Συνέδρια, Ημερίδες, Ομιλίες, Διαλέξεις Διακεκριμένων Ομιλητών

ΑΙ@AUEB talk, Friday 10 November, 16:15-17:45 (Greek time)

Speaker: Ion Androutsopoulos (https://www.aueb.gr/users/ion/)

Title: "An Introduction to Deep Learning for Natural Language Processing -- from word embeddings to ChatGPT"

Room: T203, Troias building (2 Troias St.) and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1698736417858?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

Abstract:
Like most areas of Artificial Intelligence (AI), Natural Language Processing (NLP) has been transformed by Deep Learning and has produced impressive results, most recently with systems based on large language models, like ChatGPT. This talk will provide a gentle introduction to key concepts of modern NLP, including word embeddings, Recurrent Neural Networks (RNNs), Transformers, encoder-decoder models. It will also provide examples of applications, such as information extraction from documents, filtering toxic posts on social media, legal judgment prediction, machine translation, image captioning, and code generation.

This will be a slightly extended English version of a talk given in Greek to the HIAS Universal AI summer school (Greek video available at https://www.youtube.com/@hellenic-ias/streams -- day 3, 4:05:00 to 5:12:00).

To subscribe to the mailing list of AI@AUEB, send a message (with any subject and body) to ai_meetings-subscribe@lists.aueb.gr. If you have an AUEB account and want to view all scheduled AI @ AUEB Lecture Series in your MS Teams calendar, subscribe to the "AI@AUEB" group on MS Teams (code: r2dtl45). Team members can also send text messages (chat) to other team members.

If you are an AI researcher or practitioner, please consider becoming a member of the Hellenic Artificial Intelligence Society (EETN, http://www.eetn.gr/en/).

Advanced Analytics for Data Science – Blended Intensive Programme (BIP)

September 5-15, October 2 and 20, 2023

Naples, Italy

Τhe Department of Statistics, Athens University of Economics and Business actively participates in the “Advanced Analytics for Data Science – Blended Intensive Programme (BIP)”, not only with a total of 6 students attending the course, but also with Professors of the Department giving lectures, in some of the face-to-face sessions of the course.

The training course aims to provide participants with a detailed overview of methodologies and technologies of modern parametric and non-parametric data analysis procedures, serving as a reference point on data science and advanced statistical analysis for researchers, decision-makers and application developers.

A comprehensive view of Data Science will be presented, from the management of datasets, to the presentation and visualization of results via interactive Dashboards, whilst potential real-world application domains from corporate data, health, and IT security data will be discussed and summarized, with stakeholders and professionals from the corporate world recounting their experiences with the participants.

For more information, please refer to: https://www.labstat.it/bip23/

AUEB Conference on Statistical Data Science, 6th-8th September 2023, Aegina

The Summit aims at promoting gender-equal access to the computer-related scientific frontiers, encouraging and educating women and men in an equal way to achieve their goals and utilize their potential in digital professions.

The goal of the Summit is also to celebrate and disseminate the achievements of computer professionals in a fair and gender-equal way.

Τhe Summit brings together students, researchers, and professionals in the field of Computer Science to:

• Present and share their achievements and experience in the computing field
• Discuss and understand the reasons why there is gender disparity in individuals opting for Computer Science and Engineering
• Consider and exchange views on gender stereotyping in Computer Science
• Come up with incentives and measures to reduce gender inequalities in the field

The Summit is organized by The Department of Informatics, Athens University of Economics and Business (AUEB) and the Greek Chapter of the ACM-W (ACM's Council on Women in Computing)

Information: http://gec23.aueb.gr/

Professor Vasilis Vasdekis, Vice Rector of Academic Affairs and Personnel, AUEB

Professor Vana Kalogeraki, Head of Department of Informatics, AUEB

Associate Professor Maria Roussou, Department of Informatics and Telecommunications, UOA

We are pleased to invite you to the International HERMES Ph.D. Workshop 2023: “Data Science in Business”, organized by the Department of Statistics, Athens University of Economics and Business, that will take place in Athens, Greece, on June 7^th and 8^th, 2023, at the premises of the Athens University of Economics and Business.

With topics ranging, from Forensic Science and the Pandemic Economic Crisis, all the way to Deep Learning, Time Series models and High-Resolution Data Analysis, on matters of environmental interest, the Workshop is intended to foster the exchange of ideas and networking among Ph.D. students from various different fields.

The Workshop’s participants also come from a rather diverse background, making this event the perfect opportunity for insightful, multicultural research exchange between: Technische Universität Dresden, Università di Pavia, Università Ca'​ Foscari Venezia, University of Economics in Bratislava, Universidad de Alcalá, Academia de Studii Economice din București, Leopold-Franzens Universität Innsbruck and the Department of Statistics, Athens University of Economics and Business.

