PhD Candidate · Power & Energy Systems · Control · Optimization · Machine Learning
Power and energy systems researcher and engineer specializing in intelligent buildings, optimization and control, and machine learning. Research focuses on scalable modeling and estimation of building thermal dynamics, building–grid simulation and co-simulation, and intelligent control of networked buildings for grid-edge applications. Additional work spans residential energy resiliency, home and community energy management, AC optimal power flow, distribution-grid analytics, renewable-energy forecasting, and data-driven modeling of energy systems.
Research focus: development of a framework for modeling and control of networked buildings, spanning building thermal modeling and estimation, scientific machine learning, building–grid co-simulation, and intelligent control. Major areas of study include Power Systems Analysis, Power Systems Dynamics and Control, and Estimation Theory.
Thesis: On Intelligent Control of Residential Energy Systems. Major areas of study include Machine Learning, Data Science, and Algorithmics, with research centered on intelligent control and simulation of residential energy systems.
Power and energy systems researcher and engineer specializing in intelligent buildings, optimization and control, and machine learning. Research focuses on scalable modeling and estimation of building thermal dynamics, building–grid simulation and co-simulation, and intelligent control of networked buildings for grid-edge applications. Additional work spans residential energy resiliency, home and community energy management, AC optimal power flow, distribution-grid analytics, renewable-energy forecasting, and data-driven modeling of energy systems.
Power and Energy SystemsIntelligent BuildingsBuilding Thermal Modeling and EstimationScientific Machine LearningModel Predictive ControlReinforcement LearningOptimizationDistributed Energy ResourcesDistribution SystemsBuilding–Grid Co-SimulationEnergy Resiliency
Developed modeling, estimation, simulation, and intelligent-control methods for networked buildings and grid-edge applications.
Developed computationally efficient grey-box, black-box, and scientific-machine-learning thermal models and building–grid simulation/co-simulation workflows for residential and commercial buildings.
Developed model-predictive-control and reinforcement-learning algorithms for home energy resiliency and mentored one graduate and two undergraduate researchers on related work.
Supported undergraduate Controls and Numerical Methods instruction for six semesters as a teaching assistant.
Completed MTech thesis research in solar and wind forecasting and conceptualized and developed the MATLAB GUI-based Solar & Wind Energy Estimation and Forecasting Application (SWEEFA).
Mentored two graduate students contributing to development of the forecasting platform.
T
Academic / Teaching
Jun 2024 – Aug 2024
Instructor — Computational Skills for MIRA Summer Bridge Program
Develop scalable distribution-grid simulation pipelines integrating CIM-based network models, distribution power flow, and graph-based topology validation for large feeder datasets.
Develop machine-learning methods using AMI data for secondary-distribution modeling and optimization-based tools for intelligent distribution-grid analytics and planning.
Washington State UniversityFramework for Modeling and Control of Networked BuildingsJan 2022 – PresentOPEN +
PhD research integrating control-oriented building thermal models; optimization- and Bayesian-inference-based estimation; black-box and scientific-machine-learning methods; scalable building simulation and data workflows; building–grid co-simulation; and intelligent control for grid-edge applications.
Washington State UniversityIntelligent Control of Residential Energy Systems / SmartCommunitySimJan 2024 – PresentOPEN +
MS Computer Science research developing a scalable residential-community simulation and benchmarking framework for baseline, rule-based, model-predictive-control, and reinforcement-learning controllers under on-grid and off-grid operation with heterogeneous distributed energy resources. This work extends the home-energy-resiliency research initiated at the University of Florida.
Washington State UniversityPower Systems Analysis Toolbox (PowerEdu.jl)Aug 2022 – PresentOPEN +
Julia-based power-systems analysis package developed from WSU coursework, with capabilities spanning Newton–Raphson power flow, continuation power flow, static state estimation, optimization, and ongoing power-system stability and transient simulation.
Washington State UniversityPower-System Control Algorithm Vulnerability Analysis using Network ScienceJan 2022 – Apr 2022OPEN +
Developed a modular Python power-system transient simulator with closed-loop control and communication capabilities, and evaluated degree centrality, PageRank, and eigenvalue-based analysis for identifying nodes critical to distributed frequency-control performance.
University of FloridaHome Energy ResiliencyJan 2019 – Dec 2021OPEN +
Developed model-predictive-control and reinforcement-learning methods for residential energy resiliency using rooftop PV, battery storage, controllable loads, and related home-energy resources. This research became the foundation for the later WSU MS Computer Science work on intelligent residential energy systems and community-scale simulation and control.
University of FloridaOptimal Control: Indirect and Direct Numerical MethodsAug 2019 – Dec 2019OPEN +
Implemented indirect Hamiltonian-boundary-value and direct collocation formulations for optimal-control problems in MATLAB, including nonlinear programming solved using IPOPT.
University of FloridaState-Feedback Set-Point Tracking ControlJan 2019 – Apr 2019OPEN +
Performed simulation-based system identification and designed a Linear Quadratic Regulator for set-point tracking using an estimated state-space model.
University of FloridaARMA Time-Series Modeling for Solar PV ForecastingAug 2018 – Dec 2018OPEN +
Developed ARMA forecasting models using least-squares and maximum-likelihood estimation and studied model order, training-data volume, and prediction timescale using real solar-generation data.
Indian Institute of Technology Bombay (IIT-B)Data Fault DetectionAug 2017 – Oct 2017OPEN +
Developed data-fault-detection algorithms for real building data collected using Raspberry-Pi-based sensors in collaboration with Dr. Anupama Kowli. Implemented SVM, ANN, wavelet, PCA, and hybrid PCA–wavelet methods in MATLAB using a modular software structure.
Sardar Patel College of EngineeringForecasting of Solar & Wind EnergyAug 2015 – Jun 2016OPEN +
MTech thesis project developing the Solar & Wind Energy Estimation and Forecasting Application (SWEEFA), a MATLAB GUI-based platform for plant-level solar and wind energy estimation, weather and generation-data preprocessing, ANN- and ARIMA-based forecasting, and automated WRF forecasting using Bash scripts on a four-node Raspberry Pi 2 cluster.
Sardar Patel College of EngineeringDTC Control of DFIGJan 2015 – Apr 2015OPEN +
Studied an ANN-based direct-torque-control strategy for a doubly fed induction generator, reproduced the method in SimPowerSystems/MATLAB, prepared an IEEE-style technical report, and presented the work as a departmental seminar.
Sardar Patel College of EngineeringVector Control of DFIGAug 2014 – Dec 2014OPEN +
Studied a vector-control strategy for a doubly fed induction generator, reproduced the method in SimPowerSystems/MATLAB, prepared an IEEE-style technical report, and presented the work as a departmental seminar.
University of WollongongReactive Power Capability of Distributed Energy SystemsFeb 2014 – Jun 2014OPEN +
Team project evaluating reactive-power support from DFIGs, solar inverters, and diesel generators. Led the DFIG component, interpreted IEEE research literature, and contributed to the technical report and presentation. Grade: A.
Veermata Jijabai Technological InstituteApplication of Vacuum Tubes in Sound Engineering and High-Frequency AmplificationAug 2011 – Jun 2012OPEN +
Final-year team project examining contemporary vacuum-tube devices and their potential applications in sound engineering and high-frequency amplification, with emphasis on technical-literature analysis, engineering reporting, and collaborative project work. Grade: A.
Participated in a competitive five-day winter school and conference focused on AI, optimization, and control for interdependent and low-inertia energy systems.
Engaged with researchers and presented a poster as part of a curated graduate cohort focused on theoretical advances in resilient power-grid operation.
