Join CSAIL Alliances member Susquehanna in Stata to explore how deep learning has become central to modern quantitative trading.

Susquehanna machine learning researcher Tony Yang will share some of the research problems the team works on, from modeling large-scale market data to developing models that can adapt to changing market conditions. He’ll discuss what makes financial markets different from more familiar machine learning data modalities and benchmarks, how research ideas translate into trading signals, and how the academic research background has helped him explore new and interesting research directions in industry.

Whether you're considering an internship or full-time role, or have never seriously considered research outside academia, you're invited to join this open conversation. Tony and other members of the Susquehanna research team will offer Q&A and informal discussion after the talk.

PhD students in EECS, mathematics, statistics, physics, and related fields are especially welcome. No prior knowledge of finance or trading is needed.