Govind Saraswat Email & Phone Number

Austin, TX, US

Austin, Texas, United States

Developing robust and renewable whole home energy solutions.

Greater Denver Area

• Research includes power system modeling and analysis, measurement-based operation and control, machine learning and optimization. Performed large scale Power Hardware-in-loop (PHIL) experiments for coordinating 50+.
• Developed scalable load forecasting and system identification algorithms for power systems with high penetration of distributed energy sources. Used random forest classifiers and deep neural network for non-intrusive.
• Analyzed the effects of cyber-attacks on state-of-art state estimation algorithms by designing realistic cyber-attack scenarios.

Greater Minneapolis-St. Paul Area

• Created cyber-secured distributed algorithms for cyber-physical networks with applications to smart micro grids. Implemented the algorithms on RaspberryPi clusters using NodeJS framework as a distributed controller.
• Fine-tuned the algorithm to handle real world delays and asynchrony achieving high-bandwidth (200 kHz) state updates for application toward secondary frequency regulations.
• Interfaced the distributed controller layer with high power commercial scale PV and battery inverters using Modbus communication protocol for sending power dispatch commands in micro grids for demand response.

Hyderabad Area, India

Bengaluru Area, India

• Developing high quality software in C++/Tcl for performing EM reliability analysis of microprocessors.

Santa Clara, CA

• Developed a new reliability analysis method using log-normal probability distribution and failure acceleration models to analyze the reliability of microprocessors due to Electromigration (EM). Method was able to.
• Implemented the method as a highly parallel C++ tool which can analyze designs with more than billion nodes. The implementation requires graph tracing of chip layout to match patterns for which model parameters are.
• Interfaced with the manufacturers (outside team) and other cross-function teams to understand and procure EM models for latest technology node and implement them quickly to enable fast EM verification.

University Of Minnesota - Twin Cities

1. Kalman filter based detection and identification of participatory modes of a flexure based nano-imaging systemAchieved high-bandwidth tracking of contribution of different modes of a nano-measurement probe (AFM) using a receding horizon Kalman filter. Further designed a linear unbiased estimator to detect and quantify the presence of higher modes in the.

Implemented BSIM4 (Berkeley Simulation) model for MOSFET in 'PSpice' and verified the results with another circuit simulator 'Spectre'. Programming was done in C++ on Microsoft.NET Framework.

Doctor Of Philosophy (Ph.D.), Electrical And Electronics Engineering

Bachelor Of Technology, Electrical Engineering