cacheng at gatech dot edu    
cv      Google scholar    

I am a Robotics PhD candidate advised by Byron Boots at Institute for Robotics and Intelligent Machines, Georgia Tech. I am a practical theoretician, interested in developing theoretical foundations
for designing efficient and principled algorithms that can tackle real-world challenges. My research is built on machine learning, optimization, and control theories. My current focus concerns learning efficiency, structural properties, and uncertainties in sequential decision making. Specific topics include reinforcement learning, imitation learning, online learning, meta learning, (large-scale) Gaussian processes, and integrated motion planning and control. I interned at Nvidia Research, Seattle, in Summer 2018, working with Nathan Ratliff and Dieter Fox; and aMicrosoft Research AI, Redmond, in Summer 2019, working with Alekh Agarwal and Andrey Kolobov

I was awarded with NVIDIA Graduate FellowshipGoogle PhD Fellowship (declined), Best Student Paper & Finalist to Best Systems Paper (RSS 2019), Best Paper (AISTATS 2018), and Finalist to Best Systems Paper (RSS 2018).
 
Before Georgia Tech, I received from National Taiwan University (NTU) double degrees of B.S. in Mechanical Engineering and B.S. in Electrical Engineering in 2011, and my M.S. in Mechanical Engineering in 2013During that period, I was advised by Han-Pang Huang, who directs NTU Robotics Laboratory. My previous research includes learning dynamical systems, force/impedance control, kernel methods, and approximation theory---with applications ranging from manipulator, grasping, exoskeleton, brain-computer interface, to humanoid.




