Bowen Hou

Bowen Hou

PhD Candidate

Diana Qiu's Group, Yale University

Biography

Hi! My name is Bowen Hou (侯博文). I am a third year PhD candidate at Yale , where I am fortunate to be advised by Prof. Diana Qiu. Before this, I studied at Fudan University and graduated with the highest honor for undergraduate students (Fudan Graduation Star)

I work in theoretical and computational condensed matter physics. My research includes machine learning, first-principle computational methodology development and high performance computing (HPC).

More specifically:

  • Apply machine learning approaches in condensed matter physics. Currently focus on using unsupervised learning and generative model (e.g. VAEs) to study electronic structures and predict complicated downstream many-body interaction.
  • Develop and apply the first-principle algorithm to investigate the complex many-body interaction in quantum systems. Currently focus on the exciton-phonon coupling and non-equilibrium exciton dynamics in low-dimensional quantum system.
Interests
  • Condensed Matter Physics
  • Machine Learning
  • Many-Body Interaction
  • First Principle Calculation
  • Exciton
Education

  • Ph.D., 2021-present

    Yale University

  • B.E. in Optics, 2016-2021

    Fudan University

Talks

2024:

  • APS March Meeting, “Understanding Exciton-Phonon Interactions for Long-lived High-lying Resonant Excitons in WSe2”, Minneapolis, USA

2023:

  • APS March Meeting, “Exchange-Driven Intermixing of Bulk and Topological Surface State by Chiral Excitons in Bi2Se3”, Las Vegas, USA
  • Instructor for BerkeleyGW Workshop, Oakland, USA

2022:

  • Center for Computational Study of Excited-State Phenomena in Energy Materials (C2SEPEM), “Long-Lived Chiral Excitons in the 3D Topological Insulator Bi2Se3”, Virtually
  • APS March Meeting, “Ab initio study of quasiparticle band structure and chiral exciton in the topological insulator Bi2Se3”, Chicago, USA

2020:

  • The 20th Anniversary Celebration Department of Optical Science (Fudan), “Exciton Behavior and Tunable Mobilities in JTMDs”, Shanghai, China

Academic Service

Journal Referee:

  • Crystal
  • Solid State Communications
  • Computational Materials Science

Teaching Fellow:

  • TA ENAS 775 (Yale, 2023)
  • TA MENG 211 (Yale, 2022)
  • TA PHYS 130107 (Fudan, 2019, 2020)

Projects

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All Machine Learning Exciton Dynamics Topological Insulator Collaboration
Exciton in Topological Insulator
Our results address fundamental questions about the degree to which electron-hole interactions can relax the topological protection of surface states and dipole selection rules for circularly polarized light in TIs by elucidating the complex intermixture of bulk and surface states excited in optical measurements and their coupling to light.
PDF
Exciton in Topological Insulator
Exciton-Phonon Interaction in Low-dimensional Quantum System
Coming Soon!
Exciton-Phonon Interaction in Low-dimensional Quantum System
Spin-Stabilization by Coulomb Blockade in a Vanadium Dimer in WSe2
In this study, we examine vanadium-doped WSe2 monolayers on quasi-freestanding epitaxial graphene, by high-resolution scanning probe microscopy and ab initio calculations. Our findings provide microscopic insights into the charge stabilization and many-body effects of single dopants and dopant pairs in a TMD host material.
PDF
Spin-Stabilization by Coulomb Blockade in a Vanadium Dimer in WSe2
Unsupervised Learning of Individual Kohn-Sham States
In this work, we showcase for the first time that a well-crafted VAE is capable of representing KS-DFT wavefunctions on a manifold within a significantly compressed latent space, which is 103 103 times smaller than the original input. Importantly, these succinct representations still retain the full physical information inherent in the initial data.
Unsupervised Learning of Individual Kohn-Sham States

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