Mountain View, California, United States
Experience in software development for distributed system, data analysis and optimization. Strong analytical background in combinatorial algorithms and discrete mathematics (Ph.D. in mathematics). Specialties: distributed systems, large scale data analysis, optimization, combinatorial algorithms, discrete mathematics, electronic design automation (logical and physical design), motion planning for autonomous vehicles and robotics, TPU systems.
Autoformalization of mathematical theorems and proofs. • Developed chess playing agents with OpenAI Agent SDK and Stockfish to demonstrate trace logging in the Morph Labs environment. • Prototyped a first version for the new Math.Inc Gauss app.
Platform Infrastructure Engineering for Accelerator Systems and ML Supercomputers: • Enhanced the resiliency of large scale Tensor Processor Unit (TPU) systems for large language model training and inference.
• Developed a new moving sorter induction strategy, enhancing robot station deployment capabilities. • Built and improved automatic tools for analyzing robot system performance, leading to targeted enhancements. • Fine-tuned and evaluated machine learning models for segmentation, object recognition, and grasp generation. • Enhanced motion planner for 6 degree-of-freedom robots, optimizing operational efficiency.
Motion planning for the autonomous vehicle. I worked in the Speed team and also with the Spacetime Search team. I focused on discomfort versus progress trade-off and worked on the interaction with reactive agents. I contributed to the working group on intersections for urban driving.
I worked in the Search Infrastructure Team on the analysis of the search components and on capacity planning. In the Storage Analytics Team I worked on using flash memory in addition to disk drives for globally distributed storage systems. Then I worked in the Network Architecture Team on the optimization and analysis of Google's backbone networks.