I earned my Ph.D. in Structural Engineering from UC San Diego in 2023, with a focus on multi-scale modeling of soft tissues and the mechanics of force transmission in skeletal muscle. I recently completed my Postdoctoral training at the CoMMaND Lab in the University of Notre Dame, where I developed computational models to understand how complex materials such as biological tissues grow, adapt, and respond to mechanical forces. Currently, I work as an R&D engineer in the materials team at Ansys (part of Synopsys).

My work sits at the intersection of material science, finite element modeling, and physics-informed machine learning. I build models that connect length scales, analyzing the upstream effect of lower length scale phenomena. These models answer fundamental questions about the behaviour of complex materials under real life scenarios, ranging from a tissue's response to its mechanical environment, to hydrogen embrittlement in high strength metals. I am also interested in inverse modeling — using statistical methods or physics-guided ML to infer properties from sparse measurements.

I enjoy combining theory, simulation, and data to uncover mechanisms in materials and translate them into predictive models. If you're interested in computational mechano-biology, solid mechanics, material growth & remodeling, or interdisciplinary collaborations across engineering and life sciences, I'd love to connect.

Google Scholar: https://shorturl.at/m4dKD

You can also reach out to me at ktaneja@ucsd.edu (ktaneja[at]ucsd[dot]edu) or drop me a message on twitter.