I am a Ph.D. candidate in Computer Science at the University of Massachusetts Amherst. I joined the AHHA Lab, advised by Prof. Sunghoon Ivan Lee.

My research interests:

Health Informatics / Digital Health / Wearable Sensors:
- Applying machine learning to human movement data from IMU sensors or videos for diagnosing and monitoring patients
- Designing patient‑centered, personalized health information systems
Machine learning, Deep learning

I worked as a research engineer at Robotics Lab., CTO division, LG Electronics for about five years (from July 2014 to March 2019). I received the M.S. degree in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST) and the B.S. degree in Electronics Engineering from Ewha Womans University.

I'm on the job market—I am currently seeking industry or postdoctoral opportunities.

My CV [pdf] / My Resume [pdf]

My LinkedIn profile [link]

My Google scholar [link]

My E-mail: juhyeonlee at cs dot umass dot edu

News

Our paper "Contrastive Learning Model for Wearable-based Ataxia Assessment" is now available on medRxiv as a preprint. Please check out our paper! [html][pdf]
Our paper "Evaluating the Responsiveness of Wearable-Based Motor Assessment for Stroke Upper-Limb Impairments" will be presented at the IEEE BSN 2024 conference in October! Please check out my paper! [pdf]
I worked as a Machine Learning Engineer Intern at Apple Inc. during Summer 2023.

Journal Publications

[J5] Juhyeon Lee, Brandon Oubre, Jean-Francois Daneault, Christopher D. Stephen, Jeremy D. Schmahmann, Anoopum S. Gupta*, and Sunghoon Ivan Lee*, "Contrastive Learning Model for Wearable-based Ataxia Assessment", medRxiv preprint, March 2025 [*Co-corresponding authors] [html][pdf]

[J4] Juhyeon Lee, Brandon Oubre, Jean-Francois Daneault, Sunghoon Ivan Lee*, and Anoopum S. Gupta*, "Estimation of Ataxia Severity in Children with Ataxia-telangiectasia using Ankle-worn Sensors", Journal of Neurology, pp.1-5, June 2023 [*Co-corresponding authors] [html]

[J3] Hee-Tae Jung, Yoojung Kim, Juhyeon Lee, Sunghoon Ivan Lee*, and Eun Kyoung Choe*, "Envisioning the Use of In-Situ Arm Movement Data in Stroke Rehabilitation: Stroke Survivors’ and Occupational Therapists’ Perspectives", PLOS ONE, 17(10), e0274142, Oct 2022 [*Co-corresponding authors][html]

[J2] Juhyeon Lee, Brandon Oubre, Jean-Francois Daneault, Christopher D. Stephen, Jeremy D. Schmahmann, Anoopum S. Gupta*, and Sunghoon Ivan Lee*, "Analysis of Gait Sub-Movements to Estimate Ataxia Severity using Ankle Inertial Data", IEEE Transactions on Biomedical Engineering (IEEE TBME), vol. 69, no. 7, pp. 2314-2323, July 2022 [*Co-corresponding authors]. [html][poster]

[J1] Minhae Kwon, Juhyeon Lee, Hyunggon Park, "Intelligent IoT Connectivity: Deep Reinforcement Learning Approach", IEEE Sensors Journal, vol. 20, no. 5, pp. 2782-2791, March 2020. [link]

Conference / Workshop Publications

[C4] Juhyeon Lee, Bethany Dombrow, Mary Ellen Stoykov, Sunghoon Ivan Lee, "Evaluating the Responsiveness of Wearable-Based Motor Assessment for Stroke Upper-Limb Impairments", IEEE Intl. Conf. on Body Sensor Networks (IEEE BSN), Oct 2024. (Oral Presentation)

[C3] Juhyeon Lee, Hee-Tae Jung, Sunghoon Ivan Lee, "Estimating the Quality of Reaching Movements in Stroke Survivors", IEEE Intl. Conf. on Biomedical and Health Informatics (IEEE BHI), July 2021. [pdf][poster]

[W2] Minhae Kwon*, Juhyeon Lee*, Hyunggon Park, "Learning To Activate Relay Nodes: Deep Reinforcement Learning Approach", Neural Information Processing Systems (NeurIPS) Deep Reinforcement Learning Workshop, 2018. (*equal contribution) [arxiv]

[W1] Minhae Kwon*, Juhyeon Lee*, Hyunggon Park, "Self-activating Relay Nodes for Emergent Communications", Neural Information Processing Systems (NeurIPS) Emergent Communication Workshop, 2018. (*equal contribution) [arxiv]

[C2] Juhyeon Lee, Jae Hyun Lim, Hyungwon Choi, Dae-Shik Kim, "Multiple Kernel Learning with Hierarchical Feature Representations", In Proceedings of International Conference on Neural Information Processing (ICONIP), 2013. [pdf]

[C1] Jun-Cheol Park, Jae Hyeon Yoo, Juhyeon Lee, Dae-Shik Kim, "Apparent Volitional Behavior Selection Based on Memory Predictions", In Proceedings of International Conference on Neural Information Processing (ICONIP), 2012. [pdf]

Google Sites

Report abuse