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Mike Schaekermann

University of Waterloo Computer Science Ph.D. candidate with a degree in Medicine

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Publications

Overview


Conference Papers

  1. Schaekermann, Mike, Giovanni Ribeiro, Guenter Wallner, Simone Kriglstein, Daniel Johnson, Anders Drachen, Rafet Sifa, and Lennart E Nacke. “Curiously Motivated: Profiling Curiosity With Self-Reports and Behaviour Metrics in the Game ‘Destiny.’” In CHI PLAY 2017. Amsterdam, Netherlands, 2017. doi:10.1145/3116595.3116603. View PDF
  2. Jaini, Priyank, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, and Pascal Poupart. “Online Bayesian Transfer Learning For Sequential Data Modeling.” In 5th International Conference On Learning Representations (ICLR 2017), 2017. View PDF
  3. Wehbe, Rina R, Elisa D Mekler, Mike Schaekermann, Edward Lank, and Lennart E Nacke. “Testing Incremental Difficulty Design In Platformer Games.” In Proceedings Of the 2017 CHI Conference on Human Factors in Computing Systems (CHI 2017), 5109–13. New York, New York, USA: ACM Press, 2017. doi:10.1145/3025453.3025697. View PDF

Workshop Papers

  1. Schaekermann, Mike, Edith Law, Alex C Williams, and William Callaghan. “Resolvable Vs. Irresolvable Ambiguity: A New Hybrid Framework for Dealing with Uncertain Ground Truth.” In 1st Workshop On Human-Centered Machine Learning at SIGCHI 2016. San Jose, CA, 2016. View PDF
  2. Williams, Alex C, Josh Bradshaw, Mike Schaekermann, Timmy Tse, William Callaghan, and Edith Law. “The Big Picture: Preserving Context In the Decomposition of Complex Expert Tasks.” In 1st Workshop On Microproductivity at SIGCHI 2016. San Jose, CA, 2016. View PDF

Thesis

  1. Schaekermann, Mike. “Implementation Of a Collaborative Web Application for Annotating Gameplay Videos Based on Biometric Player Data.” Bachelor’s thesis, Salzburg University of Applied Sciences, 2014. View PDF