About Me

I am a PhD student in Mathematics at George Mason University, working in PDE-constrained optimization, inverse problems, and scientific computing. My current research focuses on risk-averse optimization and numerical methods for optimization problems governed by partial differential equations, including inverse problems with CVaR-based spatial regularization and adjoint-based finite element implementations.

More broadly, I am interested in the interaction between analysis, optimization, probability, and computation. I am particularly fascinated by stochastic models and uncertainty in optimization, since randomness is an unavoidable part of most real-world systems. To me, incorporating stochasticity into mathematical models feels like one step closer to describing reality more faithfully.

I also have a deep appreciation for functional analysis and the geometric and infinite-dimensional viewpoint it brings to mathematics. Much of what draws me to mathematics is the balance between rigor, structure, intuition, and creativity.

Outside research, I am strongly inspired by visual approaches to learning mathematics, especially the style of 3Blue1Brown and Grant Sanderson’s philosophy of building deep intuition through visualization and exploration. I am increasingly interested in communicating mathematical ideas visually and computationally, particularly for PDEs, stochastic processes, and optimization.

Beyond mathematics, I enjoy playing guitar and studying music theory, especially jazz-influenced improvisation and harmonic ideas involving nondiatonic movement and extended harmony. I also enjoy reading, films, hiking, long walks in nature, and exploring new technology.

And yes — I still prefer chalkboards over whiteboards.