Faculty Directory

Chen, Po-Yen

Chen, Po-Yen

Assistant Professor
Chemical and Biomolecular Engineering
Maryland Robotics Center
The Institute for Systems Research
Maryland Energy Innovation Institute
Room 1223C, 4418 Stadium Dr., Chemical & Nuclear Engineering Building, College Park, MD 20742-2111

Dr. Po-Yen Chen is currently an Assistant Professor in the Department of Chemical and Biomolecular Engineering at University of Maryland (UMD), College Park. He received a B.S. degree in Chemical Engineering from National Taiwan University (NTU) and a Ph.D. in Chemical Engineering from Massachusetts Institute of Technology (MIT). After his Ph.D., he was awarded Hibbitt Early Career Fellowship and served as an independent researcher at Brown University for 2 years, and then he worked as an Assistant Professor in the Department of Chemical and Biomolecular Engineering at National University of Singapore (NUS) for 2.5 years before he joined UMD. In 2019, Po-Yen received AME Young Investigator Award in 2018 and AIChE SLS Outstanding Young Principal Investigator Award. In 2020, he was named as Innovators Under 35 in Asia by MIT Technology Review and received AIChE 35 under 35 Award. In 2021, he is elected to Global Young Academy (GYA) and Fellow of Vebleo. In 2022, he received 2022 John C. Chen Young Professional Leadership Scholarship.

Po-Yen is an affiliate faculty member in the Maryland Robotics Center (MRC), and his research focuses on the intersections of nanomaterials self-assembly, artificial intelligence, and robot–human teaming. Po-Yen’s lab aims to automate the discovery of functional materials via artificial intelligence (AI)/machine learning (ML) and flexible robotic technologies. By implementing emerging active learning frameworks with robot-aided experiments, high-accuracy prediction models are being constructed to accelerate the development of various functional materials for a wide range of applications, including soft electronics, sustainable plastic substitutes, piezoresistive aerogels, smart soft robots, etc. By further implementing data augmentation and statistical analyses, Po-Yen can uncover the elusive recipe–structure–functionality correlations using a more efficient approach based on machine learning/robotic automation.


  • B.S., Chemical Engineering, National Taiwan University (NTU)
  • Ph.D., Chemical Engineering, Massachusetts Institute of Technology (MIT)
  • Hibbitt Independent Postdoctoral Fellowship, Brown University


  • Nano Research Young Innovator Award (2023)
  • Recipient of John C. Chen Young Professional Leadership Scholarship (2022)
  • National Academy of Engineering’s US Frontiers of Engineering Symposium Invitee (2022)
  • Member of Global Young Academy (GYA) (2021)
  • Finalist for UMD’s Invention of the Year Award (2020–2021)
  • Editorial Board Members for Robotics journal (2021)
  • MIT Technology Review (MIT TR) Innovators Under 35 in Asia (2020)
  • AIChE 35 under 35 Award (2020)
  • Inspiring Research Mentor Award in NUS High (2020)
  • AIChE-SLS Outstanding Young Principal Investigator Award (2019)
  • Journal of Materials Chemistry B Emerging Investigator (2019)
  • A*STAR AME Young Investigator Award (2018)

Dr. Po-Yen Chen's research group focuses on Accelerating the Development and Discovery of Advanced Functional Materials via Machine Intelligence and Human–Robot Teaming. Here are the ongoing research topics:

  • Programmable Texturing of 2D Materials for Stretchable/Wearable Electronics;

  • Accelerated Materials Design via Machine Intelligence/Learning and Lab Automation;

  • Metal Ion Intercalation and Assembly of 2D Materials;

  • Assembling Nanomaterials into Soft Machines.


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


  1. 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). (link)
  2. 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)
  3. K. Li^*, Z. Li^, Z. Xiong^, Y. Wang, H. Yang, W. Xu, L. Jing, M. Ding, J. Zhu, J. S. Ho, P.-Y. Chen*, “Thermal Camouflaging MXene Robotic Skin with Bio-Inspired Stimulus Sensation and Wireless Communication.” Advanced Functional Materials 2110534 (2022). (link).
  4. Y. Li, H. Yang, T. Zhang, S. Li, S. Li, T. Chen, S. He, J. Y. Lee, Y. Zhao*, P.-Y. Chen*, “Stretchable Zn-Ion Hybrid Battery with Reconfigurable V2CTx and Ti3C2Tx MXene Electrodes as A Magnetically Actuated Soft Robot.” Advanced Energy Materials 11, 2101862 (2021). (link)
  5. M. Ding, S. Li, L. Guo, L. Jing, S.-P. Gao, H. Yang, J. M. Little, T. U. Dissanayake, K. Li, J. Yang, Y.-X. Guo, H. Y. Yang, T. J. Woehl, P.-Y. Chen*, “Metal Ion-Induced Assembly of MXene Aerogels via Biomimetic Microtextures for Efficient Capacitive Deionization and Microsupercapacitors.” Advanced Energy Materials 11, 2101494 (2021). (link)
  6. L. Jing, Q. Xie, H. Li, K. Li, H. Yang, P. L. P. Ng, S. Li, Y. 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). (link)
  7. 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). (link)
  8. K. Li, T.-H. Chang, H. Yang, T. Li, F. Fu, P.-Y. Chen*, “Biomimetic MXene Textures with Enhanced Light-to-Heat Conversion for Solar Steam Generation and Wearable Thermal Management.” Advanced Energy Materials 9, 1901687 (2019). (link)

Racing Against R&D: AI, Collaborative Robotics Automates Wearable Tech Design

A hassle-free model to fabricate materials used in wearable sensors removes experimental barriers in design.

Po-Yen Receives 2022 John C. Chen Young Professional Leadership Scholarship

Scholarship supports leadership development of young professional chemical engineers.

New Wearable Sensor Modules with Edge Machine Learning for Avatar Reconstruction

Po-Yen Chen and Sahil Shah Published in Nature Communications Journal

Chen and Raghavan Nominated for UMD Invention of the Year

The winner will be announced at a ceremony on May 10.

Machine Intelligence Builds Soft Machines

UMD research team publishes study in Nature Machine Intelligence.