Personal information

Singapore

Biography

I am a research scientist in the Energy Systems Group at A*STAR’s Institute of High Performance Computing, where I apply control, learning, and optimization algorithms to study smart grid operations. I also manage the Energy Systems group, and am the Principal Investigator (PI) for the “Modelling the Electrification of Singapore’s Harbourcrafts (MESH)” project, which is funded by the Singapore Maritime Institute and the Prime Minister’s Office’s Science and Technology Policy and Plans Office (S&TPPO).

I co-lectured an undergraduate Game Theory course as an adjunct in the Engineering Systems and Design Pillar at SUTD last summer with Prof. Lingjie Duan. Before starting at IHPC in 2020, I was a Data Scientist at Schlumberger’s Software Technology and Innovation Center at Menlo Park, CA, USA, where I was selected to present at SLB’s Reservoir Symposium and was later also awarded the Initiator Award at SLB’s FIZZ Symposium.

I received my Ph.D. from Caltech’s Computing and Mathematical Sciences Program in 2019, where I was supervised by Prof. Adam Wierman and Prof. Steven Low. At Caltech, I received the Amori Doctoral Prize in CMS for my dissertation on Online Platforms in Networked Markets. Prior to that, I obtained my Bachelor’s Degree in Mathematical Sciences (First Class Honors) from the Nanyang Technological University’s School of Physical and Mathematical Sciences in 2013 under the Accelerated Bachelor Program. My Ph.D. and B.Sc. studies were funded by Singapore’s National Science Scholarship and the A*STAR Undergraduate Scholarship.

My research lies at the intersection of optimization, control, and operations research – with a special focus on formulating and designing algorithms that are provably “not too bad” in both the offline and online optimization settings. My research is applied in the area of power and energy systems, networking, economics, and computer science.

Activities

Employment (1)

Institute of High Performance Computing: Singapore, SG

2020-11-02 to present | Group Manager / Research Scientist (Systems Science)
Employment
Source: Self-asserted source
John Zhen Fu Pang

Education and qualifications (2)

California Institute of Technology: Pasadena, CA, US

2014-09-15 to 2019-06-14 | PhD (Computing and Mathematical Sciences) (Computational and Mathematical Sciences)
Education
Source: Self-asserted source
John Zhen Fu Pang

Nanyang Technological University: Singapore, SG

2010-09-01 to 2013-12-02 | BSc (Mathematics) (School of Physical and Mathematical Sciences)
Education
Source: Self-asserted source
John Zhen Fu Pang

Professional activities (1)

California Institute of Technology: Pasadena, US

2019-06-14 | Amori Doctoral Prize (Computing and Mathematical Sciences )
Distinction
Source: Self-asserted source
John Zhen Fu Pang

Works (22)

Online Optimization in Power Systems with High Penetration of Renewable Generation: Advances and Prospects

Accepted to IEEE/CAA Journal of Automatica Sinica, currently available as arXiv preprint arXiv:2211.14569
2022 | Journal article
Contributors: Wang, Zhaojian; Wei, Wei; Pang, John Zhen Fu; Liu, Feng; Yang, Bo; Guan, Xinping; Mei, Shengwei
Source: Self-asserted source
John Zhen Fu Pang

Transparency and Control in Platforms for Networked Markets

Operations Research
2022 | Journal article
Contributors: Pang, John ZF; Lin, Weixuan; Fu, Hu; Kleeman, Jack; Bitar, Eilyan; Wierman, Adam
Source: Self-asserted source
John Zhen Fu Pang

Transparency and Control in Platforms for Networked Markets

Operations Research
2022-05 | Journal article
Contributors: John Pang; Weixuan Lin; Hu Fu; Jack Kleeman; Eilyan Bitar; Adam Wierman
Source: check_circle
Crossref

Online Station Assignment for Electric Vehicle Battery Swapping

IEEE Transactions on Intelligent Transportation Systems
2022-04 | Journal article
Contributors: Pengcheng You; John Z. F. Pang; Steven H. Low
Source: check_circle
Crossref

Pricing Electric Vehicle Charging Service with Demand Charge

21st Power Systems Computation Conference (PSCC)
2020 | Conference paper
Contributors: Lee, Zachary J; Pang, John ZF; Low, Steven H
Source: Self-asserted source
John Zhen Fu Pang

Competitive Online Optimization under Inventory Constraints

ACM Sigmetrics
2019 | Conference paper
Contributors: Lin, Qiulin; Yi, Hanling; Pang, John ZF; Chen, Minghua; Wierman, Adam; Honig, Michael; Xiao, Yuanzhang
Source: Self-asserted source
John Zhen Fu Pang

