Summary
Kshitij Lakhani is a performance-focused GPU and deep learning engineer with 7+ years of experience accelerating real-world workloads across genomics, medical imaging, and embedded systems. He combines low-level expertise in C/C++, CUDA, GPUDirect RDMA and FPGA integration with applied ML experience using TensorFlow/Keras, delivering deterministic, high-throughput data paths for heterogeneous systems. At NVIDIA and previously Roche and Exo he has shipped production-grade GPU kernels and system-level monitoring to reduce latency and memory bandwidth pressure in complex pipelines. His academic work at UC Davis—implementing direct FPGA-to-GPU DMA—highlights a practical bent for squeezing efficiency from hardware stacks while preserving data integrity. Outside of engineering he’s a competitive soccer player and outdoors enthusiast, a detail that mirrors his collaborative, results-driven approach.
7 years of coding experience
5 years of employment as a software developer
Master's degree Electrical & Computer Engineering, Master's degree Electrical & Computer Engineering at University of California, Davis
Bachelor of Engineering (B.E.) Electronics and Telecommunication , Bachelor of Engineering (B.E.) Electronics and Telecommunication at Savitribai Phule Pune University
English, Hindi, Marathi, Gujarati