Krishna Kumar

Krishna Kumar is an Assistant Professor in the Department of Civil Engineering at The University of Texas at Austin, holding the J. Neils Thompson Centennial Teaching Fellowship. His expertise lies in Geotechnical Engineering and Sustainable Systems Engineering, with a focus on multi-scale modeling of natural hazards, landslides, earthquakes, and debris flows. He employs advanced computational techniques such as the material point method, discrete element method, and lattice Boltzmann method, alongside high-performance computing and big data frameworks for infrastructure system modeling.

Education:

• Ph.D., University of Cambridge, 2015
• M.S., Indian Institute of Technology Madras, 2010
• B.E., Anna University, 2008

Research Interests: His technical interests include computational geomechanics, granular material simulations, and the integration of machine learning with physics-based models. Recent work emphasizes inverse analysis using differentiable neural networks, explainable AI for geotechnical risk assessment, and innovative teaching methods like murder mysteries to enhance engineering education.

Publications Trend: His articles from 2023–2025 highlight advancements in hybrid numerical methods (e.g., finite element-material point method), machine learning-driven simulations of granular flows, and computational tools for predicting geotechnical hazards. Cross-disciplinary themes include AI explainability, granular material behavior under cyclic loading, and scalable city-level traffic modeling.

Teaching & Innovation: Beyond technical research, he explores pedagogical innovations such as gamified learning through murder mystery scenarios to engage students in complex engineering concepts.