I am a co-founder of Trustworthy AI, which was acquired by Waymo in 2021.
At Waymo, I continue Trustworthy AI's mission to build an automated test generation and risk modeling platform for safety-critical software.
My work spans the intersection of machine learning, optimization, statistics, and control theory.
Overall, I try to make computers faster and smarter on problems that matter to people.
Previously, I received a PhD at
Stanford, where my advisor was
John Duchi. My main research focused on distributionally robust optimization and rare-event simulation, and it involved many collaborations with Russ Tedrake at MIT.
I was a member of the
Machine Learning Group, and I also researched
medical applications of machine learning as part of the
Wearable Health Lab.
I was supported by a
Stanford Graduate
Fellowship and a Hertz Fellowship.
Before Stanford, I received an MPhil in Information Engineering at the
University of Cambridge
on a
Churchill Scholarship,
where I was advised by
Glenn Vinnicombe and
Carl Rasmussen. I received a BSE in Mechanical and Aerospace Engineering
at Princeton; my thesis advisor was
Naomi Leonard, and I also worked in the research groups of
Howard Stone and
Lex Smits.
I have been fortunate to work at and collaborate with companies including
Toyota Research Institute (TRI),
Quantifind,
Microsoft, and
Merck.
aman at trustworthy dot ai,
CV,
Linkedin,
Google scholar
Rate-informed discovery via Bayesian adaptive multifidelity sampling.
Aman Sinha*, Payam Nikdel*, Supratik Paul, Shimon Whiteson. CoRL 2024.
[link]
[pdf]
[arxiv]
Embedding synthetic off-policy experience for autonomous driving via zero-shot curricula.
Eli Bronstein*, Sirish Srinivasan*, Supratik Paul*, Aman Sinha, Matthew O'Kelly, Payam Nikdel, Shimon Whiteson. CoRL 2022.
Oral presentation.
[link]
[pdf]
[arxiv]
Neural bridge sampling for evaluating safety-critical autonomous systems.
Aman Sinha*, Matthew O'Kelly*, Russ Tedrake, John Duchi. NeurIPS 2020.
[link]
[pdf]
[arxiv]
[code]
[poster]
[slides]
[talk]
[press]
FormulaZero: distributionally robust online adaptation via offline population synthesis.
Aman Sinha*, Matthew O'Kelly*, Hongrui Zheng*, Rahul Mangharam, John Duchi, Russ Tedrake. ICML 2020.
[link]
[pdf]
[arxiv]
[code]
[slides]
[talk]
Efficient black-box assessment of autonomous vehicle safety.
Justin Norden*, Matthew O'Kelly*, Aman Sinha*. NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving, CVPR 2020 Workshop on Scalability in Autonomous Driving.
[arxiv]
[blog]
Digital biomarkers of spine and musculoskeletal disease from accelerometers: Defining phenotypes of free-living physical activity in knee osteoarthritis and lumbar spinal stenosis.
Christy Tomkins-Lane, Justin Norden, Aman Sinha, Richard Hu, Matthew Smuck. The Spine Journal, 2019.
Outstanding Paper Award.
[link]
Scalable end-to-end autonomous vehicle testing via rare-event simulation.
Matthew O'Kelly*, Aman Sinha*, Hongseok Namkoong*, John Duchi, Russ Tedrake. NeurIPS 2018.
[link]
[pdf]
[arxiv]
[code]
[poster]
[videos]
Certifying some distributional robustness with principled adversarial training.
Aman Sinha*, Hongseok Namkoong*, John Duchi. ICLR 2018.
Oral presentation.
[link]
[pdf]
[arxiv]
[code]
[slides]
[talk]
Objective measurement of function following lumbar spinal stenosis decompression reveals improved functional capacity with stagnant real-life physical activity.
Matthew Smuck, Amir Muaremi, Patricia Zheng, Justin Norden, Aman Sinha, Richard Hu, Christy Tomkins-Lane. The Spine Journal, 2018.
Outstanding Paper Award.
[link]
Adaptive sampling probabilities for non-smooth optimization.
Hongseok Namkoong, Aman Sinha, Steve Yadlowsky, John Duchi. ICML 2017.
[link]
[pdf]
[code]
[poster]
Objective measurement of free-living physical activity (performance) in lumbar spinal stenosis: are physical activity guidelines being met?
Justin Norden, Matthew Smuck, Aman Sinha, Richard Hu, Christy Tomkins-Lane. The Spine Journal, 2017.
Outstanding Paper Award Runner-up.
[link]
Learning kernels with random features.
Aman Sinha, John Duchi. NIPS 2016.
[link]
[pdf]
[code]
[poster]
Dynamic management of network risk from epidemic phenomena.
Aman Sinha, John Duchi, Nick Bambos. IEEE CDC 2015.
[link]
[pdf]
[slides]
Visualizing the very-large-scale motions in turbulent pipe flow.
Leo Hellström, Aman Sinha, Lex Smits. Physics of Fluids, 2011.
[link]
[pdf]
Past and present research collaborators (alphabetically by last name in reverse chronological order):
Payam Nikdel,
Supratik Paul,
Shimon Whiteson,
Eli Bronstein,
Matthew O'Kelly,
Sirish Srinivasan,
John Duchi,
Russ Tedrake,
Rahul Mangharam,
Hongrui Zheng,
Justin Norden,
Richard Hu,
Matthew Smuck,
Christy Tomkins-Lane,
Hongseok Namkoong,
Amir Muaremi,
Patricia Zheng,
Steve Yadlowsky,
Nick Bambos,
Leo Hellström,
Lex Smits