Yu Pan

Yu Pan is a Research Assistant Professor in the Department of Biological Systems Engineering at the University of Nebraska-Lincoln (UNL). He holds a Ph.D. in Computer Science from UNL, an M.S. in Information Management from Illinois Institute of Technology, and a B.S. in Computer Science and Technology from the University of Electronic Science and Technology of China. His research focuses on Graph Learning, Manifold Learning, Representation Learning, and Data Visualization, with applications in interdisciplinary fields such as biological systems and meteorology. He designs and maintains the Scientific Data Management Infrastructure for the Institute of Agriculture and Natural Resources (IANR), implementing FAIR principles to standardize data pipelines and enhance accessibility for researchers. His work also involves High Performance Computing (HPC) frameworks like MPI and CUDA to optimize data processing and analysis.

Education:

• Ph.D., Computer Science, University of Nebraska-Lincoln
• M.S., Information Management and Technology, Illinois Institute of Technology
• B.S., Computer Science and Technology, University of Electronic Science and Technology of China

Research Interests: Dr. Pan’s work bridges computational methods with scientific data challenges. He explores techniques to extract meaningful insights from complex datasets using graph-based approaches and manifold learning, while advancing visualization tools to aid domain scientists. His infrastructure projects emphasize scalable, FAIR-compliant systems to manage heterogeneous data across disciplines. Current collaborations with biological and environmental researchers aim to enhance data-driven decision-making through advanced analytics.

Advising and Infrastructure: While no formal advisees are listed, his role in IANR’s data infrastructure project underscores his leadership in collaborative scientific computing. The infrastructure facilitates interdisciplinary research by integrating spatially and temporally co-located datasets, enabling researchers to explore patterns in agriculture, climate, and natural resources.

Labs/Teams: He is affiliated with the Department of Biological Systems Engineering and contributes to the IANR’s data management initiatives, fostering cross-disciplinary innovation through computational solutions.