Meng Cheng Lau

Dr. Meng Cheng Lau is an Assistant Professor at Laurentian University and the Director of the Laurentian Intelligent Mobile Robotics Lab (LIMRL), where he leads research in mobile and humanoid robotics, machine learning, and computer vision. With a Ph.D. in Computer Science from the University of Manitoba and prior experience as a Senior Lecturer in Malaysia, Dr. Lau has guided award-winning student teams in international robotics competitions such as FIRA RoboWorld Cup. His current projects span intelligent robot perception, reinforcement learning for control, and autonomous navigation using both wheeled and legged platforms. He has authored numerous peer-reviewed publications and introduced new interdisciplinary robotics courses at both undergraduate and graduate levels.

University of Manitoba, Canada — PhD (Computer Science)

National University of Malaysia (UKM), Malaysia — Master of Information Technology  (Full Research in Industrial Computing)

National University of Malaysia (UKM), Malaysia — Bachelor of Information Technology  (Industrial Computing with Honours)

Laurentian University, Canada — Assistant Professor

FIRA RoboWorld Cup (HuroCup) — Chair

University of Manitoba (UofM), Canada — Postdoctoral Fellow & Sessional Instructor 

National University of Malaysia (UKM), Malaysia  — Senior Lecturer/Head of Autonomous Robot and Vision Systems Laboratory (ARViS)

National University of Malaysia (UKM), Malaysia — Lecturer

Universiti Tunku Abdul Rahman (UTAR), Malaysia — Lecturer/Course Coordinator of Foundation Studies

My research focuses on AI-driven robotics, with an emphasis on machine learning, computer vision, and real-world robot applications. Current projects include developing a general-purpose humanoid robot using a Vision-Language-Action Model (VLAM), advancing visual SLAM for both legged-wheel and four-wheel robots, and applying computer vision to Cable-Driven Parallel Robots (CDPRs) in collaboration with School of Architecture’s faculty. I also co-lead a project on improving Battery Electric Vehicle efficiency through AI-driven energy modeling with support from CANMET and Laurentian’s Engineering faculty.

These projects are supported by multiple grants, including NSERC, IAMGOLD, and institutional (LU) funding. My research has led to peer-reviewed publications in PeerJ Computer Science, Electronics, Applied Intelligence, and presentations at major conferences like CDSR and ICARCE. Many of my graduate students have contributed to publications and completed applied thesis projects on topics such as human-robot interaction, deep learning for knitting robots, and multi-modal navigation.

In addition to research, I actively contribute to the academic community as a reviewer, program committee member, and executive for events like FIRA RoboWorld Cup and ICCAS. My interdisciplinary work bridges robotics, AI, and real-world implementation across both academic and industrial domains.

PI, Seed Funding for NSERC eligible research, Office of Research Services, Laurentian University

Supervisor, Nicolas Pottier. NSERC USRA Undergraduate Student Research Awards: AI-Driven Vison Module for Adaptive Humanoid Robots in Dynamic Environments

PI, New Faculty Start-up Grant.

IAMGOLD President’s Innovation Fund:

• Co-PI (Dr. Markus Timusk and Dr. Meng Cheng Lau).  AI-Driven Battery and Electric Vehicle Performance Estimation for Autonomous and Human-Operated Mining Equipment.
• Supervisor. LU Snobots Robotic Team. Enhancing Student Learning and Autonomous Robotics Innovation through Participation in the FIRA Roboworld Cup.
• Supervisor. Shauna Heron. Faculty of Arts: Psychology Emotionally Adaptive Robotics to Increase Trust in Human-Robot Collaboration.

Co-I, Adult-size Humanoid (UofM)

PI,  Auto Balancing for Humanoid Using Multisensory Model (UKM)

Co-I, Machine Learning in Decision Making With the Uncertainty With Applications to Jawi/Arabic Manuscripts, Biometric Authentication, Medical Image Database and Security and Digital Forensic Data (UKM)

Co-I, Industrial Informatics: Research Issues and The Path Forward (UKM)

Co-PI, Development of Intelligence Control Chart Software For Statistical Process Control (UKM)

FIRA Canada 2025, Markham (Coach): Adult & Kid Sized - 1st Place Allround

FIRA RoboWorld Cup 2024, Bazil (Coach): Adult Sized - 1st Place Allround

IROS Humanoid Application Challenge 2020 (Leader), Taiwan: 2nd Place

IEEE-IROS Humanoid Application Challenge 2019 (Leader), Macao: 2nd Place 

FIRA RoboWorld Cup 2019, Changwon (Leader): Adult&Kid Sized - 3rd Place Allround

IEEE-IROS Humanoid Application Challenge 2018 (Advisor), Madrid: 2nd Place 

Robocup 2018, Montreal (AMNUnited, Leader): Teensize Humanoid - 1st Place Technical Challenge 

