Chanakya Hingu
PhD student in Electrical & Biomedical Engineering
University of Nevada, Reno
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I am a Ph.D. student in Electrical and Biomedical Engineering at the University of Nevada, Reno (advisor: Dr. Xingang Fu) and an R&D engineer at Phase Technologies. My research focuses on translating algorithms into reliable silicon and firmware for power-electronic and embedded platforms, combining FPGA/DSP architectures, learning-enhanced control, and VLSI design. I build end-to-end prototypes—from modeling to hardware-in-the-loop to fieldable implementations—that advance energy efficiency, robustness, and real-time performance in converters, motor drives, and industrial power-quality systems.
Present Work
Phase Technologies: FFT-based harmonic characterization and mitigation integrated with hysteresis control; optimized dq-frame PI control for three-phase motor loads; neural augmentation of dq control under non-ideal conditions; fully FPGA-based dq control pipeline with sub-millisecond latency.
NSF #2402634 RAISE: CET: Rare-Earth-Free Magnet and AI-Driven Control for Power Generation, transmission, and Grid Integration of Offshore Wind
NSF #2131214 (CPS): Scalable, reliable, deep-learning–driven embedded control for renewable-energy integration, emphasizing real-time implementation and robustness.
NSF #2219733 (CPS): Resilient cyber-physical security framework for next-generation distributed energy resources at the grid edge (detection, response, and verification on embedded platforms).
Education
Ph.D in Electrical Engineering, (May, 2026)
University of Nevada, RenoMS in Electrical Engineering, (Aug, 2023)
Texas A&M University-KingsvilleB.E in Electrical Engineering, (Oct, 2020)
University of Mumbai
Research Interest
FPGA and ASIC design
Digital Design
Power Electronics
Renewable Energy
Cybersecurity & AI
Power Systmes and Control
News
Defended PhD Proposal Dissertation
Currently working on Active Front End Cotnrol and harmonics compensation
Currently working on single phase Active Front End scaling to high switching frequency
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