Scholar
Geoffrey Roeder
Google Scholar ID: sIfE5HIAAAAJ
Princeton University
Citations & Impact
Citations
751
H-index
10
i10-index
10
Publications
14
Co-authors
0
Publications
Resume (English only)
Research Experience
- Fall 2017: Worked with Ferenc Huszár on improving black-box optimization methods for general non-differentiable functions.
- Summer 2018: Intern at Microsoft Research Cambridge, collaborated on a novel class of deep generative models for understanding and programming information processing in biological systems.
- Summer 2019: Intern at Google Brain, collaborated with Durk Kingma on identifiable representation learning by deep discriminative models.
- Fall 2019: Joined X, the Moonshot Factory (formerly Google X) as a Resident in core ML.
- Since February 2020: 20%-time Resident with the Quantum/AI group at X, working on Bayesian inference for noisy intermediate-scale quantum algorithms.
Background
- Research interests include statistical machine learning, theory of deep generative models and their applications in scientific discovery and engineering design. Aiming to advance theoretical understanding of deep learning supporting robustness, reliability, and efficient inference.
Co-authors