The meeting will be characterized by informal discussions and exchange of ideas between participants.

For more information, please refer to the Workshop's official Website: https://lnkd.in/dHwWCqna

The Workshop’s Program may be found here:https://lnkd.in/deiVGwEX

On Monday, May 29, 2023, from 19:00 to 21:00, a seminar on "AI and Tech: Innovation, Opportunities and Risks for Business and Society" will be held by Professor Theodoros Eugeniou, in Room A24 of the main building (76 Patision Street) of the Athens University of Economics and Business.

Dr. Theodoros Eugeniou is a Professor of Decision Sciences and Technology Management at INSEAD Business School in France and Visiting Professor at the Department of Management Science and Technology of AUEB.

The seminar will take place in the English language and is addressed to the postgraduate and doctoral students of the AUEB's programs as well as to the students of the Erasmus program.

To watch the seminar, you need to register at the link: https://forms.gle/B22437N431bf3EWw6

Seminar Description:

«Tech innovations - for example internet and AI based ones - have been the focus of startups, large businesses, investors, and research for a couple of decades, with impressive results. With hindsight, it may come as a surprise that only recently – perhaps the past 5-10 years – we started to also closely consider the potential risks these technologies can create. Regulators are also developing several new requirements for online platforms and for using AI in practice. Technological progress may not only prove risky but also risks slowing down if we do not manage both tech opportunities and risks at the same time. The recent letter of Musk and others to “pause AI progress” testifies to this. How can we balance these? What does it mean for business, society, and potentially even (geo)politics? How can you participate in this unfolding global game as managers or entrepreneurs and create value for yourself, your organizations, your country, and the world?»

Short biography of Speaker:

Dr. Theodoros Eugeniou is Professor of Decision Sciences and Technology Management at INSEAD (France) and Director of the Executive Program "Transforming your Business with AI". He holds four degrees from MIT (BSc in Mathematics and BSc, MSc and PhD in Computer Science).

He has been working in research in the scientific areas of Machine Learning and Artificial Intelligence for the past 25 years, on topics such as artificial intelligence innovations to optimize business processes and improve decision-making in marketing and finance, the institutional framework for artificial intelligence, as well as new methods machine learning.

He has published over 70 scientific articles, several of them in leading scientific journals. He is a Member of the OSA Artificial Intelligence Expert Network, a BCG Henderson Institute Consultant and an Academic Advisor on Artificial Intelligence to the World Economic Forum. He has been awarded twice (2005 and 2007) with the European Case Study Award in the "Knowledge, Information & Communication Systems Management" category.

ΑΙ@AUEB talk, Tuesday 23 May, 16:15-17:30 (hybrid presentation, Greek time)

Speaker: Angelos Alexopoulos (Dept. of Economics, AUEB)

Title: A machine learning and network approach to Value Added Tax fraud detection

Abstract:
Value Added Tax (VAT) fraud erodes tax revenues and puts legitimate businesses at a  disadvantaged position thereby impacting inequality.
Identifying and combating VAT fraud before it occurs is therefore important for welfare. This paper proposes suitably flexible machine learning algorithms for detection of VAT fraudulent transactions. The innovation of the algorithms is in utilising the information provided by their VAT structure. Making use of the universe of Bulgarian VAT data the fraud detection algorithms detect around 50 percent of the VAT fraud and outperform well-known techniques that ignore the  network of VAT transactions. Importantly, the proposed methods are automated, and can be implemented following the taxpayers' submission of their VAT returns, enabling tax revenue authorities, in the EU and elsewhere, to prevent large losses of tax revenues through performing early identification of fraud between business-to-business transactions within the VAT system.
The approach developed can be applied to similar problems where network interactions exist and can be quantified, such as fraud in online transactions, in insurance and social security systems as well as in telecommunication systems.

Room: T105, Troias building

and virtually via MS Teams:
https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1683621333082?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

To subscribe to the mailing list of AI@AUEB, send a message (with any subject and body) to ai_meetings-subscribe@lists.aueb.gr. If you have an AUEB account and want to view all scheduled AI @ AUEB Lecture Series in your MS Teams calendar, subscribe to the "AI@AUEB" group on MS Teams
(code: r2dtl45). Team members can also send text messages (chat) to other team members.

If you are an AI researcher or practitioner, please consider becoming a member of the Hellenic Artificial Intelligence Society (EETN, http://www.eetn.gr/en/).

