Correlation Clustering / Synthesis Lectures on Data Mining and Knowledge Discovery (PDF)

Discovery in Inductive Databases (KDID 2005). He is co-editor of the book Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques published by Chapman & Hall/CRC Press. He will be General Chair of ECML PKDD 2023 to be held in Turin (Italy), and of ACM SIGKDD 2024, to be held in Barcelona (Spain). David García-Soriano is a Senior Research Scientist at the Institute for Scientific Interchange (ISI) in Turin, in the "Algorithmic Data Analytics" group. Previously, he received his Ph.D. in Computer Science (2012) from the University of Amsterdam and his undergraduate degrees in Computer Science (2007) and Mathematics (2009) from the Complutense University of Madrid. He has been a member of the Algorithms and Complexity group at CWI Amsterdam (the Dutch National Research Center for Mathematics and Computer Science), and a research visitor at the Israel Institute of Technology in Haifa (Technion). Later, he was a postdoctoral researcher at Yahoo Labs Barcelona and aLecturer in Computer Science at Pompeu Fabra University. He has also worked for industry as a software engineer at Google, CERN (the European Organization for Nuclear Research), and Tuenti. In recent years, he has been developing machine-learning and optimization-based solutions to financial portfolio management problems, in collaboration with Intesa San Paolo banking group. His research focuses on the theory and practice of large-scale data mining and machine learning, with an emphasis on computational efficiency and provable quality guarantees; topics include algorithmic theory, combinatorial optimization, scalable machine learning, data mining, algorithmic fairness, social network analysis, data streams, and portfolio optimization. His research findings have been published in top-tier conferences (SODA, KDD, SIGMOD, ICALP, CCC, ICDM, WWW, ICDE, RANDOM, ECML/PKDD, SDM, ...) and journals (SIAM Journal on Computing, Combinatorica, Data Mining and Knowledge Discovery, ...). Francesco Gullois a senior researcher at the UniCredit banking group, specifically in the "Applied Research & Innovation" unit of the "AI, Data & Analytics ICT" department (UniCredit Services controlled company). Previously, he has been part of the "Research & Development" department (UniCredit holding company) for 5 years. He received his Ph.D., in "Computer and Systems Engineering," from the University of Calabria, Italy, in 2010. During his Ph.D., he was an intern at the George Mason University, U.S. After his graduation, he spent 1.5 years in the University of Calabria, Italy (as a postdoc), and 4 years in the Yahoo Labs, Spain (as a postdoc first, and as a research scientist then). His research falls into the broad areas of artificial intelligence and data science, with special emphasis on algorithmic aspects. His recent interests include mining and learning on graphs, natural language processing, and AI in finance. He has been practicing both applied research (with a 10-year work experience in industrial-research environments), and fundamental research (with 80 publications in premier venues such as SIGMOD, VLDB, KDD, ICDM, CIKM, EDBT, WSDM, ECML-PKDD, SDM, TODS, TKDE, TKDD, MACH, DAMI, TNSE, JCSS, PR). He has also been serving the scientific community, by, e.g., being Workshop Chair of ICDM'16, organizing workshops/symposia (MIDAS workshop @ECML-PKDD['16-'21], MultiClust symposium @SDM'14, MultiClust workshop @KDD'13, 3Clust workshop @PAKDD'12), or being part of the program committee of major AI/data-science conferences (e.g., SIGMOD, KDD, WWW, IJCAI, AAAI, CIKM, SIGIR, ICDM, WSDM, SDM,ECML-PKDD, ICWSM).