Curriculum vitae

Zhanghao Zhouyin 周寅张皓

Physics PhD candidate · McGill University · Montréal, Canada

I develop AI-native scientific computing systems that connect machine-learned physical models, high-performance simulation, and engineering-scale prediction. My work bridges scales—from atomistic and electronic-structure simulation through quantum transport and physical observables to device-level TCAD, coupled multiphysics, and circuit-aware modeling—using scalable numerical solvers and differentiable physics.

Across scales: Atomistic / electronic structure → quantum operators and observables → quantum transport → device TCAD / multiphysics → circuit models.

Some publications use the author name Yinzhanghao Zhou or YinZhangHao Zhou.

中文版本 ↗ Research ↗ Publications ↗ Google Scholar ↗ GitHub ↗ McGill Email ↗

Education

2024–present

Ph.D. candidate in Physics, McGill University

Supervisor: Prof. Hong Guo; anticipated completion in 2027.

2021–2024

M.E. in Electronic Information, Tianjin University

Supervisor: Prof. Peng Zhang.

2017–2021

B.S. in Computer Science, Tiangong University

Supervisor: Prof. Ding Liu.

AI-native scientific computing and research projects

  • DeePTB + SLEM · 2022–2025. Co-developed learned tight-binding electronic simulation for million-atom systems (Nature Communications 2024, co-first author) and led the localized equivariant SLEM quantum-operator model (ICLR 2025 Spotlight, first author).
  • VBCSR · 2026. Designed an MPI-distributed variable-block sparse-matrix engine for orbital calculations, reporting up to 8.4× speedup in the tested sparse-multiplication benchmarks and an application to a 1,063,609-atom InP nanoparticle.
  • RESCU++ · 2026–present. Developing a C++/Python LCAO-DFT platform built on VBCSR for molecular and periodic systems, magnetism, spin–orbit coupling and hybrid functionals, with Gaussian-process SCF acceleration, Bayesian relaxation and automated validation.
  • RSATB · 2026–present. Developing diagonalization-free spectra, spatial electronic maps and response properties from large nonorthogonal Hamiltonians; large-scale twisted-trilayer-graphene study in progress, manuscript in preparation.
  • AD-NEGF. End-to-end differentiable nonequilibrium Green's-function quantum-transport simulation (Physical Review B 2023).
  • flower. Records scientific-agent calculations across local, SSH and Slurm systems and exports auditable, rerunnable protocols.

Industry and research experience

Oct 2025–Sep 2026

Research Intern · Nanoacademic Technologies Inc. (QTCAD)

Montréal. AI-enhanced multiscale modeling for Nanoacademic's QTCAD, including learned first-principles Hamiltonian surrogates for superconducting-junction and circuit quantities, and device workflows that couple finite-element electrostatics, atomistic tight binding, time-dependent quantum dynamics and circuit-level models.

May 2022–Jun 2024

Research Intern · AI for Science Institute

Beijing; machine learning for materials simulation. Research mentors: Dr. Qiangqiang Gu and Dr. Linfeng Zhang.

Oct 2020–Mar 2021

Editorial Intern · Beijing Academy of Artificial Intelligence

Tracked machine-learning research and wrote technical reviews.

Research software

Publications and preprints

This list is generated from the site's maintained publication records, so titles and publication years are not independently duplicated in the CV.

Browse publication records and citation details ↗

Leadership and service

AI4S-Benchmark · Initiator and coordinator (2026–present), organizing verifiable research-grade scientific-agent tasks across code, data, simulation and scientific tools.

Academic community: McGill Quantum Centre (MQC), Centre for the Physics of Materials (CPM), and RQMP.

Technical background and recognition

CS & HPC: Distributed block-sparse algorithms, C++17, Python, MPI/OpenMP, ELPA, ScaLAPACK, PETSc/SLEPc, FFTW, MKL.

AI & ML: Equivariant graph networks, learned Hamiltonians, active learning, Gaussian processes, Bayesian optimization, neural quantum states, PyTorch/JAX.

Physics & multiscale: LCAO-DFT, tight binding/NEGF, stochastic spectral and response methods, quantum embedding, TCAD, multiphysics device/circuit simulation.

Honors: Dr. & Mrs. Milton Leong Fellowship in Science (McGill University); National College Innovation Project (Tiangong University, 2018–2020).

Contact

yinzhanghao.zhou@mail.mcgill.ca · LinkedIn · About