LOW Kian Hsiang

Assistant Professor
Ph.D. (Electrical & Computer Engineering, Carnegie Mellon University, 2009)
B.Sc. (Computer Science, National University of Singapore, 2001)
M.Sc. (Computer Science, National University of Singapore, 2002)
COM2-02-58
651 64719

http://www.comp.nus.edu.sg/~lowkh

Research Areas

  • Artificial Intelligence

Research Interests

  • Probabilistic Machine Learning (e.g., Bayesian deep learning, Bayesian non-parametric models)
  • Data-Efficient Machine Learning (e.g., Bayesian optimization, active learning, and adaptive sampling)
  • Multi-Party Machine Learning (e.g., federated/distributed learning, decentralized data fusion, privacy-preserving machine learning)
  • Reinforcement Learning
  • Planning Under Uncertainty
  • Multi-Agent/Robot Systems
  • Computational Sustainability

Profile

Dr. Bryan Low is an Assistant Professor at the Department of Computer Science of the National University of Singapore. He obtained the B.Sc. (Hons.) and M.Sc. degrees in Computer Science from National University of Singapore, Singapore, in 2001 and 2002, respectively, and the Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, Pennsylvania, in 2009. His research interests include probabilistic machine learning (Bayesian deep learning, Bayesian non-parametric models (e.g., Gaussian processes), automatic machine learning (e.g., Bayesian optimization), privacy-preserving machine learning, active learning, parallel/distributed machine learning and online learning for big data), planning under uncertainty, reinforcement learning, and multi-agent/robot systems (multi-agent/robot coordination, planning, and learning). Dr. Low is the recipient of (1) Andrew P. Sage Best Transactions Paper Award for the best paper published in all 3 of the IEEE Transactions on Systems, Man, and Cybernetics - Parts A, B, and C in 2006; (2) National University of Singapore Overseas Graduate Scholarship for Ph.D. studies in Carnegie Mellon University (CMU) in 2004-2009; and (3) Singapore Computer Society Prize for Best M.Sc. Thesis in School of Computing, National University of Singapore in 2003. He has also served as a World Economic Forum’s Global Future Councils Fellow for the Council on the Future of Artificial Intelligence and Robotics from Sep 2016 to Jun 2018 and an organizing chair for the IEEE RAS Summer School on Multi-Robot Systems in Jun 2016.

Current Projects

  • Bayesian deep learning, data-efficient machine learning (Bayesian optimization, active learning), privacy-preserving machine learning, probabilistic machine learning, Bayesian non-parametric models, Gaussian processes, planning under uncertainty, reinforcement learning, multi-agent/robot systems, data fusion, computational sustainability.

Selected Publications

  • Trong Nghia Hoang, Quang Minh Hoang, Ruofei Ouyang, and Kian Hsiang Low (2018). Decentralized High-Dimensional Bayesian Optimization with Factor Graphs. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), [24.55% Acceptance Rate].

  • Erik Daxberger and Kian Hsiang Low (2017). Distributed Batch Gaussian Process Optimization. In Proceedings of the 34th International Conference on Machine Learning (ICML-17), pp. 951-960 [25.5% Acceptance Rate].

  • Trong Nghia Hoang, Quang Minh Hoang, and Kian Hsiang Low (2016). A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models. In Proceedings of the 33rd International Conference on Machine Learning (ICML-16), pp. 382-391 [24.3% Acceptance Rate].

  • Chun Kai Ling, Kian Hsiang Low, and Patrick Jaillet (2016). Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 1860-1866 [25.75% Acceptance Rate].

  • Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, and Mohan Kankanhalli (2016). Near-Optimal Active Learning of Multi-Output Gaussian Processes. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 2351-2357 [25.75% Acceptance Rate].

  • Jie Chen, Kian Hsiang Low, Patrick Jaillet, and Yujian Yao (2015). Gaussian Process Decentralized Data Fusion and Active Sensing for Spatiotemporal Traffic Modeling and Prediction in Mobility-on-Demand Systems. In IEEE Transactions on Automation Science and Engineering (Special Issue on Networked Cooperative Autonomous Systems), volume 12, issue 3, pp. 901-921.

