Computer Science and Engineering
Bobby B. Lyle School of Engineering
Southern Methodist University
Eric Larson is an Assistant Professor in the department of Computer
Science in the Bobby B. Lyle School of Engineering,
Southern Methodist University. His main research interests are in
machine learning, sensing, and signal & image processing for
ubiquitous computing applications, in particular, for healthcare and
security applications. His work in both areas has
been commercialized and he holds a variety of patents for
sustainability sensing and mobile phone-based health sensing. He is
active in signal processing education for computer scientists and is an
active member of ACM. He received his Ph.D. in 2013 from the
University of Washington, where he was co-advised by Shwetak N. Patel
and Les Atlas. He received his B.S. and M.S. in Electrical Engineering
in 2006 and 2008, respectively, at Oklahoma State University, where he
was advised by Damon Chandler.
CSE Office: 451 Caruth Hall
Lyle School of Engineering
3145 Dyer Street, Suite 445
Dallas, TX 75205
SMU UbiComp Lab:
Johnson Square 189
I am looking for and passionate about investigating the role of technology in solving impactful problems.
If this interests you, please contact me
so that we can setup a time to chat about mutual interests and potential research projects.
I am an Assistant Professor in Computer Science
in the Bobby B. Lyle School of Engineering
, Southern Methodist University
I am a fellow of the Hunt Institute for Engineering Humanity, member
of the Darwin Deason Institute for Cyber-security, and member of the ATT center for virtualization.
I am a passionate teacher and researcher in
Computer Science. The most important aspect of a thriving research and
teaching community is culture. An open, mentoring culture is paramount
to creating an environment where ideas, concerns, and critiques can
contribute to student growth. I believe research culture can be shaped
in three ways: (1) being highly selective of grad-uate students when
setting up a research lab, (2) intermingling undergraduate and graduate
research, providing mentoring opportunities to graduate students, and
(3) teaching courses with opportunities to conduct meaningful research.
I believe my research lab exemplifies this quality; the lab itself
becomes a mentoring tool that exemplifies research methods to new
students by example.
I received my Doctorate from the University of Washington where I was a Intel Science and Technology fellow.
At UW, I was co-advised by Shwetak Patel
and Les Atlas
I also have an MS in Image Processing from Oklahoma State University, where I was advised by Damon Chandler
am an associate editor for the ACM Journal IMWUT. My work has been
published in numerous conferences and journals disseminated through
many different cross-disciplinary venues: IMWUT, Pediatrics, JBHI, JCI, ICIP,
UbiComp, CHI, DEV, WCCI, PerCom, PETRA, SPIE, and Pervasive, garnering
numerous best paper nominations. Please see my publication page
Google Scholar page
for more details.
When I am not working, I am spending time with my wife and three wonderful children.
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, I have a
passion for teaching and mentoring, and I view research as an ideal
opportunity to instruct the next generation of computer scientists and
engineers. I have positioned myself (with plenty of help from others)
in a unique role, supporting cyber-security, education, healthcare, and
sustainability applications via the integration of machine learning and
ubiquitous sensing. I have become increasingly interested in sensing
markers of health and context awareness using commonplace sensors. My
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
• Machine Learning and Deep Learning [Sponsored
• Cyber Security, Mobile Sensor Data Leakage [Sponsored
], Counterfeit Detection [Sponsored
• Context Aware Computing/Learning in Man-Machine Interfaces [Sponsored
• Mobile Health Computing [Sponsored
• Target-Ligand Virtual Screening
Copyright (c) 2013-present Eric Larson, eclarson.com. All rights reserved. Design by FreeCSSTemplates.org. Many design elements on this site are courtesy of Jon Froehlich.