AI RESEARCHER — Cyberjaya, Malaysia
Md Sabbir
Hossen
Reinforcement learning that cuts EV charging costs, stabilizes the grid, and gives second-life batteries a second life.
MEngSc Researcher, Multimedia University — 15 publications · h-index 6 · Cyberjaya, Malaysia
[ About ]
I'm a postgraduate researcher at Multimedia University, Cyberjaya, working at the intersection of artificial intelligence and power infrastructure. My work integrates reinforcement learning, optimization, and data-driven diagnostics to solve real problems in electric vehicle charging, second-life battery reuse, and smart grid operation — most of it validated against real OCPP charging data and real Malaysian grid datasets rather than pure simulation.
Across 15 publications — 11 as first author — I've worked on tariff-aware and carbon-aware RL scheduling, physics-informed battery health estimation, federated learning for privacy-preserving smart cities, and anomaly detection for multi-station charging networks, published in venues including Energy Reports, Scientific Reports, IEEE Access, and Batteries.
Education
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M.Eng.Sc. (By Research)Multimedia University, MalaysiaNov 2024 — May 2026
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B.Sc. Computer Science & EngineeringNorth Western University, Bangladesh2016 — 2022
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Diploma, Computer Science & TechnologyJessore Polytechnic Institute, Bangladesh2009 — 2013
[ Research Focus ]
Four threads, one energy system
EV Charging Intelligence
OCPP-integrated reinforcement learning for scheduling, forecasting, and anomaly detection across multi-station charging networks.
Second-Life Battery Systems
Physics-informed, explainable state-of-health estimation and reuse pathways for retired EV batteries under sparse cycling data.
Smart Grid & Carbon Optimization
Tariff-aware and carbon-aware scheduling that keeps charging networks grid-stable while cutting operational emissions.
Federated & Explainable AI
Privacy-preserving federated learning and explainable models for trustworthy, scalable energy-system deployment.
[ Research Output ]
[ Featured Publications ]
Selected first-author research
Physics-Informed and Explainable Machine Learning for State-of-Health Estimation of Second-Life Lithium-Ion Batteries Under Sparse Cycling
OCPP Integrated Artificial Intelligence for Forecasting, Scheduling and Anomaly Detection in City-Scale Electric Vehicle Charging under Urban Tariffs
AI-OCPP Framework for Smart and Safe EV Charging: Real-World Performance Evaluation
[ Full Publication Record ]
All 14 papers, by author role
[ Experience & Leadership ]
- Developed reinforcement learning models (PPO, Q-Learning) for EV charging and smart grid optimization, achieving 25–40% peak-load reduction and ~30% energy-cost savings.
- Designed multi-station OCPP simulation environments using real Malaysian charging datasets.
- Built forecasting models with LSTM, GRU, XGBoost, and Prophet for charging-demand prediction.
- Ran carbon-aware optimization studies and investigated second-life EV battery integration for grid support.
- Developed federated learning frameworks for privacy-preserving smart energy systems.
- Led interdisciplinary research activities in AI-driven EV charging and smart grid optimization.
- Coordinated model development, experimentation, manuscript preparation, and publication activities.
[ Selected Projects ]
Applied systems, not just papers
AI-Driven OCPP Framework for EV Charging
- Optimized charging across 6 stations under an 80 kW grid constraint
- Reduced peak demand and improved grid stability with RL-based scheduling
Federated AI-OCPP Network for Smart Cities
- Designed a distributed learning system for scalable EV infrastructure
- Enhanced privacy and resilience in smart energy networks
Second-Life Battery Integration for Smart Grids
- Investigated reuse of EV batteries for stationary energy storage
- Modeled sustainable storage with AI-driven optimization
[ Student Mentorship ]
- Feasibility Study on Second-Life Electric Vehicle Batteries for Photovoltaic Energy Storage Systems — Bachelor FYP, 2026
- Quantifying the Environmental Value of Second-Life EV Batteries Through Green Cost Modelling — Bachelor FYP, 2026
[ Awards & Academic Service ]
- Gold Medal — Innovation Exhibition, AI-Driven Sustainable Energy System Research2025
- Silver Medal — iNVENTX International Innovation Competition2026
- Bronze Medal — iNVENTX International Innovation Competition2026
- Silver Medal — iNVENTX International Innovation Competition2025
- 3MT Competition Participant, Multimedia University—
- Invited Reviewer — IEEE MECON, artificial intelligence & smart energy systems2026
[ Certificates & Recognition ]
Award and certificate photos to be added.
2025
SILVER · 2026
BRONZE · 2026
SILVER · 2025
[ Contact ]
Open to research collaboration, PhD/postdoc opportunities, and industry partnerships in AI-driven energy systems.
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Prof. Dr. Gobbi RamasamyProfessor, Faculty of Engineering & Technology, MMU — Principal Research Supervisorgobbi@mmu.edu.my
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Dr. Ngu Eng EngSenior Lecturer, Faculty of Engineering & Technology, MMU — Co-Supervisor & Research Collaboratoreengu@mmu.edu.my