Alex Mariakakis

As a ubiquitous computing and human-computer interaction researcher, Alex Mariakakis’ work broadly identifies applications of machine learning and computer vision on sensor data for human-centered issues. His primary research is in mobile health, leveraging smartphone sensors to objectively measure symptoms that are typically judged qualitatively. Alex's two most cited projects, PupilScren and BiliScreen, leverage the smartphone camera to identify cases of an impaired pupillary light reflex (for traumatic brain injuries) and scleral jaundice (for pancreatic cancer). Alex's current research program seeks to combine passively collected sensor data with momentary assessments to support Bayesian diagnostics in contexts like influenza, Parkinson's disease, and mental health. 

Alex is an Assistant Professor in the Department of Computer Science at the University of Toronto. He received his Ph.D. in Computer Science and Engineering at the University of Washington. Alex's work is published in top-tier venues in his field, including CHI and IMWUT. His work has also been featured by many media outlets (e.g., BBC, National Geographic, and USA Today). Alex is a recipient of the National Science Foundation Graduation Research Fellowship, the Qualcomm Innovation Fellowship, and the Gaetano Borriello Outstanding Student Award at UbiComp 2018.