     Preprints
Authors Title Year arXiv Number
C.-A. Cheng, R. Tachet des Combes, B. Boots, & G. Gordon A Reduction from Reinforcement Learning to No-Regret Online Learning [pdf] 2019 arXiv:1911.05873
C.-A. Cheng*, J. Lee*, K. Goldberg, & B. Boots Online Learning with Continuous Variations: Dynamic Regret and Reductions (*equal contribution) [pdf] 2019 arXiv:1902.07286
    Journal/Conference Publications
Authors Title Year Journal/Proceeding
C.-A. Cheng*, X. Yan*, & B. Boots Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods (*equal contribution) [pdf] 2019 Conference on Robot Learning
M. Mukadam, C.-A. Cheng, D. Fox, B. Boots, & N. Ratliff Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping [pdf] 2019 Conference on Robot Learning
Y. Pan, C.-A. Cheng, K. Saigol, K. Lee, X. Yan, E. Theodorou, & B. Boots. Imitation Learning for Agile Autonomous Driving [pdf] 2019 The International Journal of Robotics Research 
A. Li, C.-A. Cheng, B. Boots, & M. Egerstedt Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks [pdf] 2019 IEEE Conference on Decision and Control
Z.-H. Kang, C.-A. Cheng, H.-P. Huang A Singularity Handling Algorithm based on Operational Space Control for Six-degree-of-freedom Anthropomorphic Manipulators [pdf] 2019 International Journal of Advanced Robotic Systems
N. Wagener*, C.-A. Cheng*, J. Sacks, & B. Boots An Online Learning Approach to Model Predictive Control (*equal contribution) [pdf]
Best Student Paper Award
Finalist to the Best Systems Paper Award
2019 Robotics: Science and Systems
C.-A. Cheng, X. Yan, N. Ratliff, & B. Boots Predictor-Corrector Policy Optimization [pdf]
Selected for Long Talk (5%)
2019 International Conference on Machine Learning
C.-A. Cheng, X. Yan, E. Theodorou, & B. Boots Accelerating Imitation Learning with Predictive Models [pdf] 2019 International Conference on Artificial Intelligence and Statistics
A. Shaban*, C.-A. Cheng*, N. Hatch, & B. Boots Truncated Back-propagation for Bilevel Optimization (*equal contribution) [pdf] 2019 International Conference on Artificial Intelligence and Statistics
C.-A. Cheng, M. Mukadam, J. Issac, S. Birchfield, D. Fox, B. Boots, & N. Ratliff RMPflow: A Computational Graph for Automatic Motion Policy Generation [pdf]
2018 The 13th International Workshop on the Algorithmic Foundations of Robotics
H. Salimbeni*, C.-A. Cheng*, B. Boots, & M. Deisenroth Orthogonally Decoupled Variational Gaussian Processes (*equal contribution) [pdf]
2018 Conference on Neural Information Processing Systems
C.-A. Cheng, X. Yan, N. Wagener, & B. Boots Fast Policy Learning Using Imitation and Reinforcement [pdf]
Selected for Plenary Presentation (8%)
2018 Conference on Uncertainty in Artificial Intelligence
Y. Pan, C.-A. Cheng, K. Saigol, K. Lee, X. Yan, E. Theodorou, & B. Boots Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning [pdf]
Finalist to the Best Systems Paper Award
2018 Robotics: Science and Systems
C.-A. Cheng, & B. Boots Convergence of Value Aggregation for Imitation Learning [pdf]
Best Paper Award
2018 International Conference on Artificial Intelligence and Statistics
J. Molnar, C.-A. Cheng, L. Tiziani, B. Boots, & F. Hammond Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators [pdf] 2018 IEEE International Conference on Robotics and Automation
C.-A. Cheng, & B. Boots
Variational Inference for Gaussian Process Models with Linear Complexity [pdf] 2017 Advances in Neural Information Processing Systems
M. Mukadam, C.-A. Cheng, X. Yan, & B. Boots Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference [pdf] 2017 IEEE International Conference on Robotics and Automation
C.-A. Cheng, & B. Boots Incremental Variational Sparse Gaussian Process Regression [pdf] 2016 Advances in Neural Information Processing Systems
C.-A. Cheng, & H.-P. Huang Learn the Lagrangian: a Vector-Valued RKHS Approach to Identifying Lagrangian Systems [pdf] 2016 IEEE Transactions on Cybernetics
S.-Y. Lo, C.-A. Cheng, & H.-P. Huang Virtual Impedance Control for Safe Human-Robot Interaction [pdf] 2016 Journal of Intelligent and Robotic Systems
C.-A. Cheng, H.-P. Huang, H.-K. Hsu, W.-Z. Lai, & C.-C. Cheng Learning the Inverse Dynamics of Robotic Manipulators in Structured Reproducing Kernel Hilbert Space [pdf] 2016 IEEE Transactions on Cybernetics
C.-H. Chang, H.-P. Huang, H.-K. Hsu, & C.-A. Cheng  Humanoid Robot Push-Recovery Strategy Based on CMP Criterion and Angular Momentum Regulation [pdf] 2015 IEEE/ASME International Conference on Advanced Intelligent Machatronics 
M.-B. Huang, H.-P. Huang, C.-C. Cheng, & C.-A. Cheng Efficient Grasp Synthesis and Control Strategy for Robot Hand-Arm System [pdf] 2015 IEEE International Conference on Automation Science and Engineering
H.-P. Huang, Y.-H. Liu, W.-Z. Lin, Z.-H. Kang, C.-A. Cheng, & T.-H. Huang Development of a P300 Brain-Machine Interface and Design of an Elastic Mechanism for a Rehabilitation Robot [pdf] 2015 International Journal of Automation and Smart Technology
C.-A. Cheng, H.-P. Huang, H.-K. Hsu, W.-Z. Lai, & C.-C. Cheng Identifying the Inverse Dynamics of the Robot Manipulators with Structured Kernel [pdf] 2013 International Automatic Control Conference
T.-H. Huang, C.-A. Cheng, & H.-P. Huang Self-Learning Assistive Exoskeleton with Sliding Mode Admittance Control [pdf] 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
C.-A. Cheng, T.-H. Huang, & H.-P. Huang Bayesian Human Intention Estimator for Exoskeleton System [pdf] 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
T.-H. Huang, H.-P. Huang, C.-A. Cheng, J.-Y. Kuan, P.-T. Lee, & S.-Y. Huang Design of a New Hybrid Control and Knee Orthosis for Human Walking and Rehabilitation [pdf] 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
H.-P. Huang, Y.-H. Liu, T.-H. Huang, Z.-H. Kang, W.-Z. Lin, C.-P. Wang, & C.-A. Cheng  Development of a Brain-Machine Interface for Motor Imagination Task [pdf] 2012 International Conference on Automation Technology
Y.-H. Liu, C.-A. Cheng, & H.-P. Huang Novel Feature of the EEG Based Motor Imagery BCI Systems: Degree of Imagery [pdf] 2011 International Conference on System Science and Engineering
C.-A. Cheng, Y.-H. Liu, & H.-P. Huang Motor Imagery Recognition for Brain-Computer Interfaces using Hilbert-Huang Transform and Effective Event-Related-Desynchronization Features [pdf] 2010 CSME National Conference
    Workshop Papers
Authors Title Year Venue
J. Lee*, C.-A. Cheng*, K. Goldberg, & B. Boots Continuous Online Learning and New Insights to Online Imitation Learning [pdf] (*equal contribution)
Selected for Oral Presentation (4%)
2019 NeurIPS 2019 Optimization Foundations of Reinforcement Learning Workshop
X. Yan*, C.-A. Cheng*, & B. Boots Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods (*equal contribution) [pdf]2019 NeurIPS 2019 Optimization Foundations of Reinforcement Learning Workshop
C.-A. Cheng, X. Yan, N. Ratliff, & B. Boots Predictor-Corrector Policy Optimization [pdf] 2018 Deep Reinforcement Learning Workshop NeurIPS 2018
Y. Pan, C.-A. Cheng, K. Saigol, K. Lee, X. Yan, E. Theodorou, & B. Boots Learning Deep Neural Network Control Policies for Agile Off-Road Autonomous Driving [pdf] 2017 The NIPS Deep Reinforcement Learning Symposium
C.-A. Cheng, & B. Boots Convergence of Value Aggregation for Imitation Learning [pdf] 2017 The NIPS Deep Reinforcement Learning Symposium
C.-A. Cheng, & B. Boots Incremental Variational Sparse Gaussian Process Regression. [pdf] 2016 NIPS Workshop on Adaptive and Scalable Nonparametric Methods in Machine Learning
    Thesis
Authors Title Year Degree & Institute
C.-A. Cheng 
                                                                  
Robot Dynamics Learning and Human-Robot Interaction [pdf] 2013 Master Thesis
National Taiwan University