My research largely centers around the question:
how can AI, computing, and algorithmic thinking improve science, society, and democracy?
My work is both constructive and critical for drug discovery, ranging from identifying an inhibitor of the 3CL-main-protease of SARS-CoV-2 (see PDB: 7LTJ) to novel applications of language models for navigating chemical space formulated as a lattice. I am passionate about translating computing developments to novel scientific approaches (and vice-versa) to better science (and produce tangible scientific results).
Recently, as an outgrowth of AI ethics, my work has asked the more powerful interpretive question:
how do we know when models are improving X, and how can we interpret them as decision-makers?
In science, for example, my work has pointed out that this question is more complicated than many treat it. And in terms of algorithmic justice, we ought to turn towards political theory rather than single notions of ethics. I ask how democratic institutions can channel algorithmic developments through the public? Social integration, deliberation, and, more generally, feeling at home in the world are decreasing under the current regime of AI thought. I’m currently a vising fellow at the Harvard Kennedy School’s Science and Technology Program, working on these new questions.