I'm a PhD student at Stanford working at the intersection of machine learning, optimization, and control. I try to make computers faster and smarter on problems that matter to people.
I work in the Artificial Intelligence Lab and Information Systems Lab, jointly advised by John Duchi and Nick Bambos. My recent research includes projects on fast methods for discovering feature representations, adaptive coordinate descent methods, and distributionally robust optimization. I'm supported by a William R. Hewlett Stanford Graduate Fellowship and a Hertz Fellowship.
Before Stanford, I received an MPhil in Information Engineering at the University of Cambridge, 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.
Certifiable Distributional Robustness with Principled Adversarial Training. Aman Sinha*, Hongseok Namkoong*, John Duchi. ICLR 2018. [arxiv]
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]
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]
Distributed consensus protocols in adaptive multi-agent systems. Aman Sinha. Princeton University Undergraduate Thesis, 2013. Awarded Morgan W. McKinzie '93 Senior Thesis Prize for best senior thesis. [link] [pdf]
Single-particle motion in colloids: nonlinear fluctuations in the presence of hydrodynamic interactions. Aman Sinha. Princeton University Junior-Year Independent Study, 2012. [link]