About Me


My research leverages techniques from AI, machine learning, and computational cognitive science to predict human behavior under risk and uncertainty.

This page details some of my experience across academia and industry.

Some Random


This award was granted to Erik Schlicht for achieving a 4.9/5.0 overall student rating for a Research Methods course he instructed at Harvard University.

Certificate of Teaching Distinction

Harvard University


Methods for quantifying an entity's reaction to one or more communication signals by quantifying a probabilistic relationship...

US Patent

Number 8407026



  • Present

    Sr. Research Scientist

    Dr. Schlicht is currently working as a Senior Research Scientist in the Human-AI Innovation group at Dataminr, developing algorithms that improve the efficiency of HiTL operations. More specifically, he created unsupervised methods for workflow analysis and deployed NLP algorithms that are used for the intelligent allocation of tasks to human analysts, in addition to deploying an algorithm for detecting misinformation across multiple domains, such as COVID and Elections (US and International). Finally, he is currently deriving and evaluating models for estimating the risk associated with physical and human assets, given real-time alerting information.

  • 2020 - 2021
    BrainCallus Gaming Project


    Dr. Schlicht was the Founder of the BrainCallus Gaming Project and was responsible for all technical and business aspects of the company. The BrainCallus Gaming Project was an effort seeking to improve psychiatric decision-making by leveraging a combination of computational gaming, machine learning and cognitive science. He was developing the Brain Barn Series of games that contain modules capable of quantifying player perception, decision-making and movements.

  • 2016 - 2019
    Computational Cognition Group


    Dr. Schlicht was the Founder of the Computational Cognition Group (C2-g), LLC and was responsible for all technical and business aspects of the company. During his tenure as founder, he gained attention for leveraging multifidelity methods and computational gaming to design decision-support systems. He also developed a novel model to improve the prediction of NFL outcomes by exploiting oddsmaker decision biases.

  • 2015 - 2016
    University of Minnesota


    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.

  • 2014 - 2015

    Human Factors Engineer

    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.

  • 2011 - 2014
    MIT Lincoln Laboratory

    Technical (Research) Staff

    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.

  • 2010 - 2011

    Cognitive Scientist

    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.



  • 2007 - 2010
    Harvard University and Caltech

    Postdoctoral Associate

    While a postdoctoral researcher between Harvard University and Caltech, Dr. Schlicht developed a low-fidelity game 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, and resulted in a publication that was rated in the Top 5 Percent of all research output according to metrics by Altmetric.

  • 2000 - 2007
    University of Minnesota

    Doctorate (PhD)

    Major: Cognitive and Brain Sciences; Minor: Human Factors

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

  • 1994 - 1998
    Minnesota State University, Mankato

    Bachelor of Science (BSc)

    Major: Psychology; Minor: Biology

Examples of

Invited Talks

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