Projects per year
Personal profile
Biography
Terrence W.K. Mak is currently a Lecturer in the Department of Data Science & AI of the Faculty of IT. He is located in the Optimisation disciple group under Prof. Peter Stuckey. He is an active member of the Monash Energy Institute and the Monash Data Futures Institute. He has recently started working on projects under the theme of Sustainable Informatics.
Academic history: He has obtained a PhD (2018) from the Australian National University, a MPhil (2011) & a BSc (2009) from the Chinese University of Hong Kong. He was a Postdoc Fellow in Georgia Tech and a Research Associate in University of Michigan. He has worked with his fomer PhD & Postdoc supervisor Prof. Pascal Van Hentenryck for over 10 years through University of Melbourne, Australian National University, University of Michigan, and Georgia Tech, and over 5 years with his former Master & Bachelor supervisor Prof. Jimmy Lee in Chinese University of Hong Kong. He has experience over multiple research domains and has publications spanning over computer science (AI/ML/differential privacy), electrical engineering (power/natural gas/control), and operations research (MILP/NLP).
Research interests
He is an interdisciplinary researcher and his research domain lies on the intersections of three traditional academic research areas ---
- mathematical & combinatorial optimization,
- machine learning, and
- energy systems (including electric power transmission systems and natural gas pipeline systems).
His primary focus is to seek for novel methodologies combining both machine learning and optimization to solve grand climate change challenges in the energy sector to prepare for the future era. He is particularly interested tackling problems on:
- energy sustainability,
- net-zero emissions,
- climate-change resiliency, and
- disaster management.
External engagement records:
- Government: ARPA-E, U.S. Department of Energy.
ARPA-E Grid Optimization Competition [2019 - 2023], ARPA-E PERFORM project (Grid Research for Good) [2017 - 2018], ARPA-E PERFORM project (Risk-Aware Market Clearing) [2020 - 2023]
- National laboratories: Los Alamos National Lab; National Renewable Energy Lab; Pacific Northwest National Lab.
Project collaborators for ARPA-E projects.
- Industry: RTE France - French transmission operator; Midcontinent Independent System Operator - U.S. ISO/RTO covering 15 U.S. states; Origin Energy - Australia energy generation and retail company
- NGO: Kids Tech Tech
Partner for the Seth Bonder Summer Camp
Supervision interests
Looking for motivated students interested to work on intersections between Deep Learning (DNNs) and Nonlinear Optimization for the futuristic Smart Grid.
Community service
- International Joint Conferences on Artificial Intelligence (IJCAI) 2021 - 2022, Senior/Program Committee
- International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023, Program Committee
- AAAI Workshop: Privacy-Preserving Artificial Intelligence (PPAI) 2021 - 2022, Workshop Committee
- European Conference on Artificial Intelligence (ECAI) 2023, Meta Reviewer/Senior Program Committee
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Computer Science, PhD, Australian National University (ANU)
Award Date: 13 Jul 2018
Research area keywords
- Optimisation
- Machine Learning
- Power Systems
- Smart Grid
Collaborations and top research areas from the last five years
Projects
- 2 Finished
-
Collaboration with RedGrid’: Collaboration to enhance RedGrid’s a software modelling and planning algorithms
Wagner, M. (Primary Chief Investigator (PCI)), Liebman, A. (Chief Investigator (CI)), Wang, H. (Chief Investigator (CI)) & Mak, T. (Chief Investigator (CI))
1/11/23 → 30/09/24
Project: Research
-
-
Bucketized Active Sampling for learning ACOPF
Klamkin, M., Tanneau, M., Mak, T. W. K. & Van Hentenryck, P., Oct 2024, In: Electric Power Systems Research. 235, 8 p., 110697.Research output: Contribution to journal › Article › Research › peer-review
1 Citation (Scopus) -
Compact optimization learning for AC Optimal Power Flow
Park, S., Chen, W., Mak, T. W. K. & Van Hentenryck, P., Mar 2024, In: IEEE Transactions on Power Systems. 39, 2, p. 4350-4359 10 p.Research output: Contribution to journal › Article › Research › peer-review
11 Citations (Scopus) -
Learning regionally decentralized AC Optimal Power Flows with ADMM
Mak, T. W. K., Chatzos, M., Tanneau, M. & Hentenryck, P. V., Nov 2023, In: IEEE Transactions on Smart Grid. 14, 6, p. 4863-4876 14 p.Research output: Contribution to journal › Article › Research › peer-review
24 Citations (Scopus) -
Grid optimization competition on synthetic and industrial power systems
Safdarian, F., Snodgrass, J., Yeo, J. H., Birchfield, A., Coffrin, C., Demarco, C., Elbert, S., Eldridge, B., Elgindy, T., Greene, S. L., Guo, N., Holzer, J., Lesieutre, B., Mittelmann, H., O'Neill, R. P., Overbye, T. J., Palmintier, B., Van Hentenryck, P., Veeramany, A. & Mak, T. W. K. & 1 others, , 2022, 2022 North American Power Symposium (NAPS 2022). Chen, J., Liu, C., Palmer, J. & Merrill, H. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 811-816 6 p. (2022 North American Power Symposium, NAPS 2022).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other
9 Citations (Scopus) -
Spatial network decomposition for fast and scalable AC-OPF learning
Chatzos, M., Mak, T. W. K. & Hentenryck, P. V., Jul 2022, In: IEEE Transactions on Power Systems. 37, 4, p. 2601-2612 12 p.Research output: Contribution to journal › Article › Research › peer-review
46 Citations (Scopus)
Activities
- 1 Contribution to conference
-
IEEE Power and Energy Society General Meeting 2023
Mak, T. (Organiser), Fioretto, F. (Organiser) & Van Hentenryck, P. (Organiser)
16 Jul 2023 → 20 Jul 2023Activity: Participating in or organising an event types › Contribution to conference