Rashmi Ravishankar

Rashmi is a am a PhD graduate from MIT specializing in autonomous systems, with a focus on building and optimizing ML pipelines for real-world, resource-constrained environments. During her PhD, she developed reinforcement learning–based scheduling algorithms for heterogeneous compute systems (CPU/GPU/FPGA), optimizing throughput, latency, and resource utilization under real-world constraints such as memory, power, and thermal limits. She has also built and deployed large-scale ML pipelines for visual perception on aerial and satellite imagery, spanning data engineering, model development, and optimized inference. Previously, she worked on detecting and estimating photovoltaic capacity from aerial imagery, work that was recognized with the MIT MathWorks Prize for Outstanding Master’s Research. She also has industry experience building high-throughput data systems and production-grade software across aerospace and finance applications