I have vast experience leveraging quantitative methods to understand and predict operational processes that involve complex human-technology interactions (AI and UX) to improve system-level efficiency and minimize the risk associated with errors in either AI or human performance.

Throughout my career in industry, I led high-profile projects that resulted in several deployed models, in addition to performing research at academic institutions such as Harvard, MIT, Caltech and the University of Minnesota.

I have experience operating as an individual contributor, in addition to leading technical teams either through formal scrums or informal meetings.

Research Topics


I developed algorithms across several domains to improve operational efficiency

Targeted Metrics

I enjoy producing metrics that quantify human performance in real-world settings

Human Modeling

I have a keen interest in predicting human performance under uncertainty and risk

Risk Quantification

I have vast experience quantifying risk across several mission critical environments

My Resume


Overview of my work across academia and industry


This section outlines my educational background

Sample Publications

21 Jul 2010

Behavioral Economics: Redefining a Poker Face

Schlicht, E.J., Shimojo, S., Camerer, C., Battaglia, P.R., & Nakayama, K. (2010). Human wagering behavior depends on opponents faces, PLoS ONE, 5(7): e11663. doi:10.1371/journal.pone.0011663.

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14 Aug 2012

Multifidelity Simulation for Aerospace Risk

Schlicht, E.J., Lee, R., Wolpert, D., Kochenderfer, M. , and Tracey, B. (2012). Predicting the behavior of interacting humans by fusing data from multiple sources. In the Proceedings of UAI-2012.

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30 Jan 2017

Multifidelity Simulation for Transportation Risk

Schlicht, E.J. & Morris, N. (2016). Risk Evaluation for In-vehicle Sign Information. MnDOT Report Number 2016-18.

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Media Coverage

12 Aug 2010

Scientific American

Article overviews my postdoctoral work that redefined an effective 'poker face'

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26 Mar 2013

Polygon Gaming

Article summarizes our MIT LL panel on Serious Gaming for investigating national security topics

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01 Nov 2017

ML Conf Interview

Interview with the Machine Learning Conference regarding my work on multifidelity simulation

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