Intern at Intrinsic (Google) · PhD Candidate, graduating October 2026

I am a final-year PhD candidate in Stochastic Optimization for Deep Learning at the University of Basel (Switzerland), supervised by Prof. Dr. Aurelien Lucchi. I expect to graduate in October 2026.

I am currently an Intern at Intrinsic, a robotics company of Google, working at the intersection of robotics and scalable optimization.

I enjoy turning theory into training improvements you can measure. My current interests are:

1. Stochastic optimization for deep learning, from theory to optimizer design.
2. Reinforcement learning for robotics, including PPO-style training and large-scale hyperparameter optimization.
3. VLM/VLA systems for real-world robots, including agentic frameworks for multi-step tasks.
4. Efficient and private LLM training, including differentially private optimizers and chain-of-thought compression.

Before Intrinsic, I worked on robotics/VLM systems at Flexion Robotics, where I built an agentic framework that uses vision-language models to help robots execute multi-step tasks in real-world settings. Previously, I also worked in finance at UBS.

I like hard math, clean experiments, and systems that survive contact with real robots.

Drop me an email: eneamonziocompagnoni@gmail.com