Dr. Eric Larson is a Hunt Institute Fellow and an associate professor in the computer science department at SMU. He is also a member of the Darwin Deason Institute for Cybersecurity, Center for Global Health, and SMU AT&T Center for Virtualization. Dr. Larson is a founding associate editor for the journal on Interactive, Mobile, Wearable, and Ubiquitous Technology (formerly UbiComp).
His research explores the interdisciplinary relationship of machine learning and signal/image processing with the fields of security, mobile health, education, psycho-visual psychology, human-computer interaction, and ubiquitous computing. Like most academics, he has a passion for teaching and mentoring, and views research as an ideal opportunity to instruct the next generation of computer scientists and engineers. He is in a unique role, supporting cyber-security, education, healthcare, and sustainability applications via the integration of machine learning and ubiquitous sensing, and has become increasingly interested in sensing markers of health and context awareness using commonplace sensors. His research supports many healthcare, educational, and security initiatives by creating applications that (1) manage and diagnose many chronic/infectious ailments, (2) help learners master educational topics, and (3) investigate information leakage in pervasive and mobile devices. His dissertation research has also had impact in the area of sustainable resource usage, where he created algorithms for monitoring water, gas, and electricity usage using machine learning (now a commercial product).
His work has also helped to develop applications for real time cognitive load monitoring, privacy implications of smartphones, newborn jaundice screening, and lung function measurement, among others. These projects have resulted in eight patents of which six have been commercialized by various companies including Google. He has secured over $6 million dollars in federal and corporate funding that support these various initiatives. Dr. Larson has published one textbook and disseminated his research in over 50 peer-reviewed conference and journal papers, garnering more than 3700 citations. He received received his Ph.D. from the University of Washington where he was an Intel Science and Technology fellow. At UW, he was co-advised by MacArthur Genius Fellow Shwetak Patel and IEEE Fellow Les Atlas. He also has an MS in Image Processing from Oklahoma State University, where he was advised by Damon Chandler.
When asked what motivates his work, he replied, “In my work, I hope to bridge the gap between evaluation techniques from human computer interaction and machine learning research and evaluation. Too often machine learning researchers do not appropriately scope their evaluation or use iterative HCI techniques in the design of the system. Through intersecting the research in these areas, I hope to help human subjects research become more computationally technical (in terms of the modeling performed) as well as helping to assist machine learning research in becoming more adaptive and rigorous in its application.”
When he is not working, he is spending time with his wife and three wonderful children, including bike riding, making home improvements, and drinking copious amounts of coffee.
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