Research & Publications
My main research interest lies in mathematics and foundations of data science and machine learning, exploring everything from classical statistics to modern sampling and deep learning theory. More specifically, I am especially interested in:
- Machine Learning Theory
- Optimization in Machine Learning
- Online Learning & RL Theory
- Deep Learning Theory
I have also previously worked on projects in optimization, differential privacy, number theory, and audio processing. Currently, I am trying to explore more of the topics I mentioned above. Beyond my primary focus, I also enjoy working on problems in classical statistics, number theory, theoretical computer science, combinatorics, and discrete geometry that I find interesting.
You can also find my publications on my Google Scholar profile.
If you are interested in collaborating, I’d love to hear from you -- reach out at viverson@uwaterloo.ca!
Publications & Manuscripts
Talks
I am deeply grateful to my mentors, collaborators, and friends who have profoundly shaped my path as a researcher. I extend particular gratitude to Xiaoheng Wang for introducing me to math research, Stephen Vavasis and Gautam Kamath for mentoring me and involving me in interesting machine learning theory research, and Argyris Mouzakis for his invaluable mentorship and discussions throughout the year. I am also indebted to Shai Ben-David and Aukosh Jagannath for my interest in this field.