Zoltan Szabo is a Professor of Data Science at the Department of Statistics, LSE. Zoltan's research interest is statistical machine learning with focus on kernel methods, information theory (ITE, https://bitbucket.org/szzoli/ite-in-python), scalable computation, and their applications. These applications include safety-critical learning, style transfer, shape-constrained prediction, hypothesis testing, distribution regression, dictionary learning, structured sparsity, independent subspace analysis and its extensions, Bayesian inference, finance, economics, analysis of climate data, criminal data analysis, collaborative filtering, emotion recognition, face tracking, remote sensing, natural language processing, and gene analysis.

Zoltan enjoys helping and interacting with the machine learning (ML) and statistics community in various forms. He serves/served as (i) a Senior Area Chair/an Area Chair of the most prestigious ML conferences including ICML, NeurIPS, COLT, AISTATS, UAI, IJCAI, ICLR, (ii) the moderator of statistical machine learning (stat.ML) on arXiv, (iii) the Programme Director of MSc Data Science, (iv) an editorial board member of JMLR, a senior associate editor of the journal ACM Transactions on Probabilistic Machine Learning, and an associate editor of the journal Mathematical Foundations of Computing, (v) a reviewer of European (ERC), Israeli (ISF) and Swiss (SNSF) grant applications, (vi) a mentor of newcomers (NeurIPS, ICML).