SAW2023 - Short course on Football Analytics - 2-3 May 2023

THE DEPARTMENT OF ECONOMICS OF THE ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS

WITH THE FINANCIAL SUPPORT OF HELLENIC FOUNDATION FOR RESEARCH AND INNOVATION

ORGANIZES AN INTERNATIONAL CONFERENCE ON

Refined Econometrics and Endogeneity

11:30 am – 17.00 pm, April 7th, 2023, Athens, Greece

Conference Venue: Athens University of Economics & Business (Troias Str Building)

Host Institution: Athens University of Economics & Business (AUEB)

Organizing committee: Dimitris Christopoulos (AUEB (IEES), Yiannis Dendramis (AUEB (Econ)) and Elias Tzavalis (AUEB (Econ))

Financial support: Hellenic Foundation for Research and Innovation under the “First call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (project no: HFRI-FM17-3532). 

Conference Programme (pdf)

UNESCO Chair on Digital Methods for the Humanities and Social Sciences

Seminar Series: Digital Work

Wednesday, 15 March 2023, 4:30 p.m.
Trias Building, Room 107, Trias 2 & Spetson, Athens 11362

and online via: https://www.dept.aueb.gr/el/dmh/LiveSeminar

Speakers:
Dr. Yannis Assael, Staff Research Scientist, Google DeepMind
Dr Thea Sommerschield, Marie Skłodowska-Curie fellow, Ca' Foscari University of Venice
Dr. John Pavlopoulos, Researcher, Athens University of Economics and Business

Topic: Predicting the past: AI for Ancient Greek Epigraphy

Abstract

Ancient history relies on disciplines such as epigraphy - the study of inscribed texts known as inscriptions - for evidence of the thought, language, society and history of past civilizations. However, over the centuries, many inscriptions have been damaged to the point of illegibility, transported far from their original location and their date of writing is steeped in uncertainty. In this talk we will present Ithaca, the first deep neural network for the textual restoration, geographical attribution and chronological attribution of ancient Greek inscriptions. Ithaca is designed to assist and expand the historian’s workflow. The architecture of Ithaca focuses on collaboration, decision support and interpretability. While Ithaca alone achieves 62% accuracy when restoring damaged texts, the use of Ithaca by historians improved their accuracy from 25% to 72%, confirming the synergistic effect of this research tool. Ithaca can attribute inscriptions to their original location with an accuracy of 71% and can date them to less than 30 years of their ground-truth ranges, redating key texts of Classical Athens and contributing to topical debates in ancient history. Ithaca actively demonstrates how Artificial Intelligence can unlock the cooperative potential of the Sciences and the Humanities, for a better understanding of our nature and transformationally impacting the study of one of the most significant periods in human History.

Yannis Assael

Dr. Yannis Assael is a Staff Research Scientist at Google DeepMind working on Artificial Intelligence, and he is featured in Forbes' "30 Under 30" distinguished scientists of Europe. In 2013, he graduated from the Department of Applied Informatics, University of Macedonia, and with full scholarships, he did an MSc at the University of Oxford, finishing first in his year, and an MRes at Imperial College London. In 2016, he returned to Oxford for a DPhil degree with a Google DeepMind scholarship, and after a series of research breakthroughs and entrepreneurial activities, he started as a researcher at Google DeepMind. His contributions range from audio-visual speech recognition to multi-agent communication and AI for culture and the study of damaged ancient texts. Throughout this time, his research has attracted the media's attention several times, has been featured on the cover of the scientific journal Nature, and focuses on contributing to and expanding the greater good.

Thea Sommerschield

Thea Sommerschield is a Marie Skłodowska-Curie fellow at Ca’ Foscari University of Venice. Her research uses machine learning to study the epigraphic cultures of the ancient Mediterranean world. Since obtaining her DPhil in Ancient History at the University of Oxford in 2021, she has been the Ralegh Radford Rome Awardee at the British School at Rome, Fellow in Hellenic Studies at Harvard’s Center for Hellenic Studies and Research Innovator at Google Cloud. She co-led the Pythia (2019) and Ithaca (2022) projects, and has worked extensively on Sicilian epigraphy.

John Pavlopoulos

John Pavlopoulos is a researcher currently affiliated with the Athens University of Economics and Business (AUEB) and Stockholm University (SU). Before that, he was a visiting scholar at Ca' Foscari University of Venice (Venice Centre for Digital and Public Humanities) and a senior lecturer (fixed-term) at SU. His BSc was in Applied Mathematics and Physical Sciences at the National Technical University of Athens, his MSc was in Artificial Intelligence at the University of Edinburgh, and his Ph.D. at AUEB was focused on aspect-based sentiment analysis. His research is focused on machine learning for natural language processing and his recently published work concerns opinion polarization, toxic language detection and mitigation, diagnostic captioning, Homeric computational authorship analysis, and Ithaca.