Eley Ng

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Nanshu Lu (鲁南姝), Ph.D.Professor, the University of Texas at AustinVerified email at utexas.edu
Shixuan YangUniversity of Texas at AustinVerified email at utexas.edu
Ziang LiuPhD Student in Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Monroe Kennedy IIIAssistant Professor of Mechanical Engineering, Stanford UniversityVerified email at stanford.edu
George GorospeKBR @ NASA Ames Research CenterVerified email at nasa.gov
Shankar SankararamanData Scientist and Machine Learning, IntuitVerified email at intuit.com
Chetan S. KulkarniSenior Scientist at NASA Ames Research Center (KBR, Inc)Verified email at nasa.gov
Matthew J. DaiglePrincipal Scientist, NovityVerified email at novity.us

Eley Ng

Verified email at stanford.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Indium Tin Oxide (ITO) serpentine ribbons on soft substrates stretched beyond 100% S Yang, E Ng, N Lu Extreme Mechanics Letters 2, 37-45, 2015	83	2015
It Takes Two: Learning to plan for human-robot cooperative carrying E Ng, Z Liu, M Kennedy 2023 IEEE International Conference on Robotics and Automation (ICRA), 7526-7532, 2023	12	2023
Diffusion co-policy for synergistic human-robot collaborative tasks E Ng, Z Liu, M Kennedy IEEE Robotics and Automation Letters, 2023	5	2023
GPU accelerated prognostics GE Gorospe Jr, MJ Daigle, S Sankararaman, CS Kulkarni, E Ng Annual Conference of the PHM Society 9 (1), 2017	5	2017
Long-Horizon Prediction for Human-Robot Collaboration E Ng Stanford University, 2023		2023
Learning Action and State Sampling Distributions for Human-Robot Collaboration E Ng, Z Liu, M Kennedy III Workshop on Learning from Diverse, Offline Data (L-DOD) at RSS 2022, 2022		2022

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