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.

I am currently an AI Scholar at Samsung Research America, where I work on foundation models for wearable physiological signals.

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 Machine Learning Engineering Intern at Apple during the summer of 2023. 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", was selected as a Featured Article in the April 2026 issue of IEEE TBME!!
Our paper, “𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗦𝗲𝗹𝗳-𝗦𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗼𝗿 𝗪𝗲𝗮𝗿𝗮𝗯𝗹𝗲 𝗦𝗹𝗲𝗲𝗽 𝗦𝘁𝗮𝗴𝗶𝗻𝗴 𝗨𝘀𝗶𝗻𝗴 𝗣𝗵𝗼𝘁𝗼𝗽𝗹𝗲𝘁𝗵𝘆𝘀𝗺𝗼𝗴𝗿𝗮𝗽𝗵𝘆 𝗮𝗻𝗱 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗼𝗺𝗲𝘁𝗲𝗿 𝗦𝗶𝗴𝗻𝗮𝗹𝘀,” has been accepted at 𝗜𝗘𝗘𝗘 𝗜𝗖𝗔𝗦𝗦𝗣 𝟮𝟬𝟮𝟲!
Our paper "Contrastive Learning Model for Wearable-based Ataxia Assessment" has been accepted for publication in IEEE Transactions on Biomedical Engineering. Please check out our paper! [html][pdf]

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", IEEE Transactions on Biomedical Engineering (IEEE TBME), Accepted for Publication [*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

[C7] Juhyeon Lee, Simon A. Lee, Cyrus Tanade, Viswam Nathan, Megha Thukral, Hao Zhou, Keum San Chun, Sharanya Arcot Desai, "Multimodal Self-Supervised Learning for Wearable Sleep Staging Using Photoplethysmography and Accelerometer Signals", IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), 2026.

[C6] Simon A. Lee, Cyrus Tanade, Hao Zhou, Juhyeon Lee, Megha Thukral, Md Sazzad Hissain Khan, Keum San Chun, Baiying Lu, Migyeong Gwak, Mehrab Bin Morshed, Viswam Nathan, Md Mahbubur Rahman, Li Zhu, Subramaniam Venkatraman, Sharanya Arcot Desai, "HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series", The Fourteenth International Conference on Learning Representations (ICLR 2026). [html]

[C5] Juhyeon Lee, Aurora James-Palmer, Isaac Heitmann, Allison Bierly, Jean-Francois Daneault, Sunghoon Ivan Lee, "Improving Responsiveness in Game-based Cognitive Assessment for Mild Cognitive Impairment", IEEE Intl. Conf. on Body Sensor Networks (IEEE BSN), Nov 2025. [pdf]

[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) [pdf]

[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]

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