Distributed optimal frequency control considering a nonlinear network-preserving model

IEEE Transactions on Power Systems
2019 | Journal article
Contributors: Wang, Zhaojian; Liu, Feng; Pang, John ZF; Low, Steven H; Mei, Shengwei
Source: Self-asserted source
John Zhen Fu Pang

Deep Koopman Controller Synthesis for Cyber-Resilient Market-Based Frequency Regulation

IFAC-PapersOnLine
2018 | Journal article
Contributors: You, Pengcheng; Pang, John ZF; Yeung, Enoch
Source: Self-asserted source
John Zhen Fu Pang

Efficient Online Station Assignment for Electric Vehicle Battery Swapping

Proceedings of the ACM e-Energy Conference
2018 | Conference paper
Contributors: You, Pengcheng; Cheng, Peng; Pang, John ZF; Low, Steven H
Source: Self-asserted source
John Zhen Fu Pang

Joint Placement and Routing of Network Function Chains in Data Centers

IEEE INFOCOM 2018-IEEE Conference on Computer Communications
2018 | Conference paper
Contributors: Guo, Linqi; Pang, John ZF; Walid, Anwar
Source: Self-asserted source
John Zhen Fu Pang

Stabilization of Power Networks via Market Dynamics

Proceedings of the ACM e-Energy Conference
2018 | Conference paper
Contributors: You, Pengcheng; Pang, John ZF; Yeung, Enoch
Source: Self-asserted source
John Zhen Fu Pang

Temporally networked cournot platform markets

Proceedings of the 51st Hawaii International Conference on System Sciences
2018 | Conference paper
Contributors: Pang, John ZF; You, Pengcheng; Chen, Minghua
Source: Self-asserted source
John Zhen Fu Pang

Battery swapping assignment for electric vehicles: A bipartite matching approach

2017 IEEE 56th Annual Conference on Decision and Control (CDC)
2017 | Conference paper
Contributors: You, Pengcheng; Pang, John ZF; Chen, Minghua; Low, Steven H; Sun, Youxian
Source: Self-asserted source
John Zhen Fu Pang

Networked cournot competition in platform markets: Access control and efficiency loss

2017 IEEE 56th Annual Conference on Decision and Control (CDC)
2017 | Conference paper
Contributors: Lin, Weixuan; Pang, John ZF; Bitar, Eilyan; Wierman, Adam
Source: Self-asserted source
John Zhen Fu Pang

Optimal load control for frequency regulation under limited control coverage

IREP2017 Symposium
2017 | Conference paper
Contributors: Pang, John ZF; Guo, Linqi; Low, Steven H
Source: Self-asserted source
John Zhen Fu Pang

The efficiency of open access in platforms for networked cournot markets

IEEE INFOCOM 2017-IEEE Conference on Computer Communications
2017 | Conference paper
Contributors: Pang, John ZF; Fu, Hu; Lee, Won I; Wierman, Adam
Source: Self-asserted source
John Zhen Fu Pang

Cluster statistics and quasisoliton dynamics in microscopic optimal-velocity models

Physical Review E
2016 | Journal article
Contributors: Yang, Bo; Xu, Xihua; Pang, John ZF; Monterola, Christopher
Source: Self-asserted source
John Zhen Fu Pang

Dynamic service function chaining in sdn-enabled networks with middleboxes

2016 IEEE 24th International Conference on Network Protocols (ICNP)
2016 | Conference paper
Contributors: Guo, Linqi; Pang, John ZF; Walid, Anwar
Source: Self-asserted source
John Zhen Fu Pang

Asymmetric optimal-velocity car-following model

Physica A: Statistical Mechanics and its Applications
2015 | Journal article
Contributors: Xu, Xihua; Pang, John ZF; Monterola, Christopher
Source: Self-asserted source
John Zhen Fu Pang

Efficiency and robustness of different bus network designs

International Journal of Modern Physics C
2015 | Journal article
Contributors: Pang, John ZF; Bin Othman, Nasri; Ng, Keng Meng; Monterola, Christopher
Source: Self-asserted source
John Zhen Fu Pang

A parsimonious mixture of Gaussian trees model for oversampling in imbalanced and multimodal time-series classification

IEEE Transactions on Neural Networks and Learning Systems
2014 | Journal article
Contributors: Cao, Hong; Tan, Vincent YF; Pang, John ZF
Source: Self-asserted source
John Zhen Fu Pang

MOGT: oversampling with a parsimonious mixture of Gaussian trees model for imbalanced time-series classification

2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
2013 | Conference paper
Contributors: Pang, John ZF; Cao, Hong; Tan, Vincent YF
Source: Self-asserted source
John Zhen Fu Pang