Zé Vinícius

Sai Kung, 2022

Hong Kong, China

Hi there! I’m Zé Vinícius, a PhD candidate at HKUST, in sunny Hong Kong, working with Prof. Daniel Palomar on research problems involving graphs and financial time series. I design optimization algorithms using elements of graph theory and statistical learning theory to extract knowledge from networks of financial assets.

I have done a few internships along the way:

I spend most of my time doing research and coding. I also act as a reviewer for NeurIPS, ICML, ICLR, JMLR, and IEEE TNNLS. In my free time, there is nothing better than swimming and crab hunting in the waters of Clear Water Bay and video-chatting with my nephew Chico and my dog Pluto.

selected publications

  1. NeurIPS
    Learning Bipartite Graphs: Heavy Tails and Multiple Components
    Cardoso, J. V. M., Ying, J., and Palomar, D. P.
    In Advances in Neural Information Processing Systems 2022
  2. NeurIPS
    Graphical Models in Heavy-Tailed Markets
    Cardoso, J. V. M., Ying, J., and Palomar, D. P.
    In Advances in Neural Information Processing Systems 2021
  3. NeurIPS
    Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model
    Ying, J., Cardoso, J. V. M., and Palomar, D. P.
    In Advances in Neural Information Processing Systems 2020
  4. NeurIPS
    Structured Graph Learning Via Laplacian Spectral Constraints
    Kumar, S., Ying, J., Cardoso, J. V. M., and Palomar, D. P.
    In Advances in Neural Information Processing Systems 2019