Scholar
Yaniv Romano
Google Scholar ID: L_m67ywAAAAJ
Associate Professor of Electrical Engineering and Computer Science, Technion, Israel
Citations & Impact
Citations
5,035
H-index
30
i10-index
41
Publications
20
Co-authors
44
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Co-inventor of the CQR uncertainty estimation method, which was used by The Washington Post to estimate outstanding votes for the 2020 U.S. presidential election. Co-inventor of the RAISR super-resolution technology, which is being used in Google's flagship products, increasing the quality of billions of images and bringing significant bandwidth savings. Received multiple fellowships and grants, including support from ERC (SafetyBounds Project), Israel Science Foundation, Verily Life Sciences, Citi Bank, and The Technion Center for ML and Intelligent Systems.
Research Experience
- Currently an associate professor in the Departments of Electrical Engineering and Computer Science at the Technion—Israel Institute of Technology. Previously a postdoctoral scholar in the Department of Statistics at Stanford University. Research areas include predictive inference, statistical inference, robustness, etc.
Education
- Ph.D. and M.Sc. degrees: 2017, Department of Electrical Engineering, Technion—Israel Institute of Technology, supervised by Prof. Michael Elad; Postdoctoral scholar: Department of Statistics, Stanford University, advised by Prof. Emmanuel Candès; B.Sc. degree: 2012, Department of Electrical Engineering, Technion—Israel Institute of Technology.
Background
- Research interests include the reliable deployment of modern machine learning models, particularly in high-stakes applications. Main work directions include developing protective ecosystems to provide formal statistical guarantees and designing new learning paradigms grounded in fundamental statistical principles.
Miscellany
- Personal interests and other information not mentioned.
