Alexander Borusan

Technische Universitaet Berlin, Germany

Dr. Alexander Borusan is Deputy Operations of the Database Systems and Information Management group at the Technische Universität Berlin. His research interests include data streams management. Prior to his work in Berlin, he worked at the Kiev Polytechnical Institute and as a visiting professor in the department of computer science at the University of Hamburg. Alexander worked in various national and international research projects and in projects on behalf of industry in the Ukraine, USA, France, and Germany. He is currently the member of the Management Team of BIFOLD, the Berlin Institute for the Foundations of Learning and Data.

Hichem Snoussi

University of Technology of Troyes, France

He has obtained the HDR degree from the University of Technology of Compiègne in 2009. Since 2010, he is Full Professor at the University of Technology of Troyes. His research interests include Bayesian techniques for source separation, information geometry, differential geometry, machine learning,etc. Since 2010, he has been in charge of the CapSec Plateform (Sensors for Security). He is the principal investigator of many research projects and industrial partnerships. Between 2016 and 2020, he has been manager of LM2S Lab in Charles Delaunay Institute. Since 2021, he is deputy director of LIST3N lab and team leader of M2S group. He co-founded 2 start-up: Aquilae (IA for videosurveillance) and Damavan Imaging (Compton cameras for nuclear inspection).

Chinmaya Dehury

University of Tartu, Estonia

Chinmaya Kumar Dehury is an Assistant Professor of Distributed Systems at Mobile & Cloud Lab, Institute of Computer Science, University of Tartu, Estonia. He completed his Ph.D. in Computer Science and Information Engineering from Chang Gung University, Taiwan. He has attended many international meetings and was invited to talk at workshops and conferences. His research interest varies from Artificial Intelligence Technologies and Applications. He has been a Technical Committee Member in 2021 and is currently a PC member in ACS/IEEE,2022.

Chong Leong Gan

Micron Technology, Inc., United States

Dr. Chong Leong, Gan received a B.S. degree in Chemical Engineering from the National University of Malaysia in 2000, an M.S. degree in Chemical Instrumentation in 2003 from the University of Science Malaysia, and a Ph.D. in Nanoelectronic Engineering from the University Malaysia Perlis in 2015. Since 2006, he has been a Quality and Reliability Member of Technical Staff with Altera Corporation, Senior R&D Engineering Manager with Western Digital Inc, and recently as Package Characterization Director with Micron Technology Inc.

Giancarlo Cobino

Qvantia, Italy

10+ years of experience in Data Science projects, from machine learning to Artificial intelligence, applied to real-world problems. Development and implementation of customers profiling, recommender systems and Churn algorithms. Extensive experience in managing heterogeneous teams of Software Developers, DevOps, data scientists, Sales and Marketing. Recently served as global leader of ML and MLOps for NTT DATA, he’s now CTO of Qvantia (https://qvantia.com), a unified ML and AI platform, and founder of Huok (https://huok.tech), a consultancy firm helping enterprises to adopt Artificial Intelligence.

Danilo Bruno

NTT Data, Italy

Danilo Bruno is Head of AWS Data & Analytics & Global DataOps at NTT DATA Italia. He completed his graduation with a Master of Computer Engineering, from the Sapienza University of Rome. He has a background of  working in an IT company where he was a Designer and developer of architectures of Big Data Analytics, with the development of different DBRMS & data sources, ETL Development, system support, and development in SAS. Development and configuration of various Hadoop components: Pig, Sqoop, Flume, Hive, Impala, Kafka, Oozie, Spark.

Christos Katris

University of Patras, Greece

Christos Katris is an Adjunct Lecturer at the Department of Mechanical Engineering and Aeronautics at the University of Patras and a Customs Officer (Statistician) at the Independent Authority of Public Revenue (I.A.P.R.-A.A.D.E.), Greece. He was a Postdoctoral Researcher at the Department of Accounting and Finance, Athens University of Economics and Business, and has worked as a Statistician/Econometrician in Alma Economics, as a Statistical Analyst at the Quality Assurance Unit (MO.DI.P.) of the University of Patras, and as Statistical Researcher in projects from the University of Patras and from the Athens University of Economics and Business. He holds Degrees in Statistics and Economics, a Master’s Degree in “Computer Mathematics and Decisions” and a Ph.D. (entitled “Stochastic Models for Data Analysis on the Internet”, from the University of Patras in the research area of Applied Statistics. His scientific interests are mainly in time series and forecasting, applied statistics, and applied econometrics.

Alessandro Bonaita

Generali Corporate Pension Fund, Italy

Alessandro Bonaita is Group Head of Data Science at Generali Group, one of the largest global insurance and asset management providers, where he is responsible for developing the adoption of artificial intelligence in more than 50 countries. Previously Head of Analytics at American Express and RCS Mediagroup, where he also served as Deputy Privacy Officer, in the last years he focused his attention on the ethical and legal implications of AI, its responsible and sustainable adoption, and the related organizational impacts, becoming an advisor for several institutions and research centers, including Stanford University and the European insurance and reinsurance federation.

