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LLMs ↔ Large Recommender Models.

TPUs + Neural recommenders @ Google Brain.

I started working on improving job scheduling at Google using (1) machine learning (DNNs) to help reduce interference between jobs, and (2) optimization of job placement to improve job throughput.I have also been working on various other analytical and optimization projects (how to *safely* overcommit resources, improving the flash usage efficiency of a big storage system, improving the load balancing of the Google file system).

I increased the utilization of flash at Google by *several orders of magnitude*. This required building pipelines to characterize workloads, implement optimization algorithms that decide which workloads to put on flash (and for how long), and building dashboards to help internal customers understand their workloads.

Visiting Scholar at General Motors R&D working on Vehicular Networks

Worked on a research project titled "Compressed Wireless Sensing"

Worked on various topics related to Speech Recognition and built a Speech Recognizer