Md. Shadman Abid

Vision-Informed Multi-Modal Multi-Agent Reinforcement Learning for Active Distribution Network Scheduling
AI-Driven Power Grid Path Prediction for Large-Scale Distribution Networks
Deep Learning-based Geospatial Mapping Framework for Large-Scale Electric Power Grids
Neural Architecture Search via Reinforcement Learning for Image-based Solar Panel Soiling Loss Prediction
Robust Deep Learning Model for Spatiotemporal Forecasting of Renewable Energy Sources

Actively contributed as a member of the technical team working on the "DPDC Smart Grid Pilot Project," a government-funded national initiative in Bangladesh aimed at modernizing the selected grid infrastructure in Dhaka city and implementing Advanced Distribution Management Systems (ADMS) for the DPDC networks.

Served as the engineer in charge of integrating Geographic Information System (GIS) databases with SCADA and ADMS systems to enhance spatial data management and operational efficiency.
This involved mapping grid components and ensuring seamless data flow between systems.

Utilized GIS databases to allocate Automatic Circuit Reclosers (ACRs) and Automated Load Switches (ALS) within the distribution network, optimizing system reliability and fault management.

Conducted feeder topology analysis using ETAP and CYME software to assess network configurations, perform load flow studies, and support decision-making for grid improvements.

Assessed Fault Location, Isolation, and Service Restoration (FLISR) techniques and optimal network reconfiguration strategies to enhance grid resilience and minimize downtime during outages.

Played a key role in the development and enhancement of SCADA (Supervisory Control and Data Acquisition) software, focusing on real-time monitoring, control, and visualization of the smart grid infrastructure.

Transient Stability Assessment of the Oman Grid under Large Penetration of Photovoltaic and Wind Energy Systems