I received my B.S. in Communication Engineering from the School of Electronic and Information Engineering, Beijing Jiaotong University in June 2025. I am currently a Ph.D. student in Electrical and Computer Engineering at the University of Massachusetts Amherst, advised by Prof. Jun Yao. My current research interests center on bioelectronics and physiological sensing, with an initial focus on mesh-based bioelectronic interfaces. I am also exploring possible connections between AI, signal processing, and bioelectronic systems. You can find more information in my CV.

Research Interests

Bioelectronics & Physiological Sensing

  • Flexible and conformal bioelectronic devices for interfacing with biological tissues.
  • Mesh-based electrode arrays and multichannel electrophysiological recording.

AI & Biosignal Processing (Exploratory)

  • Exploring machine learning and signal-processing methods for interpreting physiological recordings.
  • Identifying opportunities to integrate AI with bioelectronic sensing systems.

Low-Power Hardware & System Integration

  • Broader interests in energy-efficient circuits, hardware-aware computing, and on-device sensing.

📄 Publications

  1. Yin Zhang†, Zhouzhuo Guo†, Bokai Xu, Jiayi Zhang, Huahua Xiao, Wei E. I. Sha, Bo Ai. Performance Analysis of Non-paraxial Deployments Continuous Aperture MIMO for Electromagnetic Information Theory. Electromagnetic Science, vol. 4, no. 2, article no. 0140222, 2026. · Co-first author; † equal contribution · DOI · PDF
  2. Yin Zhang†, Zhouzhuo Guo†, Zhe Wang, Bokai Xu, Huahua Xiao. Research on Mutual Information for Multi-user Extremely Large-scale MIMO Systems Based on Electromagnetic Information Theory. Radio Communications Technology, 2023. Peking University Chinese Core (2023 edition) · Co-first author; † equal contribution · CNKI

Selected Projects

AI Accelerator Architecture & Performance Modeling — Duke University (2025)

  • Developed Python-based architecture-level models for AI accelerator workloads, including Point Transformer V2 and diffusion models, to study execution behavior and hardware resource trade-offs.
  • Examined performance-related parameters and power/area assumptions across hardware configurations. Project code.

VLSI Physical Design & Back-End Implementation — Duke University (2026)

Responsible for physical design and back-end implementation of AI accelerator chips, including floorplanning, placement, routing, and implementation verification.

FractalCloud accelerator chip layout
FractalCloud — Chip Layout
AI accelerator physical-design layout
AI Accelerator — Chip Layout

Earlier Academic Projects

Virtualized Platform-Based 5G Network Planning and Design (Graduation Project)

  • Leveraged the Lingte 5G virtual simulation platform and proposed an end-to-end network-planning framework for cross-regional connected-vehicle scenarios.

Continuous Aperture MIMO for Electromagnetic Information Theory

  • Multi-user XL-MIMO: Uses a random-field model to derive MI expressions under multi-user interference and varying noise, quantifying the effects of discrete sampling and noise power on performance.
  • CAP-MIMO (non-paraxial): Derives tractable MI formulas via dyadic Green’s functions and shows how azimuth, sampling density, and receiver motion govern capacity and MI statistics.

🎓 Education

  • 2026–present University of Massachusetts Amherst — Ph.D. in Electrical and Computer Engineering; Advisor: Prof. Jun Yao.
  • 2021–2025 Beijing Jiaotong University — B.S. in Communication Engineering, Jun 2025.

Research Experience

  • Feb–Jun 2026 Research Intern (Unpaid) — Duke University, Electrical and Computer Engineering (Remote). Back-end physical design and implementation of AI accelerator chips.
  • Jul–Sep 2025 Research Intern (Unpaid) — Duke University, Electrical and Computer Engineering (On-site). AI accelerator architecture and performance modeling.

🏅 Honors and Awards

  • 2024 National-level Grant, BJTU Undergraduate Innovation & Entrepreneurship Program — School of Electronic and Information Engineering: 1st place; nominated to the 18th National Undergraduate Innovation & Entrepreneurship Annual Conference (Paper Track, 2025).
  • 2024 Silver Award, “Challenge Cup” Undergraduate Entrepreneurship Training Project, Beijing Jiaotong University.

🛠 Skills

Language：Python, C   |   Tools：Cadence Innovus, Cadence Virtuoso, MATLAB, Git/GitHub, LaTeX/Overleaf, Linux shell

👋 About Me

  • Curious, open-minded, collaborative and friendly.
  • Hobbies: 🎧 Music, 🧩 LEGO, 🏸 Badminton.