Dan Kessler

XSEDE Student Champion

Dan Kessler is the University of Michigan’s XSEDE student champion and a Ph.D. student in the U-M Department of Statistics. The Extreme Science and Engineering Discovery Environment (XSEDE) is an NSF-funded virtual organization that integrates and coordinates the sharing of advanced digital services— including supercomputers and high-end visualization and data analysis resources—with researchers nationally to support science.

As an XSEDE student champion, Dan will help U-M users access the best advanced computing resource that will help them accomplish their research goals and provide training/support for XSEDE users on campus. As a user of XSEDE resources himself, he is interested in assisting others to better leverage XSEDE resources, particularly for education and training in computation. 

Dan enjoys mentoring other students and hopes to participate in outreach activities, such as workshops, for U-M high performance computing users that may benefit from XSEDE resources. He is particularly interested in building connections and community spanning existing campus groups with an interest in high performance computing.

His Ph.D. work is largely focused on the analysis of networks obtained from human neuroimaging data. Dan’s research and studies involve large and complex datasets that demand the application of complex high-performance computing. Prior to beginning his Ph.D. studies, his primary work was a research computer specialist in the U-M Department of Psychiatry.

Dan has a history of supporting others in their use of high performance computing. He serves as the chair of the student computing committee for the Department of Statistics and is a courtesy member of the department’s faculty computing committee. In this capacity he has offered tutorials and support to fellow department members and also helped the Department of Statistics develop high performance computing strategies when transitioning from ARC’s Flux to Great Lakes.

He welcomes emails from members of the University of Michigan community interested in high performance computing. Even if they’re just starting out, he’s happy to help them better understand how their needs might be met by XSEDE (or other) resources.