Xuezhou (Jack) Zhang

About

My research interest is in developing machine learning algorithms with strong theoretical and empirical performances, with a recent focus on Online and Reinforcement Learning, Algorithmic Robustness against Biased and Noisy Data, Representation Learning, Human-in-the-loop Learning, and Learning for Science.

Research topics

• Computer Science
• Physics
• Acoustics
• Materials science
• Optoelectronics
• Optics
• Telecommunications
• Artificial Intelligence
• Electrical engineering
• Engineering

Selected publications

• Terahertz investigation of bound states in the continuum of metallic metasurfaces

  Optica · 2020 · 194 citations

  Senior authorCorresponding

  The concept of “bound states in the continuum” (BIC) describes an idealized physical system exhibiting zero radiative loss composed, for example, of an infinitely extended array of resonators. In principle, vanishing of radiative losses enables an infinitely high-quality factor and corresponding infinite lifetime of the resonance. As such, BIC inspired metasurfaces and photonic designs aim to achieve superior performance in various applications including sensing and lasing. We describe an analyt…

  DOI

• Auxetics‐Inspired Tunable Metamaterials for Magnetic Resonance Imaging

  Advanced Materials · 2021 · 47 citations

  Senior authorCorresponding

  Auxetics refers to structures or materials with a negative Poisson's ratio, thereby capable of exhibiting counterintuitive behaviors. Herein, auxetic structures are exploited to design mechanically tunable metamaterials in both planar and hemispherical configurations operating at megahertz (MHz) frequencies, optimized for their application to magnetic resonance imaging (MRI). Specially, the reported tunable metamaterials are composed of arrays of interjointed unit cells featuring metallic helice…

  PublisherOA PDFDOI

• Helmholtz Coil‐Inspired Volumetric Wireless Resonator for Magnetic Resonance Imaging

  Advanced Materials Technologies · 2023 · 18 citations

  Senior authorCorresponding

  Abstract Signal‐to‐noise ratio (SNR) is one of the most common metrics in assessing the image quality of magnetic resonance imaging (MRI). Among a host of technological developments, various wireless devices, including metamaterials and volumetric wireless resonators have been reported to enhance SNR by redistributing the radio frequency magnetic field in the near field region. While theoretically feasible, their widespread clinical adoption has been limited by their field inhomogeneity, limited…

  PublisherOA PDFDOI

• Wireless, customizable coaxially shielded coils for magnetic resonance imaging

  Science Advances · 2024 · 16 citations

  Senior authorCorresponding

  Anatomy-specific radio frequency receive coil arrays routinely adopted in magnetic resonance imaging (MRI) for signal acquisition are commonly burdened by their bulky, fixed, and rigid configurations, which may impose patient discomfort, bothersome positioning, and suboptimal sensitivity in certain situations. Herein, leveraging coaxial cables' inherent flexibility and electric field confining property, we present wireless, ultralightweight, coaxially shielded, passive detuning MRI coils achievi…

  PublisherDOI

• Computational‐Design Enabled Wearable and Tunable Metamaterials via Freeform Auxetics for Magnetic Resonance Imaging

  Advanced Science · 2024 · 8 citations

  Senior authorCorresponding

  Metamaterials hold significant promise for enhancing the imaging capabilities of magnetic resonance imaging (MRI) machines as an additive technology, due to their unique ability to enhance local magnetic fields. However, despite their potential, the metamaterials reported in the context of MRI applications have often been impractical. This impracticality arises from their predominantly flat configurations and their susceptibility to shifts in resonance frequencies, preventing them from realizing…

  PublisherDOI

Recent grants

• Metamaterial-Enabled magnetic Resonance Imaging Enhancement

  NIH · $660k · 2018–2023

• Mechanical Behavior of Amorphous Plasma-Enhanced Chemical Vapor Deposited Silicon Oxide Films for MEMS Applications

  NSF · $162k · 2007–2011

• Collaborative Research: Elastic and Viscoelastic Characterization and Modeling of Polymer based Structures for Biological Applications

  NSF · $225k · 2008–2013

Frequent coauthors

• Yi Fang

  123 shared

• Richard D. Averitt

  University of California, San Diego

  103 shared

• Jingwen Guo

  Inner Mongolia University

  90 shared

• Xiaoguang Zhao

  76 shared

• Kebin Fan

  58 shared

• Stephan W. Anderson

  54 shared

• Renhao Qu

  41 shared

• Jie Zhou

  37 shared

Labs

• Machine LearningPI

Education

• B.S., Applied Mathematics

  University of California, Los Angeles (UCLA)

  2016

• Ph.D., Computer Sciences

  University of Wisconsin-Madison

  2021

Similar researchers at Boston University

• Kate Saenkoh-89
• Ran Canettih-78
• Stan Sclaroffh-69