers
Mixed-methods study of how AI-driven telemedicine was implemented and adopted in Bangladesh during the pandemic. Thirty-five in-depth interviews with practitioners, patients and platform staff, recruited by purposive sampling and conducted under institutional ethics approval. Published as Abdullah-Al Mahmood.
In preparation
Replaces the rule-based peak-shaving schedules of my undergraduate thesis with learned dispatch policies under chronic generation shortfall. The same question, fourteen years on, with the methods that were not available the first time.
Bangladesh University of Professionals, Faculty of Science and Technology, Dhaka. Examined March 2022
Deep-learning models applied to naturalistic traffic footage to detect over-speeding and lane-change manoeuvres in mixed, weakly regulated urban traffic, a setting under-represented in driver-behaviour research.
Ahsanullah University of Science and Technology, Dhaka, 2012
Dispatch scheduling to flatten demand peaks in a chronically supply-constrained national grid. Extended a decade later with machine-learning methods (see P6).
Achievements
Two journal publications and two conference papers. Hover over a certificate to enlarge it, or click to view it full screen.
Gallery
Moments from conferences and events in Malaysia. Hover over a photo to enlarge it, or click to view it full screen.
Where I have been
Research Intern, XIoT Lab
Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia.
Research collaboration, environmental and climate-health machine learning
Multimedia University, Malaysia · Miraiyo, Bangladesh · Centre for Electric Energy and High Voltage Engineering. Supervising collaborator: Ir. Dr. Siow Chun Lim. Output: P1 and P2.
MSc in Information and Communication Technology (CGPA 3.81 / 4.00)
Bangladesh University of Professionals, Dhaka. Completed in full-time employment. Group thesis on deep-learning speed and lane-change detection.
Field study: telemedicine and health-technology adoption
Thirty-five in-depth interviews with clinicians, patients and platform staff, conducted under institutional ethics approval and analysed thematically. Published as P5.
Research Engineer
Debonair Electrical & Electronics Ltd., Dhaka. Four years of applied product research and technical evaluation, reported to international suppliers and industrial clients; trained junior engineers.
BSc, Electrical and Electronic Engineering
Ahsanullah University of Science and Technology, Dhaka. Thesis on peak-shaving hydro dispatch and load shedding.
Social Media & Content Manager, Paid Media
Black Swan Business Setup Services, UAE (remote). Paid acquisition across five markets; builds and runs the full measurement stack (GA4, Tag Manager, Conversions API, Looker Studio). Controlled experiments at population scale with outcomes pre-specified before results are read.
Technical Writer · Marketing Manager · Assistant Manager
BuddyBoss, Canada · STUDiLOG · Enzaime Bangladesh. Developer documentation and pre-release testing; the Enzaime role provided the field access behind P5. The MSc was completed in full over this same period.
Support Engineer
Ahsan Automation Ltd., Dhaka. Industrial automation design and implementation; engineering drawing; collaboration with international manufacturers on new products.
September 2026. 13th UEC Seminar in ASEAN and the 8th ASEAN–UEC Workshop on Informatics and Engineering, University of Electro-Communications, Japan, held at Multimedia University, Cyberjaya. Presented two contributions: the generative-AI survey (P3) and the Dhaka air-quality work (P2). May 2026. 7th Multimedia University Engineering Conference (MECON2026 / DIFCon 2026), Malaysia; co-author of two papers, P1 and P2.
Bengali. Native, and a working research capability for fieldwork, interviewing and primary-document access in Bangladesh. English. Full professional proficiency, medium of instruction throughout higher education; IELTS Academic overall band 7.5, certificate lapsed March 2026, retest at short notice if a valid score is required. Hindi. Good working proficiency in speech and comprehension, sufficient for interviewing and South Asian source material. Malay. Basic working familiarity for regional sources.
Contact
If any of the interests above overlaps with your group’s work, I would value a short conversation. I can send a research statement, full texts of any paper listed here, and my transcripts on request.
I am a Bangladeshi national, currently resident in Malaysia, and available to relocate. I hold a valid long-term pass in Malaysia and work as a Research Intern at the XIoT Lab, Faculty of Computing and Informatics, Multimedia University. The clearest evidence of how I work is the interview study behind P5, the MSc thesis on driver behaviour in naturalistic traffic footage, and six years of controlled testing at population scale.
The fastest way to reach me is email. I reply within a day.
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