Boya Hou

Thanks for visiting! I am a final-year Ph.D. student in the ECE department at University of Illinois, Urbana-Champaign. I am fortunate to be advised by Prof. Subhonmesh Bose. I received M.Eng. from UIUC and B.S. from Zhejiang University in 2019. I am broadly interested in the area of autonomy.

My CV can be found here CV.


  • Nonparametric Compressed Learning of Dynamical Systems:

    In my research, I aim to reconcile the classical model-based approach with the modern learning-based approach, where the role of a model is to represent an agent’s existing knowledge and yet to allow for data-driven tuning to perfect control designs.

    The key threads of my research methodology are (a) an operator-theoretic approach to build an analytically tractable representation of environments; and (b) selective loss of details via compression to control model complexity.

    • B. Hou, S. Sanjari, A. Koppel, S. Bose, “Compressed Online Learning of Conditional Mean Embedding”. download

    • B. Hou, S. Sanjari, N. Dahlin, S. Bose, U. Vaidya, “Sparse Learning of Dynamical Systems in Reproducing Kernel Hilbert Space: An Operator-Theoretic Approach”, in Proceedings of the Fortieth International Conference on Machine Learning (ICML), 2023. download

    • B. Hou, S. Sanjari, N. Dahlin, S. Bose, “Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Space”, in Proceedings of the 37th Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence, 2023. download

    • A.Reddy Ramapuram Matavalam, B. Hou, H.Choi, S.Bose, U.Vaidya, “Data-Driven Transient Stability Analysis Using the Koopman Operator” (Please email me for preprint)

    • B. Hou, A.Reddy Ramapuram Matavalam, S.Bose, U.Vaidya, “Propagating Uncertainty Through System Dynamics in Reproducing Kernel Hilbert Space “, to appear at Physica D: Nonlinear Phenomena. Special issue: Topics at the Interface of Machine Learning and Dynamical Systems, 2024. download

      Also presented as a poster paper at the American Control Conference (ACC) 2023.

    • B. Hou, S. Bose and U. Vaidya, “Sparse Learning of Kernel Transfer Operators”, in Proceedings of the Asilomar Conference on Signals, Systems, and Computers, 2021. download

  • Preparing Electrified Transportation:

    Electrification can help to reduce the carbon footprint of aviation. The transition away from the jet fuel-powered airplane towards battery-powered electrified aircraft will impose extra charging requirements on airports. In order to handle the impending electrification of commercial aviation, I study the interdependency of transportation (airlines) and the energy infrastructure at airports.

    • B. Hou, S. Bose, L. Marla and K. Haran, “Impact of Aviation Electrification on Airports: Flight Scheduling and Charging”, IEEE Transactions on Intelligent Transportation Systems. download

    • B. Hou, S. Bose, and K. Haran, “Powering Electric Aircraft at O’Hare Airport: A Case Study”, presented at the IEEE Power and Energy Society General Meeting, 2020.


  • Rising Stars in EECS, 2023
  • M.A.Pai Scholarship, 2023
  • Mavis Future Faculty Fellows (MF3), 2023-2024
  • AAAI Student Scholarship, 2023
  • The second-place winner in the United States Association for Energy Economics (USAEE) Case Competition, 2019.
  • UCLA Cross-disciplinary Scholars in Science and Technology (CSST) Scholarship, 2017


Fall 2021, Teaching Assistant, ECE 365 Data Science and Engineering, UIUC.


Outside of mathematics and engineering, I pursue my passion for dancing. I performed contemporary ballet and dance of the Han-Tang dynasties (a subcategory of Classical Chinese Dance) with Champaign Park District and Zhejiang Wenqin Art Troupe.