Always fair, encouraging, and motivating.
Always patient, kind, and understanding.
Makes even dry topics interesting.
Creates a safe and inclusive space.
Encourages students to think critically.
Hao Wang is an ARC Discovery Early Career Researcher Award (DECRA) Fellow and Senior Lecturer in the Department of Data Science and Artificial Intelligence within the Faculty of Information Technology at Monash University. He also holds affiliations with the Monash Energy Institute and Monash AI Institute. Wang earned his PhD from The Chinese University of Hong Kong under the supervision of Prof. Jianwei Huang. His prior appointments include Postdoctoral Research Fellow at Stanford University's Sustainable Systems Lab working with Prof. Ram Rajagopal and Dr. Chin-Woo Tan, as well as Washington Research Foundation Innovation Fellow at the University of Washington in Seattle with Prof. Baosen Zhang in 2016.
Wang's research focuses on applied machine learning and data analytics for smart grids and smart cities, optimization of power and energy systems, and business models and mechanism design to incentivize participation of electric vehicles and prosumers. Key areas include reinforcement learning and online learning for energy systems, data analytics for distributed energy resources, and energy economics via game-theoretic analysis. He has received numerous accolades, including the ARC DECRA Fellowship, Washington Research Foundation Innovation Fellowship in 2016, Best Paper Award at IEEE PECON 2016, Best Paper Run-Up at IEEE ICC 2017, Excellent Paper Award from Energy Conversion and Economics in 2023, Young Scientist Award at AEEES 2023, First Prize Paper Award from IEEE Industry Applications Magazine in 2024, Best Vision Paper Award from ACM SIGSPATIAL 2024, and Best Paper Awards at IEEE SmartGridComm 2025 and IEEE EPEC 2025. Notable publications encompass 'Smart online charging algorithm for electric vehicles via customized actor-critic learning' (IEEE Internet of Things Journal, 2022), 'Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant' (Applied Energy, 2021), 'Machine learning approach to uncovering residential energy consumption patterns based on socioeconomic and smart meter data' (Energy, 2022), 'Incentivizing energy trading for interconnected microgrids' (2018), and 'Virtual Energy Storage Sharing and Capacity Allocation' (2020). Wang serves as Associate Editor for Energy Conversion and Economics since May 2022, IEEE Access, and Frontiers in Energy Research since August 2022, and on the editorial board of the International Journal of Precision Engineering and Manufacturing-Green Technology. He contributes to conference organization, including ACM e-Energy 2019 and IEEE SmartGridComm, and leads projects such as ARC-funded Human-in-the-loop Microgrid Project and CSIRO Next Generation AI for Clean Energy and Sustainability.