About Me

I'm a second year PhD student at Cornell University studying computer science. I'm currently a visiting student at the Kempner Institute at Harvard University, working with Kianté Brantley. I'm broadly interested in the intersection of generative modeling and reinforcement learning, and in how we can design RL algorithms to more efficiently or effectively optimize pretrained generative models for difficult tasks.

Prior to starting my PhD, I worked as a software engineer in the Debora Marks Lab at Harvard Medical School, applying machine learning methods to problems in biological sequence modeling. Before that, I received my master's in computer science from the University of Oxford, and prior to that (a while ago now) I studied computer science and political science at Brown University.

Publications

ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design
Daniel Ritter*, Pascal Notin*, Lood Van Niekerk*, Aaron W Kollasch*, Steffanie Paul, Han Spinner, Nathan J. Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora S. Marks
NeurIPS, 2023
[link]
Learning from prepandemic data to forecast viral escape
Nicole N. Thadani*, Sarah Gurev*, Pascal Notin*, Noor Youssef, Nathan J. Rollins, Daniel Ritter, Chris Sander, Yarin Gal, Debora S. Marks.
Nature, 2023
[link]

TranceptEVE: Combining family-specific and family-agnostic models of protein sequences for improved fitness prediction
Pascal Notin, Lood Van Niekerk, Aaron W Kollasch, Daniel Ritter, Yarin Gal, Debora S. Marks
NeurIPS Learning Meaningful Representations of Life Workshop, 2022
[link]

Assessing the Interpretability of Large Language Models
Daniel Ritter, Lisa Schut, Andrew Jesson, Been Kim, Yarin Gal
Master's Thesis, 2022
[link]

Multiagent Planning via Partial Coordination in Markov Games
Daniel Ritter, Mark Ho, Michael Littman
Undergraduate Honor's Thesis, 2021
[link]

DeepLTLf: Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator
Homer Walke, Daniel Ritter, Carl Trimbach, Michael Littman
Arxiv preprint, 2021
[link]

*Equal author contribution