AUTCup 2018, Tehran: Adult & Kid Sized - 1st Places Allround  

IEEE-IROS Humanoid Application Challenge 2017 (Advisor), Vancouver: 1st Place 

Postdoctoral Fellowship: Computer Science Dept. University of Manitoba, 2016-2020

Malaysian JPA and UKM Overseas Scholarship (PhD): 2009-2003

Master Research Scholarship: 2003-2005

Selected Journal and Chapter in Book

• Lau M, Anderson J, Baltes J. 2025. Integrating humanoid robots with human musicians for synchronized musical performances. PeerJ Computer Science 11:e2632 https://doi.org/10.7717/peerj-cs.2632
• Koczkodaj, W. W., Kułakowski, K., Lau, M. C., Pedrycz, W., Pigazzini, A., Song, Y. ... Żądło, T. (2025). Monte Carlo validation of the pairwise comparisons method accuracy improvement for 3D objects. Advances in Science and Technology Research Journal, 19(6), 194-202. https://doi.org/10.12913/22998624/202891
• Sheng, H., Cai, S., Zheng, X., & Lau, M. (2025). Knitting Robots: A Deep Learning Approach for Reverse-Engineering Fabric Patterns. Electronics, 14(8), 1605. https://doi.org/10.3390/electronics14081605
• Sheng, Haoliang and Lau, Meng-Cheng (2024). Optimising Real-Time Facial Expression Recognition with ResNet Architectures. Journal of Machine Intelligence and Data Science (JMIDS) 5 (1), 33-45. DOI: https://jmids.avestia.com/2024/005.html
• Zhang, Jing and Lau, Meng-Cheng and Zhu, Ziping (2024). Hybrid CNN-GRU Model for Exercise Classification Using IMU Time-Series Data. Journal of Machine Intelligence and Data Science (JMIDS) 5 (1), 54-64. DOI: https://jmids.avestia.com/2024/007.html
• Hosseinmemar, A., Baltes, J., Anderson, J., Lau, M. C., Lun, C. F., & Wang, Z. (2019). Closed-loop push recovery for inexpensive humanoid robots. Applied Intelligence (Dordrecht, Netherlands), 49(11), 3801–3814. https://doi.org/10.1007/s10489-019-01446-z
• Lau, M.-C., Anderson, J., & Baltes, J. (2019). A sketch drawing humanoid robot using image-based visual servoing. Knowledge Engineering Review, 34. https://doi.org/10.1017/S0269888919000146
• Dewi, D. A., Sundararajan, E., Prabuwono, A. S., & Cheng, L. M. (2019). Object Detection without Color Feature: Case Study Autonomous Robot. International Journal of Mechanical Engineering and Robotics Research, 646–650. https://doi.org/10.18178/ijmerr.8.4.646-650
• Wong, C.-C., Liu, C.-C., Xiao, S.-R., Yang, H.-Y., & Lau, M.-C. (2019). Q-Learning of Straightforward Gait Pattern for Humanoid Robot Based on Automatic Training Platform. Electronics (Basel), 8(6), 615-. https://doi.org/10.3390/electronics8060615
• Morris, K. J., Samonin, V., Baltes, J., Anderson, J., & Lau, M. C. (2019). A robust interactive entertainment robot for robot magic performances. Applied Intelligence (Dordrecht, Netherlands), 49(11), 3834–3844. https://doi.org/10.1007/s10489-019-01565-7

