Erik Schlicht

Erik J Schlicht, PhD

Dr. Schlicht utilizes quantitative methods to investigate human decision making under uncertainty and risk. He leverages techniques from AI, machine learning, and computational cognitive science to understand real-world decision making. This expertise has been used to innovate across many different data-driven domains; a summary of his experience is below.


Experience Timeline

Computational Cognition Group, LLC

Founder | 2016-Present

Dr. Schlicht is the Founder of the Computational Cognition Group (C2-g), LLC and is responsible for all technical and business aspects of the company. During his tenure as founder, he gained attention for leveraging multifidelity simulation methods, in addition to developing a novel model to exploit decision-biases to improve the prediction of NFL outcomes.

University of Minnesota

Research | 2015-2016

Dr. Schlicht returned to the University of Minnesota to conduct research in the HumanFIRST Lab where he developed machine learning algorithms (e.g., Bayesian Networks, Support Vector Machine regression, Binary classification with Lasso) to predict human driving behavior. These models were then used to estimate the risk associated with candidate transportation technology by using the predictive models in multifidelity simulation.

Medtronic, Inc

Human Factors Engineer | 2014-2015

At Medtronic, Dr. Schlicht was part of a team that was responsible for developing next-generation Deep-Brain-Stimulation devices to help treat diseases, such movement disorders.

MIT Lincoln Laboratory

Technical (Research) Staff | 2011-2014

Dr. Schlicht was a researcher at MIT Lincoln Laboratory conducting research related to national security. He was responsible for developing a novel model to predict the decisions of interacting humans. The model defined a quantitative method to combine the results from low-fidelity simulations (e.g., novice in an online simulator) with high-fidelity simulations (e.g., expert in an immersive simulator) to evaluate when inexpensive low-fidelity data can be used to as a proxy for expensive high-fidelity simulations. Moreover, he was part of an effort to use Serious Games as a means to develop quantitative models of operational decision-making.

Aptima, Inc

Cognitive Scientist | 2010-2011

Dr. Schlicht was a Cognitive Scientist at Aptima and led several SBIR and STTR efforts on projects related to national security. In his brief time at Aptima, he was awarded one OSD contract for a biologically-inspired approach to automated scene estimation (BIS-E), in addition to successfully securing one patent for quantifying human reactions to communications.

Harvard University and Caltech

Postdoctoral Researcher | 2007-2010

While a postdoctoral researcher between Harvard University and Caltech, Dr. Schlicht developed a novel method to quantitatively investigate human decision-making in a competitive (zero-sum) task. This research received an enormous amount of public interest and has been covered by several major media outlets (see list below), and resulted in a publication that was rated in the Top 5 Percent of all research output according to metrics by Altmetric.

Harvard University, Wellesley College and the University of Minnesota

Course Instructor | Various Dates

Dr. Schlicht has instructed several undergraduate courses at the University of Minnesota, Wellesley College, and Harvard University. In 2009, he was awarded the Certificate of Teaching Distinction from Harvard University.


University of Minnesota

Ph.D., Cognitive and Brain Sciences, with Human Factors Minor | 2007

Thesis: Statistical Decision-Theory for Human Perception-Action Cycles

Minnesota State University, Mankato

B.S., Psychology, with Biology Minor | 1998


Schlicht, E.J. (2017). Exploiting oddsmaker bias to improve the prediction of NFL outcomes. arXiv: Statistical Applications.   [PDF]

Schlicht, E.J. & Morris, N. (2017). Estimating the risk associated with candidate transportation technology through multifidelity simulation. arXiv: Statistical Applications.   [PDF]

Schlicht, E.J. & Morris, N. (2015). Risk evaluation of in-vehicle sign information.  MnDOT Technical Report Number 2016-18. [PDF]

Schlicht, E.J., Lee, R., Wolpert, D., Kochenderfer, M. , & Tracey, B.(2012). Predicting the behavior of interacting humans by fusing data from multiple sources. In the Proceedings of the Twenty-Eighth Conference of Uncertainty in Artificial Intelligence, (UAI-2012). [30% Acceptance Rate] [PDF]

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. [PDF]

Schlicht, E.J., & Schrater, P.R. (2007). Impact of coordinate transformation uncertainty on human sensorimotor control. Journal of Neurophysiology, 97(6), pp. 4203-14. [PDF]

Schlicht, E.J., & Schrater, P.R. (2007). Effects of visual uncertainty on grasping movements.  Experimental Brain Research, 182(1), 47-57.   [PDF]

Schlicht, E.J.  (2007). Statistical decision-theory for human perception-action cycles, Doctoral Thesis, University of Minnesota.   [PDF]

Stankiewicz, B.J., Legge, G.E., Mansfield, J.S., & Schlicht, E.J. (2006). Lost in virtual space: Studies in human and ideal spatial navigation. Journal of Experimental Psychology: Human Perception and Performance, 32, 688-704. [PDF]

Schrater, P.R., & Schlicht, E.J.  (2006). Internal models for object manipulation: Determining optimal contact locations, Technical Report TR 06-003, University of Minnesota.   [PDF]

Invited Talks

2017 | Stanford University

Intelligent Systems Laboratory | Palo Alto, CA

2017 | SAMSI

Summer Program on Transportation Statistics | Durham, NC - [Talk Slides]

2010 | MIT

Prelec Neuroeconomic Group | Cambridge, MA

2009 | MIT

Computational and Cognitive Sciences Group | Cambridge, MA

2009 | Harvard Medical School

Wolfe Laboratory | Cambridge, MA

2007 | Caltech

Shimojo and Andersen Laboratories | Pasadena, CA

2006 | MIT

Perceptual Sciences Group | Cambridge, MA

2005 | Harvard University

Vision Sciences Colloquium | Cambridge, MA

2004 | Institute for Mathematics and its Applications

Image Processing and Analysis Symposium | Minneapolis, MN

2002 | University of Minnesota

Vision Sciences Colloquium | Minneapolis, MN

Media Coverage

Press Coverage of Research (Abridged List)

Scientific American; ABC News (Boston, Channel 5); Boston Globe; New York Times (Freakonomics); Discover Magazine; Men’s Health; Reader’s Digest; BPS Research Digest; Life Hacker; Mind Hacks