Guest Seminar - Scalable Decision-Making in Chemical Engineering for a Greener Future
Humans are facing many unprecedented environmental problems, such as waste pollution and climate change. Addressing these urgent issues calls for advanced decision-making frameworks to design, plan, and operate various infrastructures for waste valorization and energy transition with high efficiency and reliability. First, I will describe a unified optimization framework that enables the optimal design and operation of large-scale waste valorization infrastructures. This framework reveals the economic viability and environmental benefits of such infrastructures and informs policy implications. Second, I will outline an optimization framework that integrates smart electrification with chemical processes. This offers grid flexibility, smoothens the energy transition, and reduces chemical production costs. Additionally, I will present the algorithms and software we've developed to address these complex, large-scale decision-making challenges, leveraging graph theory, classical decomposition methods, and new computing architectures like GPUs.
Jiaze Ma is a PhD candidate at the University of Wisconsin-Madison in the Department of Chemical and Biological Engineering, working with Prof. Victor Zavala. His research focuses on developing optimization models, algorithms, and software to address pressing energy and environmental challenges, such as waste valorization and smart electrification. By using advanced decision-making and data analysis techniques, his aim is to identify and implement solutions that enhance sustainability and efficiency in these domains.