Συνέδρια, Ημερίδες, Ομιλίες, Διαλέξεις Διακεκριμένων Ομιλητών

The Department of Accounting and Finance of the Athens University of Economics and Business (AUEB) and the ACCA (Association of Chartered Certified Accountants) organization invite you to the conference they co-organize on Tuesday, March 7 at 9:00 a.m. in the Antoniadou Amphitheater at AUEB.

The event will host renowned professionals in Accounting and Finance, who will inform the student audience about important issues on sustainability and emerging new technologies in Accounting and Finance. They will also provide important information on future career prospects in the Accounting and Finance disciplines.

Students will have the unique opportunity to participate in a business game, which will provide them the opportunity to get an insight into Accountancy and Finance profession, in a fun and interactive way. To participate in the business game, it is required that the students form groups (consisting of a maximum of 5 members each group) and the registration for each individual student is at the following link (closing date: February 19):

https://www.eventbrite.com/e/acca-business-game-the-future-leader-aueb-7th-march-tickets-517525451557 
 

In the attached file of this announcement, more information about the business game is provided.

Your presence would be a special honor for us.

Georgia Siougle (gsiougle@aueb.gr)
Leonidas Doukakis (ldoukakis@aueb.gr)
Efthimios Demirakos (demirakos@aueb.gr)
Sotirios Karatzimas (skaratzimas@aueb.gr)
Athanasios Sakkas (asakkas@aueb.gr)

UNESCO Chair on Digital Methods for the Humanities and Social Sciences

Seminar Series: Digital Work 

Thursday, 26 January 2023, 4-5 p.m. 
Trias Building, Room 106, Trias 2 & Spetson, Athens 11362

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

peaker: Jonathan Matthews, Head, Yad Vashem Photo Archive
Topic: "Understanding history through photo collections in a digital age - the challenges of Holocaust Archives in the future"

More info: Link

AUEB Business Analytics Laboratory and AI@AUEB talk

Title: AI Explainability and Tech Trust & Safety
Presenter: Theodoros Evgeniou, INSEAD
Scheduled: Monday 2022-12-19, 13:00 (Greek Time)
Room: T107 (Troias building)
and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1670931260154?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

## Abstract
Discussions about trustworthy and responsible AI have become central across multiple communities in recent years -  machine learning, law, social sciences, among others. A key challenge regarding trust in AI - also considered important by regulators as part of transparency for some AI applications - is to understand why black boxes may be making specific predictions. As a result, explainable AI (XAI) has been a growing topic of research. In this talk, I will discuss some potential drawbacks XAI may have - including the potential to erode safety in practice - and also present some work that takes into account behavioural aspects researchers and practitioners may need to consider when developing XAI.

## Speaker bio
Theos Evgeniou is a professor of Decision Sciences and Technology Management at INSEAD and director of the INSEAD Executive Education program on Transforming your Business with AI.

He has been working on Machine Learning and AI for the past 25 years, on areas ranging from AI innovations for business process optimization and improving decisions in Marketing and Finance, to AI regulation, as well as on new Machine Learning methods. His research has appeared in leading journals, such as in Science Magazine, Nature Machine Intelligence, Machine Learning, Lancet Digital Health, Journal of Machine Learning Research, Management Science, Marketing Science, Harvard Business Review magazine, and others.

Professor Evgeniou is a member of the OECD Network of Experts on AI, an advisor for the BCG Henderson Institute, an advisor for the World Economic Forum Academic Partner for Artificial Intelligence, and together with three INSEAD alums also a co-founder of Tremau, a B2B SaaS company whose mission is to build a digital world that is safe & beneficial for all. He gives talks and consults for a number of organisations in his areas of expertise, and in the past he has been involved in developing hedge fund strategies with more than $100 million invested. He has received four degrees from MIT, two BSc degrees simultaneously, one in Computer Science and one in Mathematics, as well as a Master and a PhD degree in Computer Science.

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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/).
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«Croatia's Path to the EU and the Eurozone»: The M.Sc. Program in International Negotiations of the Department of International and European Economic Studies of the Athens University of Economics and Business is organizing a Special Lecture by Mr. Boris Vujčić, Governor of the Central Bank of Croatia, in collaboration with Get Involved.