Selected Chapter in Book

• Lau, M. C., Anderson, J., Baltes, J., Gallegos, C. M., Diaz, M. M., Li, B., Chen, W., Nguyen, A., Yap, E.-H., Liu, P., Huang, X., Abdul Majeed, A. P. P., & Kim, U.-H. (2024). Collaborative Music Performances with Humanoid Robots and Humans. In Robot Intelligence Technology and Applications 8 (Vol. 1132, pp. 165–175). Springer. https://doi.org/10.1007/978-3-031-70684-4_14
• Hosseinmemar, A., Anderson, J., Baltes, J., Lau, M. C., Wang, Z., Fujita, H., Fournier-Viger, P., Ali, M., & Sasaki, J. (2020). Push Recovery and Active Balancing for Inexpensive Humanoid Robots Using RL and DRL. In Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices (Vol. 12144, pp. 63–74). Springer International Publishing AG. https://doi.org/10.1007/978-3-030-55789-8_6
• Hosseinmemar, A., Baltes, J., Anderson, J., Lau, M. C., Lun, C. F., Wang, Z., Mouhoub, M., Sadaoui, S., Ali, M., & Ait Mohamed, O. (2018). Closed-Loop Push Recovery for an Inexpensive Humanoid Robot. In Recent Trends and Future Technology in Applied Intelligence (Vol. 10868, pp. 233–244). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-92058-0_22
• Morris, K. J., Samonin, V., Anderson, J., Lau, M. C., Baltes, J., Mouhoub, M., Sadaoui, S., Ali, M., & Ait Mohamed, O. (2018). Robot Magic: A Robust Interactive Humanoid Entertainment Robot. In Recent Trends and Future Technology in Applied Intelligence (Vol. 10868, pp. 245–256). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-92058-0_23
• Lau, M. C., Cheng, C.-T., Baltes, J., Anderson, J., Jo, J., Sincak, P., Kim, J.-H., Yang, W., & Myung, H. (2015). Drawing Pressure Estimation Using Torque Feedback Control Model of A 4-DOF Robotic Arm. Robot Intelligence Technology and Applications 3, 401–410. https://doi.org/10.1007/978-3-319-16841-8_37

Selected Proceeding

• X. Zheng, H. Sheng, S. Cai, M. Cheng Lau and K. Zhao, "Automated Knitting Instruction Generation from Fabric Images Using Deep Learning," 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE), China, 2024, pp. 197-201, doi: 10.1109/ICARCE63054.2024.00044.
• W. Luo and M. Lau, "A Dynamic Control System for Robotic Goalkeeping Using YOLOv9 and Path Planning," 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE), China, 2024, pp. 45-49, doi: 10.1109/ICARCE63054.2024.00016.
• G. Gong and M. Lau, "Implementation of Rao-Blackwellized Particle Filter on LIMO ROS2," 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE), China, 2024, pp. 30-35, doi: 10.1109/ICARCE63054.2024.00013.
• J. Zhang and M. Lau, "Human-Robot Interaction: A ROS2-Based Approach with Voice and Vision Integration," 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE), China, 2024, pp. 21-25, doi: 10.1109/ICARCE63054.2024.00011.
• Haoliang Sheng, MengCheng Lau. (2024). Optimising Facial Expression Recognition: Comparing ResNet Architectures for Enhanced Performance. 11th International Conference of Control, Dynamic Systems, and Robotics (CDSR 2024), Totonto, Canada
• Zhang, Jing; Meng Cheng, Lau; ZiPing, Zhu. (2024). Advanced Exercise Classification with a Hybrid CNNGRU Model: Utilising IMU Data from Cell Phones. 11th International Conference of Control, Dynamic Systems, and Robotics (CDSR 2024), Totonto, Canada
• Meng Cheng Lau, John Anderson, Jacky Baltes, Christian Melendez Gallegos, Mario Mendez Diaz, and Borui Li. (2024). Collaborative Music Performances with Humanoid Robots and Humans. 11th International Conference on Robot Intelligence Technology and Applications, Xi'an, China.
• Hosseinmemar, Amirhossein and Anderson, John and Baltes, Jacky and Lau, Meng Cheng and Wang, Ziang. (2020). Push Recovery and Active Balancing for Inexpensive Humanoid Robots Using RL and DRL. 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Kitakyushu, Japan.
• Hosseinmemar, Amirhossein and Baltes, Jacky and Anderson, John and Lau, Meng Cheng and Lun, ChiFung and Wang, Ziang. (2019). Closed-loop push recovery for inexpensive humanoid robots. Applied Intelligence. International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Montreal, Canada.
• Kyle John Morris, John Anderson, Meng Cheng Lau, Jacky Baltes. (2018). Interaction and Learning in a Humanoid Robot Magic Performance. AAAI Spring Symposium, Palo Alto, USA.
• Lau, M. C., Cheng, C.-T., Baltes, J., Anderson, J., Jo, J., Sincak, P., Kim, J.-H., Yang, W., & Myung, H. (2015). Drawing Pressure Estimation Using Torque Feedback Control Model of A 4-DOF Robotic Arm. Robot Intelligence Technology and Applications 3, 401–410. https://doi.org/10.1007/978-3-319-16841-8_37.
• Lau, M. C., Baltes, J., Mamun, A. A., Anderson, J., Ahlgren, D., Vadakkepat, P., Kim, J.-H., Kiong, T. K., Jesse, N., & Verner, I. (2010). The Real-Time Embedded System for a Humanoid: Betty. Trends in Intelligent Robotics, 122–129. https://doi.org/10.1007/978-3-642-15810-0_16

Complete Publication (Google Scholar Profile): 

https://scholar.google.ca/citations?user=jxcJG0gAAAAJ&hl=en&authuser=1