Scholar
Priyank Jaini
Google Scholar ID: keg9BGEAAAAJ
Google DeepMind
Citations & Impact
Citations
1,596
H-index
15
i10-index
20
Publications
20
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers including 'Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent' (NeurIPS 2021), 'Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions' (NeurIPS 2021), etc. Served on the program committee for ICML 2021, NeurIPS 2021, and others.
Research Experience
- Currently a Research Scientist at Google DeepMind; Previously a post-doctoral researcher hosted by Max Welling at the University of Amsterdam (AMLAB and UvA-Bosch Delta Lab).
Education
- PhD from the University of Waterloo and Vector Institute, supervised by Pascal Poupart and Yaoliang Yu; Undergraduate from IIT-Kanpur, majoring in Mathematics and Statistics.
Background
- Research interests include multimodal models, building memory systems for multimodal models, understanding, and measuring capabilities of generative models.
Miscellany
- Hosts weekly office hours on Monday through the ML Collective initiative to discuss career directions, industry job market, graduate school, or research.
