Sunil P. Khatri
Papers
1
Total Citations
4
H-Index
1
About
Sunil P. Khatri is a leading researcher in electronic design automation (EDA), VLSI design, and hardware acceleration for machine learning. His work bridges the gap between efficient digital circuits and emerging computational paradigms, with a particular focus on FPGA-based implementations. Among his notable contributions is the development of "TD3lite," a framework that introduces structural and representation optimizations to accelerate reinforcement learning (RL) on FPGAs. This work, published in 2022, addresses the computational bottlenecks of deep Q-learning and similar RL techniques by enabling faster neural network inference and training directly on reconfigurable hardware. With over 4 citations in a short time, this paper reflects Khatri’s impact at the intersection of hardware design and artificial intelligence. His broader portfolio includes pioneering work in logic synthesis, formal verification, and low-power design, often achieving significant improvements in performance and energy efficiency. Khatri’s research has been widely cited in top venues such as DAC, ICCAD, and IEEE Transactions, and he is recognized for mentoring students who have gone on to influential roles in academia and industry. His work continues to shape how complex algorithms are realized in silicon, making him a key figure in advancing both hardware and AI systems.
Research Focus
Key Achievements
Top Papers
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