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Ke Liu
Ph.D., Assistant Professor
Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University

RESEARCH INTERESTS
Soft robots, metamaterials, reconfigurable structures, compliant mechanisms, soft matter, design optimization, solid mechanics, differential geometry, AI for design


WORK EXPERIENCE

2022-present  Peking University, Beijing, China
                     Assistant Professor, Department of Advanced Manufacturing and Robotics

2019-2021     California Institute of Technology, Pasadena, CA, USA
                     Postdoctoral Scholar, Department of Mechanical and Civil Engineering, Supervisor: Chiara Daraio


EDUCATION

2014-2019    Georgia Institute of Technology, Atlanta, GA, USA
                    Ph.D. in Civil Engineering, Advisor: Prof. Glaucio H. Paulino

2016-2017    University of Tokyo, Tokyo, Japan
                    Visiting Research Student, Supervisor: Prof. Tomohiro Tachi

2012-2014    University of Illinois at Urbana-Champaign, Urbana, IL, USA
                    M.S. in Civil Engineering, Advisors: Prof. Glaucio H. Paulino, Prof. Paolo Gardoni

2009-2013    Zhejiang University, Hangzhou, Hangzhou, China
                    B.Eng. in Civil Engineering


HONORS AND AWARDS

2022  ASME Melville Medal

2020  Sigma Xi Best Ph.D. Thesis Awards (Georgia Tech)

2018  7OSME Gabriella & Paul Rosenbaum Foundation Travel Award

2017  Best poster at the 2nd Int. Workshop on Origami Eng.

2013  Outstanding Undergraduate Thesis (Zhejiang University)

 


JOURNAL PUBLICATIONS

See: Google Scholar (https://scholar.google.com/citations?user=kWjWFvAAAAAJ&hl)

ResearchID (https://publons.com/researcher/3039407/ke-liu/)

 

  1. D. Misseroni, P. P. Pratapa, K. Liu, G. H. Paulino. Experimental realization of tunable Poisson’s ratio in deployable origami metamaterial. Extreme Mechanics Letters, 53, 101685, 2022.
  2. L. Wang, J. Boddapati, K. Liu, P. Zhu, C. Daraio, W. Chen. Mechanical cloak via data-driven aperiodic metamaterial design. PNAS, 119 (13), e2122185119, 2022.
  3. K. Liu, F. Hacker, C. Daraio. Robotic surfaces with reversible, spatiotemporal control for shape morphing and object manipulation. Science Robotics, 6:eabf5116, 2021.
  4. K. Liu, T. Tachi, G. H. Paulino. Origami metamaterial with metastable phases through mechanical phase transitions. ASME Journal of Applied Mechanics, 88(9): 091002,2021.
  5. K. Liu, L. Novelino, P. Gardoni, G. H. Paulino. Big influence of small random imperfections in origami-based metamaterials. Proceedings of the Royal Society – A, 476: 20200236, 2020. Featured on the cover.
  6. K. Liu, T. Tachi, G. H. Paulino. Invariant and smooth limit of discrete geometry folded from bistable origami leading to multistable metasurfaces. Nature Communications, 10: 4238, 2019.
  7. K. Liu, T. Zegard, P. P. Pratapa, and G. H. Paulino. Unraveling tensegrity tessellations for metamaterials with tunable stiffness and bandgaps. Journal of the Mechanics and Physics of Solids, 131:147-166, 2019.
  8. P. P. Pratapa*, K. Liu*, and G. H. Paulino. Geometric mechanics of origami patterns exhibiting Poisson's ratio switch by breaking Mountain and Valley assignment. Physical Review Letters, 122:155501, 2019. *co-first author.
  9. K. Liu, G. H. Paulino. Tensegrity topology optimization by force maximization on arbitrary ground structures. Structural and Multidisciplinary Optimization, 59(6):2041-2062, 2019.
  10. K. Liu, G. H. Paulino. Nonlinear mechanics of non-rigid origami: An efficient computational approach. Proceedings of the Royal Society–A. 473:20170348, 2017.
  11. K. Liu*, J. Wu*, G. H. Paulino, and H. J. Qi. Programmable Deployment of Tensegrity Structures by Stimulus-Responsive Polymers. Scientific Reports. 7:3511, 2017. *co-first author. In collections: Top 100 in Materials Science, Editor’s choice.
  12. K. Liu, G. H. Paulino, P. Gardoni. Segmental multi-point linearization for parameter sensitivity approximation in reliability analysis. Structural Safety, 62:101-115, 2016.
  13. K. Liu, G. H. Paulino, P. Gardoni. Reliability-based topology optimization using a new method for sensitivity approximation - application to ground structures. Structural and Multidisciplinary Optimization, 54(3):553-571, 2016.