Scholar
Borja Balle
Google Scholar ID: xa-6ZlkAAAAJ
DeepMind
Citations & Impact
Citations
8,828
H-index
32
i10-index
53
Publications
20
Co-authors
66
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers such as 'Differentially Private Diffusion Models Generate Useful Synthetic Images' (2023), 'Tight Auditing of Differentially Private Machine Learning' (2023), and participated in various projects, for example, 'Reconstructing Training Data with Informed Adversaries' presented at IEEE Symposium on Security and Privacy (S&P) 2022.
Research Experience
- Senior machine learning scientist in Neil Lawrence's team at Amazon (Cambridge, UK) from April 2017 until May 2019; before that, a lecturer affiliated with the Department of Mathematics and Statistics and the Data Science Institute at Lancaster University; post-doctoral fellow in the Reasoning and Learning Laboratory at McGill University, working with Prakash Panangaden, Joelle Pineau, and Doina Precup from October 2013 to September 2015.
Education
- Obtained PhD in 2013 from UPC, working in the LARCA research group under the supervision of Jorge Castro and Ricard Gavaldà. During his PhD, he spent several months visiting Mehryar Mohri at the Courant Institute (NYU).
Background
- Research interests revolve around all aspects of Machine Learning: theory, algorithms, and applications. Currently focusing on the foundations of privacy-preserving data analysis, including Differential Privacy and Private Multi-Party Machine Learning.