Public discussion: George Pagoulatos, Professor of European Politics and Economy at the Athens University of Economics and Business (AUEB), Visiting Professor at the College of Europe in Bruges.

The event will take place on December 8, 2022 at the Radisson Blu Park Hotel (18:00).

 Supported by ELIAMEP

International Conference on

«Non-linear Econometrics and Endogeneity»

December 16th, 2022, Athens, Greece
10:30 am – 17.30 pm

Host Institution: Athens University of Economics and Business

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

Conference Venue: The conference will take place at Radisson Blu Park Athens
(Atlantis Room), 10, Alexandras Av 10682 Greece

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 Agenda: 
https://www.aueb.gr/sites/default/files/aueb/Brochure_conf_16_12_elidek_final.pdf

ΑΙ@AUEB talk (hybrid presentation)
Tuesday, 22 November 16:15-17:00 (Greek time)

and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1668589269563?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

Room: T106, Troias building

Speakers: Konstantina Dritsa, John Pavlopoulos, Panos Louridas

Title: “What we Talk about When we Talk about Politics"

Abstract:

How does the meaning of words change over time? Methods in Natural Language Processing allow us to study the semantic shift of language elements, opening up a window onto language change. To this end, we curated a dataset of the Greek Parliament Proceedings that extends chronologically from 1989 up to 2020. It consists of more than 1 million speeches with extensive metadata, extracted from 5,355 parliamentary record files. The dataset can be used for both computational linguistics and political analysis-ideally, combining the two. We present such an application, showing (i) how the dataset can be used to study the change of word usage through time, (ii) between significant historical events and political parties, (iii) by evaluating and employing algorithms for detecting semantic shifts. The presentation is based on a paper that was accepted at the NeurIPS 2022 conference Track on Datasets and Benchmarks.

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/).

The 19th e-Summer School in Risk Finance and Stochastics, 28 - 30 September 2022 is organized by AUEB (Departments of Accounting & Finance, Business Administration, Statistics) in collaboration with the University of the Aegean (Departments of Statistics & Actuarial-Financial Mathematics, Financial & Management Engineering).

Due to the current situation concerning the COVID 19 pandemic, the standard operation of the Summer School would be difficult, if not impossible. However, trying to stay loyal to our usual annual meeting, we decided to transform the school into e-mode, thus enabling distant participation. Surely, we will lose the joy of meeting, interacting and exchanging views, however, we hope that next year we will be able to get back to our usual modus operandi.

As always, we will have the pleasure and honour of having with us distinguished academics in the field.

Details concerning the keynote speakers as well as the program of the school will be announced after the 15th of September.

The school is addressed to postgraduate students, PhD students, postdocs, researchers and practitioners whoa are interested to stay informed about the latest developments in the field of stochastic finance.

There is no fee for attending the school, but interested participants should send an e-mail of intention to participate to masterst@aueb.gr , stating their name, capacity, affiliation and including a short cv (no more than 10 lines), by 15 September, so that the selection procedure can proceed on time.

The maximum number of participants will be 30 and among equivalent participants priority will be given to those who applied first.

The Organizing Committee

I. Baltas (Aegean),
G. Kouretas (AUEB),
G. Papayiannis (HNA),
A. Tsekrekos (AUEB),
S. Vakeroudis (AUEB)
S. Xanthopoulos(Aegean),
A.N. Yannacopoulos (AUEB)
A. Zimbidis (AUEB)

AUEB-NKUA-Indiana Conference in Biostatistics & Health Analytics

4-6 July 2022, Aegina Island

We are pleased to announce the first AUEB-NKUA-Indiana Conference on Biostatistics & Health Analytics. 

​This is within the broader collaboration between the The Fairbanks School of Public Health, the School of Public Health in Bloomington of Indiana University and the Department of Statistics of Athens University of Economics and Business and the National and Kapodistrian University of Athens School of Medicine (NKUA). 