  • Trong Nghia Hoang, Quang Minh Hoang, and Kian Hsiang Low (2015). A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data. In Proceedings of the 32nd International Conference on Machine Learning (ICML-15), pp. 569-578 [26.0% Acceptance Rate].

  • Quoc Phong Nguyen, Kian Hsiang Low, and Patrick Jaillet (2015). Inverse Reinforcement Learning with Locally Consistent Reward Functions. In Proceedings of the 29th Annual Conference on Neural Information Processing Systems (NIPS-15) [21.9% Acceptance Rate].

  • Trong Nghia Hoang, Kian Hsiang Low, Patrick Jaillet, and Mohan Kankanhalli (2014). Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes. In Proceedings of the 31st International Conference on Machine Learning (ICML-14), pp. 739-747 [25.0% Acceptance Rate].

  • Nuo Xu, Kian Hsiang Low, Jie Chen, Keng Kiat Lim, and Etkin B. Ozgul (2014). GP-Localize: Persistent Mobile Robot Localization using Online Sparse Gaussian Process Observation Model. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pp. 2585-2592 [28.3% Acceptance Rate].

  • Jie Chen, Kian Hsiang Low, and Colin Keng-Yan Tan (2013). Gaussian Process-Based Decentralized Data Fusion and Active Sensing for Mobility-on-Demand System. In Proceedings of the Robotics: Science and Systems Conference (RSS-13) [30.1% Acceptance Rate].

  • Nannan Cao, Kian Hsiang Low, and John M. Dolan (2013). Multi-Robot Informative Path Planning for Active Sensing of Environmental Phenomena: A Tale of Two Algorithms. In Proceedings of the 12th Inter- national Conference on Autonomous Agents and Multiagent Systems (AAMAS-13), pp. 7-14 [22.9% Acceptance Rate].

  • Prabhu Natarajan, Trong Nghia Hoang, Kian Hsiang Low, and Mohan Kankanhalli (2012). Decision-Theoretic Approach to Maximizing Observation of Multiple Targets in Multi-Camera Surveillance. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-12), pp. 155-162 [20.4% Acceptance Rate].

  • Kian Hsiang Low, John M. Dolan, and Pradeep K. Khosla (2009). Information-Theoretic Approach to Efficient Adaptive Path Planning for Mobile Robotic Environmental Sensing. In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS-09), pp. 233-240 [33.9% Acceptance Rate].

  • Kian Hsiang Low, John M. Dolan, and Pradeep K. Khosla (2008). Adaptive Multi-Robot Wide-Area Ex- ploration And Mapping. In Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-08), pp. 23-30 [22.2% Acceptance Rate].

  • Kian Hsiang Low, Wee Kheng Leow, and Marcelo H. Ang, Jr. (2006). Autonomic Mobile Sensor Network with Self-Coordinated Task Allocation and Execution. In IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews (Special Issue on Engineering Autonomic Systems), volume 36, issue 3, pp. 315-327.

  • Kian Hsiang Low, Wee Kheng Leow, and Marcelo H. Ang, Jr. (2005). An Ensemble of Cooperative Extended Kohonen Maps for Complex Robot Motion Tasks. In Neural Computation, volume 17, issue 6, pp. 1411-1445.

Awards & Honours

  • Invited to serve as a World Economic Forum’s Global Future Councils Fellow for the Council on the Future of Artificial Intelligence and Robotics, Sep 2016 – Jun 2018
  • Best PhD Forum Paper Award in 6th ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC’12) won by my PhD student, Prabhu Natarajan, Nov 2012
  • Featured in Association for Unmanned Vehicle Systems International (AUVSI) Unmanned Systems Magazine "Ones to Watch" June 2010 issue
  • Andrew P. Sage Best Transactions Paper Award for the best paper (first author) published in all 3 of the IEEE Transactions on Systems, Man, and Cybernetics - Parts A, B, and C in 2006
  • NUS Overseas Graduate Scholarship for Ph.D. studies in Carnegie Mellon University, 2004-2009
  • Winner of Singapore Computer Society Prize for Best M.Sc. Thesis (among 81 graduates of M.Sc. by research) in SOC, NUS, 2002-2003

Teaching (2019/2020)

  • CS3244: Machine Learning