The Penn State Institute for Computational and Data Sciences' (ICDS) Mid-Scale Seed Grant Program has awarded over $540,000 in total to 23 Penn State faculty members across eight teams representing six colleges and three campuses - University Park, Behrend and Hershey - that will contribute to one or more of the institute's research hubs or affiliated centers.
"ICDS is thrilled to support projects and Penn State faculty as they take part in multi-disciplinary research collaborations that will contribute to one or more of our five research hubs," said Guido Cervone, ICDS director. "The ICDS research hubs are in a unique position to advance different disciplines while catalyzing vibrant communities of researchers, students, administrators and leaders who seek to educate and elevate sciences at the University."
The Mid-Scale Seed Grant Program is a new initiative that aims to accelerate multi- and interdisciplinary research projects that can build new collaborations; increase the competitiveness of an upcoming high-risk, high-reward proposal; build a foundation for future large projects; and support Penn State researchers contributing to multidisciplinary teams that extend beyond the University.
All selected projects will contribute to one or more of the five ICDS research hubs: artificial intelligence, quantum sciences, computational sciences, data sciences or digital twins.
Selected faculty members and projects are:
"Reinforcement Learning for High-Dimensional Adaptive Surrogate Modeling"
Principal investigator (PI): Nathan Brown, associate professor of architectural engineering, College of Engineering
Co-PI: Kostas Papakonstantinou, associate professor of civil and environmental engineering, College of Engineering
"Real-time thermal and flow field reconstruction via a fidelity-aware digital twin"
PI: Tamy Guimaraes, assistant professor of mechanical engineering, College of Engineering
Co-PIs: Xiang Yang, Kenneth K. and Olivia J. Kuo Early Career Professor in Mechanical Engineering, College of Engineering; Keefe Manning, professor of biomedical engineering, College of Engineering; Nicolas Tobin, assistant research professor
"Water Evaluation and Treatment Digital Twin (WET-DT): A Framework for Robust, Predictive Process Controls for Water Treatment Plants"
PI: Ilya Kovalenko, assistant professor of mechanical engineering and of industrial and manufacturing engineering, College of Engineering
Co-PIs: Margaret Busse, assistant professor of mechanical engineering, College of Engineering; Gamini Mendis, assistant professor of polymer engineering and science and of plastics engineering technology at Penn State Behrend
"Discovering Plausible Extreme Events in Large-Scale Infrastructure Systems with Multimodal Reinforcement Learning"
PI: Aron Laszka, assistant professor of informatics and intelligent systems, College of Information Sciences and Technology (IST)
Co-PI: Anirudh Subramanyam, Charles and Enid Schneider Early Career Assistant Professor of Industrial and Manufacturing Engineering, College of Engineering
"Toward Robust and Interpretable Graph Machine Learning for Molecular Discovery"
PI: Lu Lin, assistant professor of informatics and intelligent systems, College of IST
Co-PI: Vasant Honavar, ICDS co-hire, professor of informatics and intelligent systems, College of IST
"Preparation for the Creation of a National Sediment Model and NSF Center-Scale Proposal"
PI: Xiaofeng Liu, ICDS co-hire and professor of civil and environmental engineering, College of Engineering
Co-PIs: Li Li, professor of civil and environmental engineering, College of Engineering; Chaopeng Shen, professor of civil and environmental engineering, College of Engineering; Roberto Fernandez, assistant professor of civil and environmental engineering, College of Engineering; Roman DiBiase, associate professor of geosciences, College of Earth and Mineral Sciences
"iTwin-ERW: Integrated Digital Twin Framework for Decision-Support in Enhanced Rock Weathering"
PI: Tushar Mittal, assistant professor of geosciences, College of Earth and Mineral Sciences
Co-PIs: Matthew Fantle, professor of geosciences, College of Earth and Mineral Sciences; Charlie White, associate professor of plant science, College of Agricultural Sciences
"Scalable Privacy-Preserving AI for Genomic Risk Modeling"
PI: Ying Sun, assistant professor of electrical engineering, College of Engineering
Co-PIs: Dajiang Liu, distinguished professor of public health sciences and biochemistry and of molecular and precision medicine and director of artificial intelligence and biomedical informatics, College of Medicine; Lingzhou Xue, professor of statistics, Eberly College of Science