More info: https://aueb-analytics.wixsite.com/biostats-conf

Registration: https://aueb-analytics.wixsite.com/biostats-conf/registration

ΑΙ@AUEB talk (hybrid presentation)

Tuesday, 28 June 17.15 (Greek time)

Room: Ground floor, Troias building

and virtually via MS Teams:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1653150802937?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

Speaker: Stratis Ioannidis, Northeastern University, USA

Title: Spectral Algorithms for Ranking Regression

Abstract: We consider learning from rankings, i.e., learning from a dataset containing subsets of samples ranked w.r.t. their relative order. For example, a medical expert presented with patient records can order them w.r.t. the relative severity of a disease. Rankings are often less noisy than class labels: human experts disagreeing when generating class judgments often exhibit reduced variability when asked to compare samples instead. Rankings are also more informative, as they capture both inter and intra-class relationships; the latter are not revealed via class labels alone. Nevertheless, the combinatorial nature of rankings increases the computational cost of training significantly. We propose spectral algorithms to accelerate training in this ranking regression setting; our main technical contribution is to show that the Plackett-Luce negative log-likelihood augmented with a proximal penalty has stationary points that satisfy the balance equations of a Markov Chain. This observation yields fast spectral algorithms for ranking regression for both shallow and deep neural network regression models.
Compared to state-of-the-art siamese networks, our resulting algorithms are up to 175 times faster and attain better predictions by up to 26%
Top-1 Accuracy and 6% Kendall-Tau correlation over five real-life ranking datasets.

Bio: https://ece.northeastern.edu/fac-ece/ioannidis/bio.html

We are happy to announce the next (remote) AI@AUEB talk:

Date/time: Tuesday 7 June 2022, 17:15-18:00 (Greek time)
Title: "On new variants of multiplicative weights update and mirror descent methods for zero-sum games"
Speaker: Vangelis Markakis (http://pages.cs.aueb.gr/~markakis/)

Abstract:

Our work focuses on extra gradient learning algorithms for finding Nash equilibria in bilinear zero-sum games. Such algorithms tend to exhibit a stronger performance than simple gradient methods, by having an intermediate and a final gradient step in each iteration. In this talk, we will first give an overview of recently proposed learning algorithms in this context, such as the Optimistic Multiplicative Weights Update method (by Daskalakis, Panageas, 2019) and Optimistic Mirror Descent (by Mertikopoulos et al. 2019). We will then propose a new algorithm, which can be formally considered as a variant of Optimistic Mirror Descent, using a large learning rate for the intermediate gradient step (and interpreted as computing approximate best response strategies against the profile of the previous iteration). Our main theoretical result is that the method guarantees last-iterate convergence to an equilibrium. In particular, we show that the algorithm reaches first an approximate Nash equilibrium, by decreasing the Kullback-Leibler divergence of each iterate, until the method becomes a contracting map, and converges to the exact equilibrium. Furthermore, we present experimental comparisons against the optimistic multiplicative weights update method, and show that our algorithm has significant practical potential since it offers substantial gains in terms of accelerated convergence.

Paper: https://arxiv.org/abs/2106.03579

MS Teams link:

https://teams.microsoft.com/l/meetup-join/19%3aOiYUJgd5vTDTv9p0FnXvTdZ9TTZxIBRHwZzEpD02P-Y1%40thread.tacv2/1653150802937?context=%7b%22Tid%22%3a%22ad5ba4a2-7857-4ea1-895e-b3d5207a174f%22%2c%22Oid%22%3a%225b49c8b5-6801-409c-a8f8-6e18215b3a08%22%7d

ΑΙ@AUEB Lecture Series aim is to create collaborations, both between AUEB’s Departments and with external bodies and organizations, promoting the work of AUEB members, further strengthening existing collaborations, and possibly attracting additional resources.

To subscribe to the mailing list of AI@AUEB, send a message (with any subject and body) to ai_meetings-subscribe@lists.aueb.gr. To unsubscribe, send a  message (with any subject and body) to ai_meetings-unsubscribe@lists.aueb.gr. Only the organizers of AI@AUEB can post messages to the mailing list.

If you have an AUEB account, you can also subscribe to the MS Teams team "AI@AUEB" (team code: r2dtl45). This way you will be able to see the scheduled AI@AUEB talks on your MS Teams calendar. You will also be able to send messages to the members of the team.