Faculty Directory

Dr. Po-Yen Chen is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Maryland, College Park (UMD), with an affiliate appointment in the Department of Electrical and Computer Engineering. He is also a core member of the Maryland Robotics Center (MRC) and the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM). Dr. Chen earned his B.S. in Chemical Engineering from National Taiwan University (NTU) and his Ph.D. in Chemical Engineering from the Massachusetts Institute of Technology (MIT). Prior to joining UMD, he served as an Assistant Professor at the National University of Singapore (NUS) and conducted independent research as a Hibbitt Early Career Fellow at Brown University.

Awards  & Honors

2026                   Allan P. Colburn Memorial Lectureship of University of Delaware

2025                   Maryland Research Excellence Honoree of UMD

2024                   Shining Star Award, American Institute of Chemical Engineers (AIChE)

2023                   Winner of UMD’s Invention of the Year Award (Information Sciences)

2023                   Faculty–Student Research Award (FSRA) of UMD

2023                   Young Innovator Award by Nano Research, Springer

2022                   John C. Chen Young Professional Leadership Scholarship, AIChE

2022                   Innovative Early-Career Engineers, National Academy of Engineering (NAE)’s U.S. Frontiers of Engineering Symposium

2022                   Finalist of UMD’s Invention of the Year Award (Information Sciences)

2021                   Fellow of Vebleo

2021                   Member of Global Young Academy (GYA)

2020                   AIChE 35 Under 35 Award, AIChE

2020                   Innovator Under 35 in Asia, MIT Technology Review (MITTR)

2020                   Inspiring Research Mentor Award, NUS High School of Mathematics & Science

2019                   Outstanding Young Principal Investigator Award, AIChE Singapore Local Section

2019                   Emerging Investigator, J. Mater. Chem. B, Royal Society of Chemistry, UK

2018                   A*STAR AME Young Investigator Award, A*STAR, Singapore

2015                   Hibbitt Early Career Fellowship, Brown University, USA

2014                   MIT-Eni Energy Fellowship, MIT, USA

2013                   National Study Abroad Fellowship, Taiwan

2011                   MIT-Eni Energy Fellowship, MIT, USA

2009                   Dr. An-Tai Chen Scholarship (Best Undergraduate Researcher), NTU, Taiwan

2009                   Presidential Awards (Top 5% Undergraduates), NTU, Taiwan

Dr. Chen’s research operates at the convergence of machine learning (ML), robotic automation, and materials science. His group integrates predictive and generative modeling with automated experimentation to accelerate the discovery of high-performance, sustainable, and functional materials. By bypassing the bottlenecks of traditional trial-and-error methods, his work addresses complex challenges in multi-component formulation and multi-property optimization. This integrated workflow significantly accelerates the development of materials with programmable properties, targeting urgent global issues such as plastic pollution and resource depletion. The AI-discovered materials emerging from his lab have broad applications, ranging from biodegradable packaging and conductive aerogels to smart soft robotics and sustainable technologies.

Please see our full publication list on Our Group Website or Google Scholar.

In the publication list below, * indicates the corresponding author, and ^ marks equal contribution. My name is underlined, and contributions from my Ph.D., master’s, and undergraduate students are marked with #.

REPRESENTATIVE PUBLICATIONS

• H. Yang^#, Q. Chen, T. Chen^#, Y. Li^#, E. A. Norris^#, J. M. Little^#, J. Sun, S. Shrestha^#, E. Chen, S. Ren, T. Li*, P.-Y. Chen*, “Predictive Design of Ultrastretchable Electrodes with Strain-Insensitive Performance via Machine–Human Collaboration.” Nature Communications (2026).
• Y. Li^^,#, S. Schreiber^, H. Yang^#, M. Liu, J. M. Little^#, Y. Luo, Y. Bao*, C.-J. Shih*, H. Bai*, P.-Y. Chen*, “From Molecules to Machines: A Multiscale Roadmap to Intelligent, Multifunctional Soft Robotics.” Chemical Review 125, 8123 (2025).
• S. Shrestha^#, K. J. Barvenik, T. Chen^#, H. Yang^#, Y. Li^#, M. M. Kesavan^#, J. M. Little^#, H. C. Whitley^#, Z. Teng, Y. Luo, E. Tubaldi*, P.-Y. Chen*, “Machine Intelligence Accelerated Design of Conductive MXene Aerogels with Programmable Properties.” Nature Communications 15, 4685 (2024).
• T. Chen^^,#, Z. Pang^, S. He^^,#, Y. Li^#, S. Shrestha^#, J. M. Little^#, H. Yang^#, T.-C. Chung^#, J. Sun, I-C. Lee, T. J. Woehl, T. Li*, L. Hu*, P.-Y. Chen*, “Machine Intelligence-Accelerated Discovery of All-Natural Plastic Substitutes.” Nature Nanotechnology 19, 782 (2024).
• H. Yang^^,#, J. Li^, X. Xiao^, J. Wang^, Y. Li, K. Li^#, Z. Li, H. Yang^#, Q. Wang, J. Yang^#, J. S. Ho, P.-L. Yeh, K. Mouthaan, X. Wang, S. Shah*, P.-Y. Chen*, “Topographic Design in Wearable MXene Sensors with In-Sensor Machine Learning for Full-Body Avatar Reconstruction.” Nature Communications 13, 5311 (2022).
• H. Yang^^,#, J. Li^, K. Z. Lim, C. Pan, T. V. Truong, Q. Wang, K. Li^#, S. Li^#, X. Xiao, M. Ding^#, T. Chen^#, X. Liu, Q. Xie, P. Valdivia y Alvarado, X. Wang*, P.-Y. Chen*, “Automatic Strain Sensor Design via Active Learning and Data Augmentation for Soft Machines.” Nature Machine Intelligence 4, 84 (2022). (link)
• L. Jing^#, Q. Xie, H. Li, K. Li^#, H. Yang^#, P. L. P. Ng^#, S. Li^#, E. H. T. Teo, X. Wang*, P.-Y. Chen*, “Multigenerational Crumpling of 2D Materials for Anticounterfeiting Patterns with Deep Learning Authentication.” Matter 3, 2160 (2020).
• H. Yang^^,#, B. S. Yeow^, Z. Li^, K. Li^#, T.-H. Chang^#, L. Jing^#, Y. Li^#, J. S. Ho, H. Ren, P.-Y. Chen*, “Multifunctional Metallic Backbones for Origami Robotics with Strain Sensing and Wireless Communication Capabilities.” Science Robotics 4, eaax7020 (2019).