Yoonjin Won is a Professor of Mechanical and Aerospace Engineering at the University of California, Irvine, where she also holds courtesy appointments in Electrical Engineering and Computer Science, as well as Materials Science and Engineering. She earned her PhD from Stanford University (Nanoheat) and her undergraduate degree from Seoul National University. She is a recipient of the National Science Foundation CAREER Award, the ASME Electronic & Photonic Packaging Division Early Career Award, the ASME Electronic & Photonic Packaging Division Women Engineer Award, the ASME ICNMM Outstanding Leadership Award, the Emerging Innovation/Early Career Innovator from UCI Beall Innovation Center, Faculty Excellence in Research Awards (Mid-Career) from UCI, and numerous best paper and poster awards.
Research
The Won Lab studies physical scene understanding as it relates to heat and mass transfer, with a core mission of developing physically eXplainable AI models for the physical sciences. We build machines that don't just predict; they see, reason about, and explain the complex interactions of the physical world. Our research investigates the physics-informed representations needed to make AI predictions truly interpretable to scientists. We aim to answer fundamental questions about phase-change phenomena by drawing inspiration from both first-principles thermodynamics and human-like visual reasoning. Representative projects include VISION-iT, BubbleMask, BubbleML, and our frameworks for interpretable digitalized bubble statistics.
- Interpretable Thermofluidics: Leveraging machine learning to decode the underlying physics of phase-change phenomena. This research moves beyond black-box pattern recognition to establish causal relationships in boiling and condensation heat transfer.
- Trustworthy Design Optimization: Developing heterogeneous surfaces where AI-driven insights provide a clear physical rationale for specific nanostructure geometries and surface textures in next-generation high-flux heat sinks.
- Multi-Modal Sensor Fusion: Synthesizing high-fidelity data from high-speed imaging, infrared thermography, and acoustic emissions to provide a comprehensive, real-time diagnostic of various scenes.
Media
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08/2024
Four Engineers Win PoP Grants to Further Commercialization of Innovations
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05/2024
Department of Defense (DoD) for Multi-University Research Initiative (MURI) Investigating Thermal Energy Technologies is featured in UCI, UIUC engineering website (May 2024)
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11/2022
2022 Scientists and Engineers Early Career Development (SEED) Workshop is highlighted where Won was the director
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12/2021
Won’s work published at Advanced Science is highlighted
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11/2021
Journal cover is featured in UCI engineering website (Nov 2021)
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11/2021
Journal cover is featured in UIUC website (Nov 2021)
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11/2020
Early Career Innovator Award is featured in UCI and Innovation websites (Nov 2020)
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10/2020
ASME Women Engineer Award is featured in UCI engineering website (Oct 2020)
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09/2020
Journal cover is featured in UCI engineering website (Sep 2020)
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12/2019
Two Best Poster Awards are featured in UCI engineering website (Dec 2019)
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05/2019
Journal cover is featured in UCI engineering website (May 2019)
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09/2018
ASME Early Career Award is featured in UCI engineering website (Sep 2018)
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06/2018
Best Paper Award is featured in UCI engineering website (June 2018)
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04/2018
Prof. Won’s NSF CAREER is featured in UCI engineering website (April 2018)
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04/2018
Prof. Won’s paper is featured in IEEE and DARPA website (April 2018)
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11/2017
Best Poster Award is featured in UCI engineering website (Nov 2017)
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10/2016
UCI Dean’s report 2016, Hot Topic (Oct 2016)Link not available
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04/2016
UCI mechanical engineer sees tiny solution to big problem (April 2016)Appeared in engineering.uci.edu (Brian Bell): engineering.uci.edu
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12/2013
Stanford engineers show how to optimize carbon nanotube arrays for hot spots (Stanford Engineering Report)
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12/2013
University of Tokyo Research press: A flexible heat conductor using carbon nanotube arrays
Group
Students
Alumni
- Chuanning Zhao (PhD 2025) - Huawei
- Nicholas Choi (MS 2025) - Panasonic
- Youngjoon Suh (PhD 2023, Postdoc 2025) - Assistant Professor, University of Illinois Chicago
- Nhi Quach (PhD 2024) - NNSA Postdoctoral Fellow, Lawrence Livermore National Laboratory
- Changsu Kim (Visiting Scholar, 2024) - Hyundai Motors
- Jaiyoung Ryu (Visiting Scholar, 2023) - Professor, Korea University
- Keonwook Kang (Visiting Scholar, 2022) - Professor, Yonsei University
- Jewoo Park (Visiting Scholar, 2022) - Hyundai Motors
- Hunjae Kim (Visiting Scholar, 2022) - Hyundai Motors
- Cheng-Hui Lin (PhD 2021) - Taiwan Research Lab
- Kimia Montazeri (PhD 2021) - Google
- Jonggyu Lee (PhD 2021) - Samsung Electronics
- Ilhwan Kim (Visiting Scholar, 2021) - Samsung Electronics
- Quang Pham (PhD 2020) - Northrop Grumman
- Michael Barako (Visiting Scholar, 2020) - Northrop Grumman
- Jinseong Park (Visiting Scholar, 2020) - Professor, Hanyang University
- Shiwei Zhang (Postdoc, 2019) - Professor, South China University of Technology
- Pranav Dubey (MS 2017) - Intel
- Kuan-Wei Chen (MS 2017) - TSMC
Talks
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09/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer Invited2025 UCI-TAU Conference, 2025, invited speaker
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08/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer KeynoteThe 11th World Conference on Experimental Heat Transfer, Fluid Mechanics and Thermodynamics (ExHFT-11), Virtual, August 15-18, 2025, invited keynote speaker
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08/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer InvitedMini-Workshop, Choong-Ang University, Aug 2025. Hosted by Prof. Hyoungsoon Lee.
