I’m a 3rd year PhD student at the MIT Computer Science & Artificial Intelligence Lab (CSAIL), where I am a member of the Laboratory of Financial Engineering advised by Professor Andrew W. Lo. My research is supported by the MIT Presidential Fellowship and the Mathworks Engineering Fellowship. I’ve spent time in industry at Replicate, Adobe Research, and BlueCove Limited.
I have a SM in Computer Science from MIT and a BS in Computer Science and Philosophy from Columbia Engineering. While I was an undergraduate at Columbia, I worked on problems in multimodal deep learning with Carl Vondrick. I was also involved in the entrepreneurial ecosystem on campus.
Outside of research, I enjoy running and cycling around Boston and NYC, sculling at Community Rowing, and reading nonfiction.
Research Interests
I work on the economic alignment of large language models (LLMs). Specifically, I examine the capabilities and limitations of LLMs as individual agents and assess their impact in complex systems like financial markets. By addressing real-world concerns about AI agents and their impact within the specific context of finance and economics, I believe we can make tangible strides towards a more nuanced approach to general AI alignment.
Publications
- Lo, Andrew W., and Jillian Ross (2024), Generative AI from Theory to Practice: A Case Study of Financial Advice, in An MIT Exploration of Generative AI. [MIT Press]
- Lo, Andrew W., and Jillian Ross (2024), Can ChatGPT Plan Your Retirement?: Generative AI and Financial Advice, Harvard Data Science Review (Special Issue 5). [HDSR] [Press]
- Ross, Jillian, Yoon Kim, and Andrew W. Lo (2024), LLM economicus? Mapping the Behavioral Biases of LLMs via Utility Theory, Conference on Language Modeling. [arXiv]
Talks
[July 2024] Harvard STAT S-115, Virtual
[June 2024] 9th International Pension Research Association Conference, Paris, France
[May 2024] New Frontier Advisors, Boston, MA, USA
Contact
If you’re interested in economic alignment, would like to collaborate, or have good biography recommendations, send me an email:
[firstname] [at] csail [dot] mit [dot] edu