Deploying machine learning models in adversarial environments with uncertain requirements.

I work at the intersection of machine learning and economics, with a focus on designing incentives that promote "good" participation in complex systems.

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I am co-founder and Chief Scientist at Arthur, where we develop and deploy enterprise-grade AI systems. I'm also a tenured professor of Computer Science at the University of Maryland, with a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS). I hold a PhD in computer science from Carnegie Mellon. At Maryland, I am also formally affiliated with the Applied Mathematics & Statistics, and Scientific Computation (AMSC) program, the Human-Computer Interaction Laboratory (HCIL), and the Maryland Transportation Institute (MTI).

You can read more about Arthur in this Wired article. If you're interested in building scalable monitoring solutions for AI systems, get in touch; we're hiring! I also actively advise, and more recently invest in, startups; I have a soft spot for UMD- and CMU-founded firms. An example is GovShop, which provides market intelligence to public sector buyers and suppliers. And, a while ago, I built the earliest allocation and pricing products at Optimized Markets.

The academic research that I have and continue to lead has been supported by an NSF CAREER award, as well as by current or recent grants from NIST, NSA, DARPA, ARPA-E, NIH (R01), NSF, and generous gifts from industry partners such as Google. Previously, I was supported by a Facebook Fellowship (2015–2017), Siebel Scholarship (class of 2016), and an NDSEG Fellowship (2012–2015). Recently, I've become involved with worldwide blood donation, primarily through a visiting research position at Facebook. I've also been heavily involved in the world of organ allocation for more than a decade, primarily through the United Network for Organ Sharing (UNOS).