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<h2>About Me</h2>
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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. 
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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.
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<h2>Publications</h2>
<b>ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design</b>
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<b>Daniel Ritter*</b>, 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
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<i>NeurIPS, 2023</i>
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[<a href="https://www.proteingym.org/">link</a>]
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<b>Learning from prepandemic data to forecast viral escape</b>
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Nicole N. Thadani*, Sarah Gurev*, Pascal Notin*, Noor Youssef, Nathan J. Rollins, <b>Daniel Ritter</b>, Chris Sander, Yarin Gal, Debora S. Marks.
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<i>Nature, 2023</i>
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[<a href="https://www.nature.com/articles/s41586-023-06617-0">link</a>]
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<b>TranceptEVE: Combining family-specific and family-agnostic models of protein sequences for improved fitness prediction</b>
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Pascal Notin, Lood Van Niekerk, Aaron W Kollasch, <b>Daniel Ritter</b>, Yarin Gal, Debora S. Marks
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<i>NeurIPS Learning Meaningful Representations of Life Workshop, 2022</i>
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[<a href="https://www.biorxiv.org/content/10.1101/2022.12.07.519495v1.full.pdf">link</a>]
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<b>Assessing the Interpretability of Large Language Models</b>
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<b>Daniel Ritter</b>, Lisa Schut, Andrew Jesson, Been Kim, Yarin Gal
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<i>Master's Thesis, 2022</i>
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[<a href="/assets/pdfs/msc_thesis.pdf">link</a>]
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<b>Multiagent Planning via Partial Coordination in Markov Games</b>
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<b>Daniel Ritter</b>, Mark Ho, Michael Littman
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<i>Undergraduate Honor's Thesis, 2021</i>
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[<a href="/assets/pdfs/thesis.pdf">link</a>]
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<b>DeepLTLf: Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator</b>
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Homer Walke, <b>Daniel Ritter</b>, Carl Trimbach, Michael Littman
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<i>Arxiv preprint, 2021</i>
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[<a href="https://arxiv.org/abs/2111.04147">link</a>]
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<p>*Equal author contribution</p>