Scholar
Erik B. Sudderth
Google Scholar ID: ePiPQ2cAAAAJ
Professor of Computer Science, UC Irvine
Citations & Impact
Citations
2,079
H-index
27
i10-index
43
Publications
20
Co-authors
41
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published new variational inference algorithms for image inpainting and superresolution; presented work on stable training of differentiable particle smoothers at NeurIPS 2024; received best poster award at ICML 2021 Time Series Workshop; NSF CAREER Award for BNPy development; proposed a prediction-constrained training framework at AISTATS 2018, winning the SoCal NLP Symposium best paper award.
Research Experience
- Director of the UCI Center for Machine Learning and Intelligent Systems, HPI Research Center in Machine Learning and Data Science at UC Irvine, and other research affiliations; involved in BrainGate project to improve brain-computer interfaces; developed BNPy, a Python toolbox for Bayesian nonparametric clustering.
Education
- Ph.D. from MIT EECS, advised by Professors Alan Willsky and William Freeman; Postdoctoral research at Berkeley EECS, advised by Professors Michael Jordan and Stuart Russell.
Background
- Professor of Computer Science and Statistics at the University of California, Irvine, with research interests in statistical methods for scalable machine learning and applications in AI, computer vision, and natural and social sciences.
Miscellany
- No personal interests or additional information provided in the HTML content.
