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World Conference on Data Science & Statistics (Data Science Week 2023) slated in Frankfurt from 26th to 28th June, 2023 with the theme “Understanding the Data Science: Can help now and in the Future”.
Data Science Week 2023 will provide a universally unique forum for extant work that develops computational methods, statistical, and mathematical in the field of data sciences. This Meeting aims to bring together data scientists, analysts, visualizers, statisticians, mathematicians, researchers who are building fundamentals for data science and its applications across science, engineering, technology, and society. Data Science Week 2023 is an inclusive and totally academics and industry-focused meeting and it’s the conference to engage, build, develop, and learn from the whole data science leaders and experts. It would set up a high standard for its organizing committees, keynote speakers, plenary speakers and session presenters, and a competitive rate for poster presenters.
The conference platform will provide you with many opportunities for online networking and discussion in smaller groups. You’ll be able to share your opinions directly with other attendees and with the speakers.
The conference brought together academics and practitioners in areas including data science, machine learning, artificial intelligence, computational statistics and software, as applied in the Biotech & Pharma, Communications, Cyber & Fraud, Education, Energy, Travel, and many more industry.
Our Conference agenda will offer answers and practical advice that you can take back to your workplace to build mature data practices and strategies for DevOps & CI/CD, cloud, data compliance, AI/ML, and more.
Data Science Week 2023 is an annual academic and business gathering with the Data Science peers at a single platform to discuss ways of enabling faster Innovation and deployment across the enterprise by setting up modern Data Science strategies. With renowned international speakers, presenting across three days, roundtable discussions, and plenty of other learning and networking activities, the Data Science Week 2023 is the place for all CDOs and data practitioners working with Machine learning, Artificial Intelligence, Robotics, Data Governance, Data Management, Data Quality, Enterprise Architecture, and DataOps. This global Conference is where executives and business professionals meet the best and brightest innovators in AI, ML, and Data Science.
The conference will facilitate the young researchers, industries leaders, and research agencies especially, those, who are functioning their research work in the data science domain of Computer Science, Information Technology, Healthcare, Finance, Electronics, and Communication Engineering with valuable deliberations in order to make the results more representative. The program is divided into three days, each day focusing on a specific topic, and contributions to this colloquium will also present practice-oriented research as well as research on teachers’ professional development.
Business executives:
VPs, heads, and leaders from the following industries: healthcare, education, finance, insurance, biotechnology/pharmaceuticals, manufacturing, retail, media & marketing, energy & utilities, government, transportation, and e-commerce.
Chiefs and Heads of: A chief or head of the following departments: Data, Data Science, Technology, Information, Analytics, Strategy, Innovation, Marketing, etc.
Innovators such as: Innovators include entrepreneurs, investors, VCs, apostle & Decision-makers, and Strategy Executives.
Researchers and Scientist: Professors, lectures, scientists, post-doctorate, students
University of Technology of Troyes, France
Prof. Hichem Snoussi received the diploma degree in Electrical Engineering from the Ecole Supérieure d'Electricité (Supélec), Gif-sur-Yvette, France, in 2000. He also received the DEA degree and the Ph.D. in signal processing from the University of Paris-Sud, Orsay, France, in 2000 and 2003 respectively. Between 2003 and 2004, he was postdoctoral researcher at IRCCyN, Institut de Recherches en Communications et Cybernétiques de Nantes. He has spent short periods as visiting scientist at the Brain Science Institute, RIKEN, Japan and Olin Neuropsychiatry Research Center at the Institute of Living in USA. Between 2005 and 2009, he was associate professor at the 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).
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.
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.
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.
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.
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" (concentration in Statistics and Operational Research), 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. He has research publications in scientific journals and conferences, his scientific interests are mainly in the areas of time series and forecasting, applied statistics, and applied econometrics.
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.
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.
Alpen Adria Universität Klagenfurt- Institute of Statistics, Austria
Professor Jürgen Pilz supervises Ph.D. students and postdoctoral researchers and teaches courses on statistics and data science. In 1988, he received his DSc from Germany. His major areas of interest include Bayesian Statistics, Spatial Statistics, Design of Experiments, Bayesian Epidemiology, and Bayesian Statistical Learning. Over 180 publications have been published in international journals and conference proceedings by him. Author of 8 books published by renowned publishers such as Wiley, Springer, Elsevier, Chapman & Hall from 2007-2015. Former Head of the Department of Applied Statistics at Alpen Adria University Klagenfurt - Emeritus Professor since October 1, 2020 - elected member of the International Statistical Institute (ISI) and the Institute of Mathematical Statistics (IMS) - on editorial boards of several international statistics journals.
Weserstraße 43, 60329 Frankfurt am Main, Germany
Name: Ms. Santona
Phone: +44 1442 781 082
Email: datascience@thepeopleevents.com
Reception manned 24 hours a day
Reception manned at weekends
Check-In : 15:00
Check-Out : 12:00
Hilton Garden Inn Frankfurt City Centre puts you 4.1 mi (6.7 km) from Deutsche Bank Park. The property is just a short walk to public transportation: Central Station Tram Stop is 7 minutes and Taunusanlage S-Bahn is 7 minutes.
Getting Around
Conference starts will some guest talk followed by Keynote speeches by several renowned personalities.
The topics for this session, will be: Data Science & Technology and AI & Machine Learning
Here, discussion would be on Public Policy and Big Data & Analytics
Presentation topics: Advanced Analytics and Databases & Data Security
Day 2 starts with Keynote presentation from eminent people in the field of Climate Change and other related fields.
Technologies in Data Visualization and Computational Science & Numerical Analysis
Neuromorphic Computing
Cloud Computing
Day 3 Starts with 5-7 Keynote Talks from multinational speakers.
Mathematical Aspects of Data Science and Deep Learning
Statistical Learning and The Best of Predictive Analytics
Business Intelligence and Digital Transformation
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Reserve your seat while they last. We have a limited number available.
