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Professor Raymond R. Tan

Raymond R. Tan is a Distinguished Full Professor of the Department of Chemical Engineering, a University Fellow, and the Vice-President for Research and Innovation of De La Salle University. He is a Fellow of The World Academy of Sciences and an Academician of the Philippine National Academy of Science and Technology. Prof. Tan works in the areas of process systems engineering and process integration, and is best known as the co-developer of the carbon emissions pinch analysis technique. He is a founding editor-in-chief of Process Integration and Optimization for Sustainability, an associate editor of Sustainable Production and Consumption, and an editorial board member of other scientific journals. He is also a multi-awarded academic who has been listed in the Scopus database of the top 2% of the world’s scientists since 2019 and in the Reuters “Hot List” of the 1,000 most globally influential climate researchers.

Professor Suzana Yusup

Application of Machine Learning (ML) and Computational Modelling (CM) in Energy Transition Journey to Achieve Net Zero 2050

Climate change has significantly impacted the livelihood of mankind. Extreme weather, rising of sea levels and increasing temperature are among the results of climate change. Globally and nationally significant measures have been addressed to mitigate the impact of climate change not limited to policies and developed strategies. Malaysia pledged to achieve the Net Zero target by 2050. To progress towards this target, the Carbon Development Strategy for Malaysia has been established to progress towards achieving the Net Zero target. Industry sectors are paving to reduce carbon emissions through improved energy efficiencies, integration of renewables in the energy mix and applying fuel switching among the initiatives. The talk highlights low-carbon development initiatives from lab to industrial case studies that apply ML and Computational Modelling. ML and deep learning play significant roles in today’s computational era to enable predictions/forecast specific outcomes with a higher degree of accuracy and finding patterns and relationships in data for various aims. It enables prediction and forecasted scenarios ranging across many disciplines and chemical engineering. 

Professor Pei Liu

Energy systems engineering and applications in the energy sector

The energy sector is going through an unprecedented transition period towards a less carbon-intensive end. The way human society uses and consumes energy is expected to change dramatically from the way as of today, from centralized generation and distribution to more distributed yet integrated, from fossil fuel dominated to renewable energy dominated, and from automatic energy management and control to intelligent. The transition period that we are going through is thus a rather challenging one as the energy systems need to have tremendous structural changes whilst meeting energy demands. Energy systems engineering, as a branch of process systems engineering, could facilitate this procedure with the planning, design, and operation of various energy systems. In this talk, we will illustrate how energy systems engineering concept and methods can be used in planning of the energy transition pathway of a large region, which is heterogeneous in terms of energy supply and demand, optimal design of integrated energy systems, intelligent operation of energy systems through mechanism-modelling and big data based digital twins, and flexible operation of energy systems to accommodate intermittent renewable energy. 

Professor Fengqi You

Fengqi You is the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering at Cornell University. He holds affiliations with multiple Graduate Fields at Cornell, including Chemical Engineering, Computer Science, Electrical and Computer Engineering, Operations Research and Information Engineering, Systems Engineering, Mechanical Engineering, Civil and Environmental Engineering, and Applied Mathematics. Within Cornell, he serves as the Chair of Ph.D. Studies in Systems Engineering, Co-Director of the Cornell University AI for Science Institute (CUAISci), Co-Director of the Cornell Institute for Digital Agriculture (CIDA), and Director of the Cornell AI for Sustainability Initiative (CAISI). Before joining Cornell in 2016, he worked at Argonne National Laboratory’s Mathematics and Computer Science Division and served as a faculty member at Northwestern University. His research focuses on fundamental theories and methods of systems engineering, with applications in materials informatics, smart manufacturing, digital agriculture, energy systems, and sustainability. Fengqi has an h-index of 91 and has authored over 300 refereed articles in journals such as Nature, Science, Nature Sustainability, Nature Food, Nature Communications, Science Advances, and PNAS. His research has garnered editorial highlights in Science and Nature, featured on dozens of journal covers (e.g., Energy & Environmental Science), and covered by leading media outlets (e.g., New York Times, BBC, Reuters, Washington Post, Forbes, Wall Street Journal, Fortune, Daily Mail, The Guardian, Agence France-Presse, Bloomberg, Scientific American, Newsweek, BusinessWeek, Hill, CNN, Harvard Business Review, New Scientist, and National Geographic).  He is an award-winning scholar and teacher, having received over 25 major national and international awards in the past six years from leading professional organizations such as the American Institute of Chemical Engineers (AIChE), American Chemical Society (ACS), Royal Society of Chemistry (RSC), American Society for Engineering Education (ASEE), and American Automatic Control Council (AACC), in addition to multiple best paper awards. Selected ones include the NSF CAREER Award (2016), AIChE Environmental Division Early Career Award (2017), AIChE Research Excellence in Sustainable Engineering Award (2017), Computing and Systems Technology (CAST) Outstanding Young Researcher Award from AIChE (2018), Cornell Engineering Research Excellence Award (2018), ACS Sustainable Chemistry & Engineering Lectureship Award (2018), AIChE Excellence in Process Development Research Award (2019), AIChE Innovations in Green Process Engineering Award (2020), Mr. & Mrs. Richard F. Tucker Excellence in Teaching Award (2020), ASEE Curtis W. McGraw Research Award (2020), O. Hugo Schuck Award from AACC (2020), AIChE Sustainable Engineering Forum Education Award (2021), AIChE George Lappin Award (2022), Stratis V. Sotirchos Lectureship Award by the Foundation for Research & Technology – Hellas (FORTH) (2022), and the Lawrence K. Cecil Award in Environmental Chemical Engineering (2024). He serves as an editor of Computers & Chemical Engineering; associate editor of the AAAS journal Science Advances, Applied Energy, and IEEE Transactions on Control Systems Technology; consulting editor of the AIChE Journal; subject editor of Advances in Applied Energy; guest editor of Energy, Journal of Cleaner Production, and Renewable & Sustainable Energy Reviews; and was on the editorial boards of ACS Sustainable Chemistry & Engineering, Industrial & Engineering Chemistry Research, PRX Energy, and more. He is an elected Fellow of the Royal Society of Chemistry (FRSC), Fellow of the AIChE, and Fellow of the American Association for the Advancement of Science (AAAS).