AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
Scientific Reports
Web CV
Austin Clyde
Computer scientist working across AI for science, high-performance computing, drug discovery, and Harvard STS research on the legitimacy of algorithmic systems. Former quantitative developer.
2xGordon Bell Special Prize awardee
HKSHarvard STS fellow
2CACHE PI challenges
Research Interests
AI for science, high-performance computing, large language models, computational drug discovery, quantitative systems, interpretability, algorithmic accountability, and science and technology studies.
Experience
Science
AI for science and high-performance computing
At Argonne, I worked on AI/HPC systems for computational drug discovery, COVID-19 response, molecular modeling, and predictive oncology. This work included two ACM Gordon Bell Special Prize winning teams, 2021 finalist teams, DOE Secretary's Honor Award recognition, and the 100x faster SARS-CoV-2 docking paper.
STS
Science, technology, democracy, and legitimacy
As a visiting research fellow in Harvard Kennedy School's Program on Science, Technology, and Society, I studied how AI changes scientific practice, public reasoning, rights, and democratic participation.
Leadership
Drug-discovery grants, teaching, talks, and mentoring
I led two CACHE computational hit-finding challenge projects as PI, taught AI/human-rights and computer science courses at the University of Chicago, gave 24 presentations and invited talks, and mentored students across LLMs, genomics, docking, graph neural networks, and virtual ligand discovery.
Systems
Former quantitative developer
Former quantitative developer at Cubist Systematic Trading / Point72 and desk developer at XR Trading, with experience in performance-sensitive trading systems and infrastructure.
Earlier
Investment research and systems background
Earlier experience includes an investment associate internship at Bridgewater Associates and systems work before doctoral research.
Education
2022
Ph.D., Computer Science, University of Chicago
Thesis: Artificial Intelligence and High-Performance Computing for Accelerating Structure-Based Drug Discovery. Advisor: Rick Stevens.
2019
M.S., Computer Science, University of Chicago
2019
B.A., Mathematics with general honors, University of Chicago
Awards and Recognition
- Two-time ACM Gordon Bell Special Prize award team member: 2022 for GenSLMs and 2020 for AI-driven multiscale simulations of SARS-CoV-2 spike dynamics.
- ACM Gordon Bell Special Prize 2021 finalist teams for #COVIDisAirborne and Intelligent Resolution.
- Special recognition in the U.S. Department of Energy Secretary's Honor Award for COVID-19 research.
- Pozen Family Center for Human Rights Graduate Lectureship.
- Impact Argonne Award for Discovery and for Innovation.
Grants and Research Leadership
PI
CACHE Challenge 2: SARS-CoV-2 NSP13 ligand discovery
Principal Investigator for computational hit-finding work targeting the conserved RNA binding site of SARS-CoV-2 NSP13.
PI
CACHE Challenge 1: LRRK2 WDR domain hit prediction
Principal Investigator for a computational hit-finding challenge focused on the WDR domain of LRRK2.
Key personnel
IMPROVE, Autonomous Discovery for Science, and RadBio-AI-3
Key personnel and milestone-author roles on large AI-for-science programs across oncology model evaluation, autonomous discovery, and radiation biology.
Selected Publications
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics
International Journal of High Performance Computing Applications
Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors
Science
Large Language Models for Science
Artificial Intelligence for Science
AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics
ACM Gordon Bell Special Prize 2020
AI for science and global citizens
Patterns
Teaching
2023
Is the Public Square Online? Human Rights and Democracy on Social Media
Instructor, University of Chicago Human Rights Program.
2022
AI, Algorithms, and Human Rights
Instructor. Cross-listed in Human Rights, Computer Science, and Media Arts and Design.
2021
Introduction to Computer Science II (C/C++)
Instructor, University of Chicago Department of Computer Science.
2020-2022
Computational Thinking
Instructor, University of Chicago Academic Achievement Program.
2020
Reinforcement Learning for Drug Discovery Practicum
Instructor, University of Chicago Master's Program in Computer Science.
2019
Machine Learning in Biology and Medicine
Graduate teaching assistant, University of Chicago Department of Computer Science.
Talks, Mentoring, and Service
- 24 presentations and invited talks across AI for science, drug discovery, democracy, synthetic biology, high-performance computing, and information integrity.
- Mentored students and early-career researchers working on LLMs and genomics, graph neural networks, reinforcement learning for drug discovery, and virtual ligand discovery.
- Organizer of AI and human-rights workshop programming between the University of Chicago Pozen Family Center for Human Rights and Harvard Kennedy School STS.
- Organizer for AI Across America, Democratizing AI at PASC, and Harvard STS Writing Group; co-host of the Science, Technology, and Society podcast for New Books Network.
Selected Public Writing
- Are Social Media Platforms a Legitimate Component of Democracy? Tech Policy Press, 2022.
- Algorithmic Systems Designed to Reduce Polarization Could Hurt Democracy, Not Help It Tech Policy Press, 2022.
- Human-in-the-Loop Systems Are No Panacea for AI Accountability Tech Policy Press, 2021.