Research Spotlight

Hi! I am a Mathematician, Postdoc and research software developer @ Concordia University, School of Engineering and Computer Science. I am currently working on network simulation and a Bayesian PDE approach to explainable deep learning . I completed my last postdoc in computer social media, FEIT, UTS. I built dependence structure between labor occupation based on job counts data, using copulae. I also developed a theoretical model based on hawkes intensity point processes allows fitting information diffusion based on observed counts of events. The main tools we used were functional analysis and distribution theory. I completed my PhD in early 2018 on the topic of stochastic Navier-Stokes equations on the rotating spheres with stable Lévy noise, under supervision of Prof. Beniamin Goldys, the univeristy of Sydney. I have been teaching in universities on various topics for roughly 10 years. Prior to my PhD, I was a researcher in quantitative finance and stochastic processes.

Research interests:

  • Graph theory and algorithms

  • Physical informed Deep Learning

  • C++ programming for scientific computing

  • Explainable AI (XAI), Intepretable Machine Learning

  • Probablistic programming/inferencing

  • Mathematical Analysis of Artificial Intelligence and Theoretical Computer Science

  • Theoretical or Statistical Machine Learning

  • Stochastic PDEs, Financial Mathematics

Side Interests

  • Quantum Computing, Quantum game theory, Information Geometry, Quantum Machine Learning

  • Point processes and applications to Social Media, Finance, Insurance, Quantum Physics