PRISM Project
We look forward to the collaboration between you and the energetic and intelligent group of researchers. Industry 4.0 is transforming many industries with much of the progress through shared innovations.
This research group seeks to bring people and ideas together to increase the innovation and pace of progress. We use the latest methods for data science and provide platforms such the Gekko Optimization Suite for hybrid machine learning and optimization.
PRISM develops people and organizations through 3 routes including training, collaborating, and projects to tackle the next generation of challenges. We are glad that you are here and look forward to working together.
Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science. The group includes graduate and undergraduate students who are taking a lead role in data science, machine learning, optimization, estimation, and control applications. The PRISM group also develops new methods for large-scale and complex systems. Please reach out to Sam Arce with any additional questions or to schedule a time to talk about your company's involvement.
Collaborations
LaGrande Gunnell (Brigham Young University PhD Candidate) has been awarded the Outstanding Performance Award (OPA). This prestigious recognition comes from his mentor, Xiaonan Lu, and Richard Daniel, Team Lead of Waste Form Development at the Energy & Environment Directorate of the Pacific Northwest National Laboratory (PNNL).
During his 9-week internship at PNNL earlier this year, LaGrande made substantial contributions to the Office of River Protection (ORP) and Bechtel National, Inc. (BNI) programs. His work involved critical experimental and computational support that advanced the PNNL-led ORP Glass Science programs. Additionally, LaGrande played a crucial role in integrating Python into BNI’s APPS model, working directly with client engineers to troubleshoot model implementation issues—tasks that go beyond the typical responsibilities of a research intern.
