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:
- equity quant at Merrill Lynch: wrote code for portfolio risk optimization and limit order book forecasting;
- research scientist at Shell Street Labs: wrote code for portfolio strategy optimization;
- scientific software engineer at NASA: wrote code for lightkurve;
- Google Summer of Code developer for OpenAstronomy: improved the point spread function photometry capabilities of photutils;
- guest researcher at NIST: research on nanophotonics published in Nature and Review of Scientific Instruments;
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.
- NeurIPSLearning Bipartite Graphs: Heavy Tails and Multiple ComponentsIn Advances in Neural Information Processing Systems 2022
- NeurIPSGraphical Models in Heavy-Tailed MarketsIn Advances in Neural Information Processing Systems 2021
- NeurIPSNonconvex Sparse Graph Learning under Laplacian Constrained Graphical ModelIn Advances in Neural Information Processing Systems 2020
- NeurIPSStructured Graph Learning Via Laplacian Spectral ConstraintsIn Advances in Neural Information Processing Systems 2019