About me

I'm a Mathematics PhD student at Tufts University working at the intersection of scientific computing, numerical optimization, and deep learning. My research focuses on developing mathematically grounded neural network architectures and computational methods, with an emphasis on reliable and efficient algorithms for scientific applications.

My research interests include scientific computing, deep learning, numerical methods and optimization, topology optimization, and generative modeling.

I am currently developing a unified framework for discriminative learning and generative modeling using diffeomorphic transformations in reproducing kernel Hilbert spaces (RKHSs).

I work under the supervision of Andreas Mang.

Prior to joining Tufts, I pursued my doctoral studies at the University of Houston.

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