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Matthew Lee

HCI Researcher & Scientist


I am an expert in UX and Human-Computer Interaction research, with over 10 years of industry experience in B2B and B2C. My research interests lie at the intersection of ubiquitous computing, artificial intelligence, and applications in real-world problems of health and social connections.

My multi-disciplinary approach is grounded in extensive user experience research, building system prototypes, and analysis of qualitative and quantitative datasets for generating actionable insights and machine learning.

My research aims to bring about a more personalized and a more meaningful user experience for intelligent systems by making sense of people's data trails to reveal rich behavioral patterns and help people achieve their goals.

I am currently a Senior Research Scientist at FXPAL, where I am a Research Group Leader for the Ambient Computing Group. Prior to joining FXPAL, I founded an HCI group in personal and connected health at Philips Research North America.

I enjoy collaborating with others in academia and industry, so please contact me if you would like to discuss a project together.

Research & Design



Real-time Feedback for Video Calls

Faucett, H.A., Lee, M.L., and Carter, S. 2017.I Should Listen More: Real-time Sensing and Feedback of Non-Verbal Communication in Video Telehealth. Proceedings of the ACM on Human-Computer Interaction (abstract) (pdf)


"ReflectLive" (YouTube)



Focus Level Detection using Physiological Sensors

Matthew Lee. 2020. Detecting Affective Flow States of Knowledge Workers Using Physiological Sensors. arXiv:2006.10635 [cs].



Wellness through sensing and reflection

Lee, M.L. and Dey, A.K. 2014. Real-time Feedback to Improve Medication Taking. CHI 2014 (Best Paper Award) (abstract) (pdf)

Lee, M.L. and Dey, A.K. 2014. Sensor-based Observations of Daily Living for Aging in Place. Personal and Ubiquitous Computing. September 2014, pages 1-17. (abstract)

Lee, M.L. Task-based Embedded Assessment of Functional Abilities for Older Adults Doctoral Dissertation, August 2012 (abstract) (pdf)

Lee, M.L. and Dey, A.K. 2011. Reflecting on Pills and Phone Use: Supporting Self-Awareness of Functional Abilities for Older Adults. CHI 2011 (Best Paper Honorable Mention) (pdf)

Lee, M.L. and Dey, A.K. 2011. Smart Lifelogging Technology for Episodic Memory Support. In Smart Healthcare Applications and Services: Developments and Practices. Röcker, C. & Ziefle, M. (Eds.) IGI Global, 2011. (link)

Lee, M.L. and Dey, A.K. 2010. Embedded Assessment of Aging Adults: A Concept Validation. In Proceedings of PervasiveHealth 2010. (pdf)

Lee, M.L. 2010. Creating Salient Summaries of Home Activity Lifelog Data. CHI 2010 Doctoral Consortium. (pdf)


"CMU to research sensors to track elderly" (Pittsburgh Post-Gazette)

"Testing The Ability Of Embedded Sensors To Detect Onset Of Dementia, Infirmity" (Medical News Today)

"High tech helps elderly, impaired" (Pittsburgh Tribune-Review)



Capturing missing memories for Alzheimer's disease.

Lee, M.L. and Dey, A.K. 2008. Lifelogging Memory Appliance for People with Episodic Memory Impairment. Proceedings of the 10th International Conference on Ubiquitous Computing, (abstract)  (pdf)

Lee, M. L. and Dey, A. K. 2007. Providing good memory cues for people with episodic memory impairment. In Proceedings of the 9th international ACM SIGACCESS Conference on Computers and Accessibility 2007. (abstract)  (pdf)


A Little Black Box to Jog Failing Memory
The New York Times

A Helping Hand from a Robot
National Public Radio, IEEE Spectrum, NSF


Patient Engagement Tools

Assessing and coaching patients through behavior change

Hospital to Home: supporting patients to self-care (youtube)


Caregiver Coordination

Connecting individuals to create a circle of care

Patient Portal

Engaging patients with their own data

Disease Journey

Supporting health literacy for newly diagnosed patients


Download my CV here.


Email: matt [ at ]