Aakanksha is pushing the frontier of agentic LLMs by leveraging RL techniques to enable autonomous self-improving agents, especially in software engineering at the startup Reflection AI. At Stanford, Aakanksha is co-teaching CS329A (Self-Improving AI agents) in Fall/Winter 2025 and is the Program Chair for MLSys 2026.
Before this, Aakanksha was the technical lead of the 540B PaLM model and lead researcher in Gemini at Google in pre-training, scaling, and fine-tuning of Large Language Models. She was also a core contributor in PaLM-E, MedPaLM, and Pathways project at Google. Prior to joining Google, she was a technical lead for several interdisciplinary research initiatives at Microsoft Research and Princeton University across machine learning and distributed systems.
Aakanksha completed her PhD in Electrical Engineering from Stanford University and was awarded the Paul Baran Marconi Young Scholar Award for the outstanding scientific contributions of her dissertation in the field of communications and Internet.