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08/2025
Machine Learning Applications in Two-Phase Heat Transfer for Advanced Thermal Management InvitedInternational Seminar on Thermal Management in High-Density Data Centers, Seoul, South Korea, August 11-12 2025, invited speaker
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06/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer PanelIIR Conference on Thermophysical Properties and Transport Processes of Refrigerants (TPTPR), the University of Maryland, June 15-18, 2025, invited panel speaker
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06/2025
Learning from Complexity: Machine Learning for Two-Phase Heat Transfer KeynoteMicro Flow and Interfacial Phenomena (µFIP), June 2025, Santa Babara, CA, invited keynote speaker
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02/2025
Applications of Machine Learning for Phase Change Heat Transfer PanelASME SHTC 2024, Feb. 2025, ASHRAE Winter Conference, Feb 4-8, Orlando, Florida, invited panel speaker
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11/2024
Emerging Technology Conference PanelInvited panel speaker, organized by Prof. and Dean A.-H. "Alissa" Park of UCLA.
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10/2024
2024 IEEE Symposium on Reliability for Electronics and Photonics Packaging Reliability (SiPho) KeynoteTheme: Reliability for Advanced Semiconductor Packaging, invited keynote speaker
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10/2024
Applications of Machine Learning for Heat Transfer in Electronics Cooling PanelASME InterPACK 2024, Oct 2025, San Jose, California, invited panel speaker
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07/2024
Fundamentals of Machine Learning for Phase Change Heat Transfer PanelASME SHTC 2024, July 2024, Anaheim, California, invited panel speaker
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05/2024
Artificial Intelligence: Industry use cases and investment trends PanelIEEE ITHERM 2024, May 2024, Denver, Colorado, invited panel speaker
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10/2023
Thermal Science, Engineering, and Management: AI and Machine Learning Perspectives PanelASME InterPACK 2023, Oct 2023, San Diego, California, panel moderator
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07/2023
Accelerating Thermal Science with AI Invited10th US-Japan Joint Seminar on Nanoscale Transport Phenomena, July 2023, San Diego, California, USA, invited speaker
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06/2023
Artificial Intelligence: Industry use cases and investment trends PanelIEEE ITHERM 2023, June 2023, Orlando, Florida, panel speaker
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03/2023
Artificial Intelligence for Two Phase Heat Transfer Invited8TH American Society of Thermal Fluids Engineering Conference, March 2023, College Park, Maryland, TEC talk, invited talk speaker
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01/2023
Learning Thermal Energy Science via Artificial Intelligent Techniques InvitedGordon Research Conference, Jan 2023, Italy, invited speaker
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08/2022
Advancing Thermal Energy Science on Bio-inspired Nanostructures via Artificial Intelligent Technologies KeynoteNature Inspired Surface Engineering (NISE 2022), Aug 2022, invited keynote speaker
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04/2022
The convergence of phase change phenomena, data, and art TalkSeoul National University Alumni Forum, April 2022. Hosted by Prof. Thomas Han.
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12/2021
The design of porous materials through machine learning algorithms KeynoteMRS Fall meeting, Dec 2021, keynote speaker
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10/2021
Issues, challenges, and future opportunities for nanomaterials integration into large systems PanelASME InterPACK 2021, Oct 2021, panel moderator
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10/2021
AI innovations, data-centric thinking, and opportunities in thermofluidic topics TalkmTAS, Oct 2021, workshop speaker
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06/2021
AI innovations, data-centric thinking, and opportunities in thermofluidic topics InvitedK-16 Hotspot placeholder, June 2021, invited speaker
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06/2021
AI innovations, data-centric thinking, and opportunities in thermofluidic topics KeynoteMicro Flow and Interfacial Phenomena, Virtual Version, June 2021, keynote speaker
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09/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer Invited2025 UCI-TAU Conference, 2025, invited speaker
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08/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer KeynoteThe 11th World Conference on Experimental Heat Transfer, Fluid Mechanics and Thermodynamics (ExHFT-11), Virtual, August 15-18, 2025, invited keynote speaker
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08/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer InvitedMini-Workshop, Choong-Ang University, Aug 2025. Hosted by Prof. Hyoungsoon Lee.
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08/2025
Machine Learning Applications in Two-Phase Heat Transfer for Advanced Thermal Management InvitedInternational Seminar on Thermal Management in High-Density Data Centers, Seoul, South Korea, August 11-12 2025, invited speaker
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06/2025
Fundamentals of Machine Learning for Phase Change Heat Transfer PanelIIR Conference on Thermophysical Properties and Transport Processes of Refrigerants (TPTPR), the University of Maryland, June 15-18, 2025, invited panel speaker
Publications
See the full list of publications at Google Scholar.