About the researcher
Connecting hands-on distribution-system operations with transparent, data-driven research for resilient energy infrastructure.
Bikash Halder
Mechanical Engineering graduate · Electricity-distribution O&M engineer · Prospective PhD researcher
My research interests bridge electricity-distribution engineering, probabilistic machine learning, demand forecasting, sanctioned-load analytics and resilience-aware operational decision support.
Through professional work with WZPDCL in Meherpur, Bangladesh, I have practical exposure to feeder and distribution-transformer operation, load measurement, consumer mapping and utility records. My research direction applies rigorous AI and engineering methods to problems grounded in utility operations.
This is an independent research portfolio. Professional affiliation is provided for background and does not indicate official WZPDCL endorsement.
BSc, Mechanical Engineering
Graduated 2023
System Engineer
WZPDCL · Meherpur Electric Supply Unit · O&M, Kushtia Circle
November 2023 – Present
Fully funded PhD in AI-driven analytics for resilient, renewable-integrated smart distribution systems.
Methods and application areas
Machine learning
XGBoost, LightGBM, quantile forecasting, consumer-grouped cross-validation and model calibration.
Utility analytics
Feeder and consumer records, prepaid simulations, anomaly screening and regulatory decision support.
Future research
Physics-informed analytics, renewable uncertainty, DSM optimization and grid resilience.