Summary
Pulkit Tandon is a research engineer with 8 years of experience building scalable, data-efficient ML systems and optimization tools for AI and cloud platforms. Currently at Granica (formerly NData/ProjectN), he focuses on data selection, compression, and cost-aware optimization for large-scale AI workloads. He holds an MS and is pursuing a PhD in Electrical Engineering from Stanford and has taught graduate courses there, including a new class on data compression. His industry work includes video encoding research at Netflix and practical lab-to-field hardware and measurement projects from earlier academic visits to EPFL and Syracuse. Known for bridging deep theoretical insight with production engineering, he combines signal-processing roots with hands-on systems design to reduce data and compute footprints in ML pipelines.
8 years of coding experience
Indian Institute of Technology Bombay
Doctor of Philosophy (Ph.D.) Electrical and Electronics Engineering, Doctor of Philosophy (Ph.D.) Electrical and Electronics Engineering at Stanford University