About Me

Owen Dugan Headshot

Hi, I'm Owen, a Hertz Fellow pursuing a PhD at Stanford University under the guidance of Professor Chris Ré. Artificial intelligence fascinates me, and in my research I design better machine learning systems and algorithms.

I am fortunate to be funded by the Hertz Fellowship, the Knight-Hennessy Scholarship, and the NSF Graduate Research Fellowship.

Previously, I studied the intersection of AI and physics at MIT with Professor Marin Soljačić, where I was awarded the Outstanding Undergraduate Research Award from the School of Science.

MIT Stanford Hertz Foundation Knight-Hennessy Scholars

Contact

Feel free to contact me. I'm open to collaborations and conversations regarding my research in machine learning, AI systems, or related areas.

Blog Posts

Selected technical blog posts from the Hazy Research group at Stanford.

3) Benjamin Spector, Jordan Juravsky, Stuart Sul, Dylan Lim, Owen Dugan, Simran Arora, Chris RéSeptember 2025
"We Bought the Whole GPU, So We're Damn Well Going to Use the Whole GPU"
A full throughput-focused, 8x-tensor-parallel inference megakernel for Llama 70B. Read Post →
2) Benjamin Spector, Jordan Juravsky, Stuart Sul, Dylan Lim, Owen Dugan, Simran Arora, Chris RéSeptember 2025
"How Many Llamas Can Dance in the Span of a Kernel?"
A full throughput-focused, 8x-tensor-parallel inference megakernel for Llama 70B (overview). Read Post →
1) Benjamin Spector, Jordan Juravsky, Stuart Sul, Owen Dugan, Dylan Lim, Dan Fu, Simran Arora, Chris RéMay 2025
"Look Ma, No Bubbles! Designing a Low-Latency Megakernel for Llama-1B"
A low-latency Llama 1B decode megakernel. Read Post →

Select Awards, Accomplishments, and Affiliations

Hertz Fellowship Francis F. Lee Memorial Fellow 2025
Fannie and John Hertz Foundation
Hertz Fellow 2024
Fannie and John Hertz Foundation
Knight-Hennessy Scholar 2024
Stanford University Knight-Hennessy Scholarship
NSF Graduate Research Fellow 2024
National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP)
U.S. Patent Nos. 11,688,045 and 11,756,304 2023
US Patent & Trademark Office
164th place (top 5%) 2022
William Lowell Putnam Mathematical Competition
US Presidential Scholar 2021
US Department of Education
Phi Beta Kappa Member 2024
The Phi Beta Kappa Society
Sigma Pi Sigma Member 2024
The Sigma Pi Sigma Society
Outstanding UROP (Undergraduate Research) Award 2023
MIT School of Science
Neo Scholar 2022
Neo Venture Capital Firm
329th place (top 12%) 2021
William Lowell Putnam Mathematical Competition
Earned credit for 8 MIT classes prior to first semester 2021
MIT Advanced Standing Examinations
Davidson Fellows Scholar 2021
Davidson Institute
Regeneron Science Talent Search Scholar 2021
Regeneron Science Talent Search
RSI Scholar 2020
Research Science Institute
DoD Scholar 2020
Department of Defense
SAT Perfect Score (1600) 2020
College Board
Caroline D. Bradley Scholar 2016
Institute for Educational Advancement

Publications

Expect more soon!

14) Jerry Liu, Jessica Grogan, Owen Dugan, Ashish Rao, Simran Arora, Atri Rudra, Christopher Ré,2025
"Towards Learning High-Precision Least Squares Algorithms with Sequence Models"
  arXiv:2503.12295
13) Andrew Ma, Owen Dugan, Marin Soljačić,2025
"Predicting band gap from chemical composition: A simple learned model for a material property with atypical statistics"
  arXiv:2501.02932
12) Julia Balla, Sihao Huang, Owen Dugan, Rumen Dangovski, Marin Soljačić,2025
"AI-Assisted Discovery of Quantitative and Formal Models in Social Science."
Nature Humanities and Social Sciences Communications 12 Nature Link
11) Jerry Weihong Liu, Jessica Grogan, Owen M Dugan, Simran Arora, Atri Rudra, Christopher Re,2024
"Can Transformers Solve Least Squares to High Precision?"
Workshop on Efficient Systems for Foundation Models II @ ICML2024 Openreview Link
10) Owen Dugan, Donato Manuel Jimenez Beneto, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljačić,2024
"OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step"
  arXiv:2406.06576
9) Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljačić,2024
"QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation"
  arXiv:2406.00132
8) Owen Dugan,2024
"Machine Learning for Physics: from Symbolic Regression to Quantum Simulation"
MIT Undergraduate Physics Thesis Thesis Link
7) Owen Dugan, Peter Lu, Rumen Dangovski, Di Luo, Marin Soljačic,2023
"Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows"
Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii. PMLR 202. arXiv:2302.12235
6) Owen Dugan, Rumen Dangovski, Allan Costa, Samuel Kim, Pawan Goyal, Joseph Jacobson, Marin Soljačić,2023
"OccamNet: A Fast Neural Model for Symbolic Regression at Scale."
  arXiv:2007.10784
5) Owen Dugan,2021
"QiskiFT: Quantum Error Correction and Quantum Fault Tolerance Development Kit."
  druidowm.github.io/qiskift
4) Owen Dugan,2020
"Astronomy Will Not Trail Off: Novel Methods for Removing Satellite Trails from Celestial Images."
Journal of the American Association of Variable Star Observers, vol. 48, no. 2, p. 262. Abstract
3) Peyton Robertson, Connor Espenshade, Jay Sarva, Owen Dugan, Kalée Tock,2020
"An Automated Approach to Modeling Jupiter's Synchrotron Radiation from Radio Telescope Observations."
Astronomy Theory, Observations and Methods, vol. 1, no. 1, pp. 24-33. PDF Link
2) Owen Dugan, Thomas Robinson, Finnian Carmeci, Kalée Tock,2019
"CCD Measurements and Reclassification of WDS 07106+1543 to an Optical Double."
Journal of Double Star Observations, vol. 15, no. 1, pp. 119–129. PDF Link
1) Owen Dugan, James Krasner,2022
"Soup, Bones, and Shakespeare: Literary Authorship and Allusion in Middle-earth."
Mythlore, vol. 40, no. 2, pp. 105-120. PDF Link

Research Presentations and Posters

8) OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step December 2024
The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
7) QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation December 2024
The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
6) Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows March 2024
American Physical Society (APS) March Meeting
5) Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows July 2023
International Conference on Machine Learning
4) OccamNet: A Feed-Forward Neural Model for Symbolic Regression April 2023
MIT Conference on Artificial Neuroscience
3) Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows April 2023
NSF Institute for AI and Fundamental Interactions External (IAIFI) Advisory Board Review
2) Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows February 2023
NSF Institute for AI and Fundamental Interactions External (IAIFI) Mini Symposium
1) Astronomy Will Not Trail Off: Novel Methods for Removing Satellite Trails from Celestial Images May 2020
Joint Meeting, Society for Astronomical Sciences (SAS) and the American Association of Variable Star Observers (AAVSO 108th Spring Meeting)