I am a fifth year PhD student at UW-Madison advised by Prof. Krishnan Suresh at the Engineering Representations and Simulation Lab, majoring in Mechanical Engineering with a minor in Computer Sciences.

My research interests include engineering design optimization, numerical methods for PDEs, and machine learning. Recently, I developed a novel approach for representing engineering materials and catalogs using neural networks (autoencoders) enabling visualization, optimal selection, and customization. Additionally, I have explored using implicit neural networks for geometric representation and automatic differentiation in the design of microstructures and designs that span multiple scales via topology optimization.

I believe that the integration of optimization techniques and machine learning can not only elevate engineering design but also inform engineers and practitioners with invaluable understanding and insights.

You can find more details about my work by checking the publications and talks tabs, and my contact details on the sidebar. I’d love to connect!

News

July 24: Presented on material selection and topology optimization at WCCM 2024, Vancouver, Canada.

May 24: Work on hybrid machine learning and evolutionary approach to material selection and design optimization for eco-friendly structures publish in SAMO

Jan 24: Interned at Ansys, Austin TX for the Spring 2024 semester.

Sep 23: Presented a poster at the annual PANTHER workshop, Madison, WI

Aug 23: Presented at the ASME-IDETC 2023 - Boston, MA

Mar 23: Work on visual representation of engineering catalogs accepted to ASME-IDETC 2023

Jan 23: Work on graded multiscale topology optimization published in Advanced in Engg Software