I am an Associate Mechanical Engineer in the Engineering Mechanics and Design (EMD) group at Stress Engineering Services, Inc. (SES), where I apply advanced computational mechanics, finite element analysis (FEA), and fitness-for-service (FFS) methodologies to solve complex engineering challenges across a wide range of industries. My work involves structural integrity assessments, fracture mechanics, nonlinear analysis, pressure equipment evaluation, and computational modeling for industrial assets, consumer products, and medical device applications.
I hold a PhD and MS in Mechanical Engineering from the University of Cincinnati, where my research focused on scientific machine learning and computational solid mechanics under the guidance of Prof. Kumar Vemaganti. My doctoral work explored data-efficient Gaussian Process (GP) surrogate models within Bayesian optimization frameworks and developed energy-based machine learning approaches for solving nonlinear solid mechanics problems, including hyperelastic multistable structures and phase-field plasticity. A key aspect of my research was evaluating the strengths and limitations of physics-informed machine learning methods relative to traditional finite element techniques.
During my Ph.D., I worked with Procter and Gamble (P&G) Digital Accelerator, and Innovative Numerics LLC, developing finite element models, simulation automation tools, and machine learning solutions for consumer products. Before pursuing graduate studies, I worked as a Senior CAE Engineer at Bajaj Auto Limited, applying finite element analysis and durability methods to two and three wheelers in India.