Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
Details, Liu, L., and P. Fieguth, "Texture classification using compressed sensing", 7th Canadian Conference on Computer and Robot Vision, pp. Canada Research Chair and Assistant Professor. Nov 2011: we are part of the Canada/UK team for antibiotic resistance research Aug 2011: Dr. Liu was awarded Early Researcher Award May 2011: Web article: Nanotechnology thought … His main research interests are in the theory and applications of hybrid systems and control, including rigorous computational methods for control design with applications in robotics and cyber-physical systems.
Finally, real vehicle testing is implemented and relevant experiment data is collected and calibrated. 5. Then, two classical reinforcement learning (RL) algorithms, Q-learning and Dyna, are leveraged to derive the DM strategies in a predefined driving scenario. 6. Associate Professor (2018-present)Assistant Professor (2015-2018)Department of Applied Mathematics As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. Deep reinforcement learning Canada Research Chair and Associate Professor, Department of Automatic Control and Systems Engineering, Department of Computing and Mathematical Sciences, Journal of Nonlinear Systems and Applications, ACM International Conference on Hybrid Systems: Computation and Control, IFAC Conference on Analysis and Design of Hybrid Systems, IEEE CSS Technical Committee on Computational Aspects of Control System Design, IEEE CSS Technical Committee on Hybrid Systems, Canadian Applied and Industrial Mathematics Society, Institute of Electrical and Electronics Engineers, Society for Industrial and Applied Mathematics, Ontario MRIS Early Researcher Award (2018-2023), IFAC Journal Nonlinear Analysis: Hybrid Systems Paper Prize (2017), EU Marie Curie Career Integration Grant (2013-2017), Royal Society International Exchange Grant (2014-2015), NSERC Postdoctoral Fellowship (2011-2012). Facing the problem of the “curse of dimensionality” in the reinforcement learning method, a novel deep reinforcement learning algorithm deep Q-learning (DQL) is designed for energy management control, which uses a new optimization method (AMSGrad) to update the weights of the neural network. October 2013, we were awarded NSERC Strategic Project Grant in collaboration with Taiwan September 23, 2013, we moved to the new QNC labs. I am now most interested in the techonology of using sparse representation algorithm to do image denoising, super-resolution, and medical image reconsruction, etc. Prior to joining the University of Waterloo, he was a Lecturer in Control and Systems Engineering at the University of Sheffield and a Postdoctoral Scholar in Control and Dynamical Systems at the California Institute of Technology. Results show that the proposed deep reinforcement learning method realizes faster training speed and lower fuel consumption than traditional DQL policy does, and its fuel economy quite approximates to global optimum. 200 University Ave. West, Waterloo, Ontario, Canada N2L3G1.
Nine students have published 11 first-authored papers already! Protection and Promotion of UV Radiation-Induced Liposome Leakage via DNA-Directed Assembly with Gold Nanoparticles.
30, no. j.liu@uwaterloo.ca.
He is a Canada Research Chair in Hybrid Systems and Control and an Associate Professor in Applied Mathematics at the University of Waterloo, where he directs the Hybrid Systems Laboratory. Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River. successful graduate schools. This research proposes a reinforcement learning-based algorithm and a deep reinforcement learning-based algorithm for energy management of a series hybrid electric tracked vehicle. degree in Remote Sensing and Geographic Information Systems in 2005 from the National University of Defense Technology, Changsha, China, where she is currently pursuing a Ph.D. University of Waterloo Coronavirus Information website, See list of Faculty of Engineering Modified Services. The student’s salary will amount to $1,625-$1,725/month depending on the student’s seniority. 2, pp. Chem. Details, Liu, L., P. Fieguth, M. Pietikäinen, and S. Lao, "Median Robust Extended Local Binary Pattern for Texture Classification", IEEE International Conference on Image Processing, Accepted. Department: Department of Mechanical and Mechatronics Engineering. In the past three years, Nanotechnology Engineering co-op students have been very successful in my lab. degree in Applied Mathematics from Shanghai Jiao-Tong University, the M.S. September 2015 (front row: Juewen Liu, Wenhu Zhou, Runjhun Saran, Chang Lu, Lingzi Ma; Back row: Feng Wang, Anand Lopez, Biwu Liu, Jimmy Huang, Zijie Zhang, Zhicheng Huang, James Yu), August 2013: Mahsa, Feng, Sylwia, Imran, Biwu, Jimmy, Alex, Juewen, Shine, Elsa & Jenny, August 2012, Nathan, Biwu, Kiyoshi, Juewen, Alex, Neeshma, Puja, Shine, Imran (not in picture: Jimmy), August 2011 Juewen, Zach, Youssof, Ahmed, Neeshma, Shine, and Jimmy, For future postdoctoral fellows: if you have a very strong background, please consider the Banting Fellowship with $70,000 annual salary. This document is designed to outline laboratory safety in general and specific to the Liu Lab, and to make you aware of hazards and hazardous materials you may encounter during your time in the lab. Details
Our main campus is situated on the Haldimand Tract, the land promised to the Six Nations that includes six miles on each side of the Grand River.
Jun Liu received the B.S.
degree in Mathematics from Peking University, and the Ph.D. degree in Applied Mathematics from the University of Waterloo. Numerous journals and conferences, some book publishers, and several funding agencies. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time. 482 - 496, 2015. The high-level establishes a parallel system first, which includes a real powertrain system and an artificial system. Institution: University of Waterloo. Subsequently, a new variant of reinforcement learning (RL) method Dyna, namely Dyna-H, is developed by combining the heuristic planning step with the Dyna agent and is applied to energy management control for SHETV.
General Laboratory Safety at Liu Lab at UW (must read and follow) Version 1.0 (Juewen Liu, October 5, 2013) You are required to read and follow this document before you can work in the Liu Lab. from Chinese Academy of … Adv. PRL is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined rules. www.itsslab.com. First, the highway driving environment is built, wherein the ego vehicle, surrounding vehicles, and road lanes are included. 86-99, 2012. This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). This paper focuses on discussing the decision-making (DM) strategy for autonomous vehicles in a connected environment.
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