Gianpaolo Di Bona

University of Cassino, Italy

Gianpaolo Di Bona is an Associate Professor at the University of Cassino. He earned a Ph.D. in Civil and Mechanical Engineering from the University of Cassino, and a Master’s Degree in Civil Engineering from the University of Rome “La Sapienza”. He has been involved – as a team member and, more recently, as a scientific coordinator – in research projects of national and international importance. These projects are in the areas of Manufacturing, Quality Management and Operations Improvement, and Supply Chain Management. Since 2017, he has served on many international committees, as a member of editorial boards, and as a reviewer. Over 70 publications in relevant journals, scientific conferences, and books.

Jürgen Pilz

Alpen Adria Universität Klagenfurt- Institute of Statistics, Austria

Jürgen Pilz is Emeritus Professor at the Department of Statistics, Alpen Adria University (AAU) of Klagenfurt, Austria. He received his Ph.D. and DSc degrees from TU Mining Academy Freiberg, Germany. From 1994 – 2020 he was Professor and Chair of Applied Statistics at AAU Klagenfurt, Austria, from 2007-2015 and 2018-2019 he served as (Founding) Head of the Dept. of Statistics at AAU Klagenfurt. He held guest professorships at Charles University Prague (Czech Rep.), University of Augsburg (Germany), Purdue University (USA), University of British Columbia, Vancouver (Canada), and the University of Canterbury, Christchurch (New Zealand).

His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. He has published over 200 papers in international journals and conference proceedings. He has supervised more than 80 Master theses and 40 Ph.D. theses. He is the author of seven books from renowned publishers including Wiley, Springer, Chapman & Hall, the latest one being „Applied Statistics – Theory and Problem Solutions with R“ published by J. Wiley and Sons, Oxford 2020. He is an elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS), and on editorial boards of several international statistics journals.

Jürgen Pilz is Emeritus Professor at the Department of Statistics, Alpen Adria University (AAU) of Klagenfurt, Austria. He received his Ph.D. and DSc degrees from TU Mining Academy Freiberg, Germany. From 1994 – 2020 he was Professor and Chair of Applied Statistics at AAU Klagenfurt, Austria, from 2007-2015 and 2018-2019 he served as (Founding) Head of the Dept. of Statistics at AAU Klagenfurt. He held guest professorships at Charles University Prague (Czech Rep.), University of Augsburg (Germany), Purdue University (USA), University of British Columbia, Vancouver (Canada), and the University of Canterbury, Christchurch (New Zealand).

His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. He has published over 200 papers in international journals and conference proceedings. He has supervised more than 80 Master theses and 40 Ph.D. theses. He is the author of seven books from renowned publishers including Wiley, Springer, Chapman & Hall, the latest one being „Applied Statistics – Theory and Problem Solutions with R“ published by J. Wiley and Sons, Oxford 2020. He is an elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS), and on editorial boards of several international statistics journals.

Mike Williamson

Tradeshift, Denmark

Mike Williamson is the director of machine learning and data engineering at Tradeshift. Prior to Tradeshift, Mike worked at companies of all sizes, primarily in Silicon Valley, now living in the greater Copenhagen region. He began his career in semiconductor manufacturing and came to love the capability of statistics to deliver experimental success with less effort and cost. He made the jump to data science shortly thereafter, primarily working in SaaS companies. He focused on the “productionizing” of machine learning, elements such as MLOps, Infrastructure as Code, and CI/CD. Mike spent most of his career as an individual contributor, but has spent the last several years as an ML architect, professor, and currently as director of the ML and data engineering team at Tradeshift.

Eric Peukert

ScaDS.AI, Leipzig University, Germany

Dr. Eric Peukert is the Administration Director of the National Data Science Center ScaDS.AI. He studied Media Informatics at the Dresden University of Technology and received a Ph.D. in SAP Research in the field of data integration within various BMBF and EU research projects. After completing his doctorate and two more years in at SAP, Mr. Peukert moved to ScaDS at the University of Leipzig. Mr. Peukert coordinates the AI center’s research activities with a special focus on industry cooperation and gives lectures at the University of Leipzig on big data and cloud data management. His research focuses on big data technologies, graph-based analysis, data integration, and machine learning-based methods.

Willi Sauerbrei

Medical Center - University of Freiburg, Germany

Dr. Sauerbrei is a senior statistician and professor in medical biometry. Since 1983, he has worked as an academic biostatistician with a main interest in various issues of model building and in cancer research. For 16 years, he was the head of a Clinical Trials Unit. With Patrick Royston, he has developed the multivariable fractional polynomial approach (MFP) and its extensions of it. Methodological topics of interest include variable and function selection, model stability, treatment covariate interactions, meta-analysis, reporting of research findings, and high-dimensional data. He is the initiator and chair of the STRATOS (STRengthening Analytical Thinking for Observational Studies).

Scientific Committee Operator Event Reviewer

 

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Rajsekhar works for Apple as an Engineering Manager for Data Platform and ML Infra focused on providing Lake House solutions for Machine Learning and Data Engineering use cases. Raj has over 18 years of experience in data space. One of the founding engineering members responsible for building large scale, multi-cloud and secure data/ML infrastructure at Apple. The platform runs at PB scale, over a trillion events ingestion daily. Adopters of open source technologies and responsible for designing, implementing and automating the managed services to deploy in various accounts.