About me

I am a Ph.D student in Stevens Institute of Technology under the supervison of Prof.K.P.(Suba)Subbalakshmi. I also obtained a M.S degree in Applied Artificial Intelligence at Stevens Institute of Technology. Before that I received my M.S degree in Multimedia Telecommunication at University of Liverpool and was a member of LCCAT Lab, directed by Prof.Qiufeng Wang and Prof.Kaizhu Huang. I received my B.Eng degree in Department of Electrical Engineering & Electronics at Xi’an Jiaotong-Liverpool University.

In General, I’m interested in Natural Language Processing, Multimodal and Deep Learning. Specially, I have the research/project experience in Misinformation Detection, Mental Healthcare, Generative Model for Tabular Data, Scene text classification and recognition.


  • Stevens Institute of Technology, 2021 - 2025 (expected)
    • Ph.D in Computer Engineering
  • Stevens Institute of Technology, 2019 - 2021
    • M.S. in Applied Artifical Intelligence
  • University of Liverpool, 2017 - 2019
    • M.S. in Multimedia Telecommunication (Merit)
  • Xi’an Jiaotong-Liverpool University, 2013 - 2017
    • B.Eng. (Honours) in Telecommunication Engineering


  • Provost Doctoral Fellowship Award, 2021-2025
  • Best Master Thesis Award, 2021.5
  • ECE 2020 Honours Summer Research Program 3rd Award, 2020.8

Professional Experience

Selected Publications

  • Causal-TGAN: Modeling Tabular Data Using Causally-Aware GAN
    B Wen, Y Cao, F Yang, K Subbalakshmi, R Chandramouli
    ICLR 2022 Workshop on Deep Generative Models for Highly Structured Data

  • Modular Multi-Modal Attention Network for Alzheimer’s Disease Detection Using Patient Audio and Language Data
    N Wang, Y Cao, S Hao, Z Shao, KP Subbalakshmi
    Interspeech 2021, 3835-3839

  • Improving script identification by intergating text recognition information
    Y Cao, J Li, QF Wang, K Huang, R Zhang
    26th International Conference on Neural Information Processing.


  • Languages
    • Mandarin (Native), English (Fluent)
  • Programming Language
    • Python, C/C++, CUDA C/C++, Assembly, MATLAB
  • Deep Learning Framework
    • PyTorch = Keras > Tensorflow2.x > Tensorflow1.x > Caffee
  • Tools
    • Linux, LaTeX, Git, Vim, Shell