Our paper on the forward mode differentiation of Maxwell’s equations was published in ACS Photonics! This mode is the counterpart to the adjoint / backward mode typically used in inverse design.
Our work towards realizing nonlinear activation functions for optical neural networks was published in IEEE Journal of Selected Topics in Quantum Electronics
Greetings, and welcome to my website!
I am currently a Postdoctoral Researcher at Stanford University in Professor Shanhui Fan’s research group. Previously, I was at The University of Texas at Austin, where I graduated in 2017 with a PhD in Electrical Engineering.
I am an engineer with a research background in optics and electromagnetics. I am also excited by physics at the intersection between optics, electronics, mechanics, and acoustics. Generally, I am interested in any application of these kinds of physics that involves information processing, analog computing, and neuromorphic hardware. I also really enjoy developing numerically-focused software in Python, Julia, Matlab, and other languages for high-performance simulation and optimization.
Lately, I have been interested in using the automatic differentiation capabilities of libraries like Tensor Flow and PyTorch (which are typically used for machine learning) for inverse design problems and, more generally, for physics-constrained optimization. Check out my software page for more information on some of my projects. In general, I think it is a very exciting time to be working in the areas where computational / numerical physics, machine learning, and optimization overlap. Along a related direction, I have been exploring how optical, acoustic, and other physics can be used to develop specialized hardware platforms for machine learning and analog computing. I think this is currently a very exciting research direction. Feel free to check out some of my recent papers for more information on these ideas.
During my PhD, I worked on several projects that spanned a large part of the electromagnetic spectrum, ranging from microwave and terahertz frequencies to the optical regime. One of these projects led to the development of a microwave fiber transmission line with engineered attenuation for applications in broadband sensing and communications. I also led several efforts to engineer graphene nanostructures for light-matter interaction and optomechanics at terahertz frequencies. The last project of my PhD led to the development of a design for integrated magnet-free nonreciprocal optical devices and involved novel finite element simulation techniques for modeling dynamic modulation.