Power Systems
Distribution systems, distributed energy resources, grid-edge applications, optimal power flow, and power-system modeling and control.
POWER · OPTIMIZATION · CONTROL · LEARNING
Ninad Kiran Gaikwad
Power & Energy Systems Optimization Control Scientific Machine Learning
Intelligent, scalable, and resilient energy systems.
Researching scalable modeling, estimation, optimization, simulation, and intelligent-control methods for buildings, distributed energy resources, and electric power systems.
RESEARCH IDENTITY
Intelligent energy systems, across models and decisions.
My work lies at the intersection of electrical power systems, optimization and control, and data-driven and physics-informed learning—with buildings and distributed energy resources as a major grid-edge application domain.
Optimization + Control
Model predictive control, optimal control, distributed optimization, estimation, and decision-making for energy systems.
ML + Scientific ML
Data-driven modeling, Bayesian estimation, deep learning, and physics-informed learning for buildings and power systems.
Reinforcement Learning
Sequential decision-making and learning-based control for residential and grid-edge energy-management problems.
Buildings + DER
Building thermal dynamics, HVAC, PV, battery storage, EVs, resiliency, building-grid co-simulation, and coordinated control.
Research communication · publications · conferences
SELECTED PUBLICATIONS
Recent work across buildings, optimization, and intelligent energy systems.
2026
Accepted · IEEE IAS 2026
Building Thermal Models using Real-World Data: Seasonal Transferability and Setpoint Sensitivity
Kunal Shankar, Ninad Gaikwad, Anamika Dubey
2026
IEEE PESGM 2026
Learning to Optimize: Gaussian Process Surrogates for Battery Energy Storage Coordination
D. Glover, A. Parajuli, N. Gaikwad, A. Jha, A. Dubey
2025
IEEE SmartGridComm 2025
Smart Residential Community Simulator for Developing and Benchmarking Energy Management Systems
Ninad Gaikwad, Anamika Dubey
2025
IEEE PESGM 2025
Comparing Building Thermal Dynamics Models and Estimation Methods for Grid-Edge Applications
Ninad Gaikwad, Kunal Shankar, Anamika Dubey, Alan Love, Olvar Bergland
ENGINEER + RESEARCHER
Working across academic research and applied power-system development.
PhD Candidate
Electrical Engineering and Computer Science · Washington State University
Lead Power Systems Developer
iGridSim · distribution-grid simulation, topology validation, AMI analytics, and scalable planning tools
My broader trajectory connects electrical power systems, controls, optimization, intelligent buildings, machine learning, scientific computing, and research software.
AboutCONNECT
