Xiaoru Zhang

2515 Speedway

Austin, Texas 78712

I am a Ph.D. candidate in Physics with a focus on computational and theoretical condensed matter physics. My current research centers on modeling of ferroelectric oxides. I am particularly interested in integrating traditional physics-based models with emerging machine learning and data-driven approaches to predict the behavior of large-scale atomic systems. These modeling methods have the potential to accelerate the development of next-generation, energy-efficient electro-optic devices based on ferroelectric materials.

My academic journey began with experimental research on nano-scale acoustic metamaterials. While I achieved promising result in this area, I found myself developed a deeper passion for theoretical modeling and computation methods, which ultimately led me to shift my research focus.

In parallel with my Ph.D., I am also pursuing a Master’s degree in Statistics. I began this path with the goal of building a solid foundation in statistical modeling and machine learning. I believe a deeper under standing of the underlying mathematical principles is essential for interpreting and applying machine learning for physics research.

latest posts

Aug 26, 2025	DFT Calculations Using Quantum ESPRESSO
Aug 18, 2025	Longest Palindromic Substring
Jul 13, 2025	Negative Binomial Distribution

selected publications

Adv. Photonics Res.

Detection and demultiplexing of cylindrical vector beams enabled by rotational Doppler effect

Xiaoru Zhang, Junliang Jia, Kaiyi Zhai, and 3 more authors

Advanced Photonics Research, 2022

Abs DOI

Cylindrical vector beams (CVBs) detection is of vital significance in various kinds of studies such as particle observation and mode-division multiplexing (MDM). Herein, a comprehensive detection of CVBs based on the rotational Doppler effect (RDE) including analysis of topological charge (TC), relative amplitude module, and phase for superimposed mode bases is realized. A mode demultiplexing scheme is constructed through the complex amplitude of the harmonic terms in the beating signal. The method resolves both absolute values and signs of the TC of CVB simultaneously, which cannot be simply realized by existing polarization examination techniques. It may be of big potential in related research since an efficient, quantitative, and complete scheme to detect CVBs is verified starting from this work.
AIP Advances

Reservoir computing using a Si-integrated electro-optic oxide: A numerical study

Xiaoru Zhang and Alexander A. Demkov

AIP Advances, May 2026

Abs DOI

Reservoir computing is a compelling neuromorphic architecture due to its natural compatibility with many physical systems. Among available implementations, the electro-optic reservoir, where an optical delay feedback loop serves as the reservoir, offers energy-efficient computation without the need for a separate memory, making its chip-scale implementation very appealing. Barium titanate, with its exceptionally large Pockels coefficient, has recently enabled significant advances in compact electro-optic modulators, positioning it as a suitable platform for such a chip-scale electro-optic reservoir. Here, we numerically investigate the performance of an electro-optic reservoir under the practical constraints of a Si-integrated photonic design. We also introduce a method of constructing reservoir states that results in a significant performance improvement. Furthermore, we demonstrate the superior energy efficiency of barium titanate-based devices, owing to their very efficient electro-optic modulation. Our results show that compact, energy-efficient electro-optic reservoirs are feasible using barium titanate-based integrated Si photonic devices.