Ph.D. student Ripon Chandra Malo is driven by a passion for advancing geotechnical engineering through data, computation, and innovation. His research focuses on granular material compaction and the application of artificial intelligence to improve how engineers interpret subsurface conditions—bridging the gap between complex geotechnical data and real-world decision-making.

That work recently earned national recognition at GeoCongress 2026, where Malo won the championship title at the first-ever G-I DIGGS Student Hackathon. Representing the University of Utah as part of Team “Ground Decoder,” he competed against leading national and international teams to tackle real-world geotechnical data challenges.

DIGGS, Data, and Discovery

With advising support from Dr. Tong Qiu and Dr. Kami Mohammadi, Malo developed DIGGS Analyzer, a web-based platform that transforms DIGGS XML files into actionable engineering insights. The tool integrates data parsing, visualization, and core analyses—such as liquefaction, settlement, and bearing capacity—along with an AI-powered assistant designed to deliver geotechnical-specific interpretations based strictly on project data. Judges recognized the project for its technical depth, innovation, and strong real-world applicability.

Originally from Bangladesh, Malo is a second-year Ph.D. student in the Department of Civil & Environmental Engineering at the University of Utah. He conducts his research under an NSF-funded project and is advised by Dr. Tong Qiu, with additional mentorship from Dr. Kami Mohammadi.

Their guidance, combined with Malo’s research vision, reflects the collaborative and forward-looking environment at the University of Utah, where he continues to develop tools that push the boundaries of modern geotechnical engineering.