Hi! I'm currently a Ph.D student at UC Berkeley, where I'm advised by Sanjit Seshia. My Ph.D. has been gratefully supported by the NDSEG Fellowship.

I research neuro-symbolic machine learning, with particular focus on applications in robotics, autonomy, and program synthesis. By integrating formal and logical symbolic structures into learning algorithms, I hope to improve the safety and reliability of ML-based systems.

I received my Bachelor's and Master's degrees from Rice University, where I worked on projects related to interpretable machine learning via program synthesis and formal methods. I was advised by Swarat Chaudhuri, who I worked with on the "Understanding the World Through Code" NSF Expeditions Project. As an undergrad, I also collaborated with Ankit Patel and Richard Baraniuk. I was fortunate to be supported by the Rice CS Graduate Fellowship.

I've spent time at Microsoft Research AI, where I worked with Alex Polozov and the GRAIL group on interactive ML-driven program synthesis. I also collaborated with Jon DeCastro and the Human-Aware AI team at TRI to improve learned behavior in safety-critical settings.

In my free time, I enjoy doing a lot of things, including but not limited to: playing tennis, reading novels, inventing new recipes, and repeatedly fixing and breaking my jumpshot. I'm originally from Cleveland, Ohio, and I love watching my beloved Cavaliers break my heart year after year.

You can find me on X or on Google Scholar. The best way to reach me is by sending me an email at ameesh@berkeley.edu.