Anastasia Ailamaki, Professor of Computer and Communication Sciences, EPFL

"ReTINA: Real-Time Intelligent Analytics"

In today’s ever-growing demand for fast data analytics, heterogeneity severely undermines performance. On one hand, data format variety forces people to load their data into a single format, spending tons of resources and often losing valuable structural information. Or, requires a separate database system for each data type plus an integration tool to bring all the results together. All options are costly and waste valuable resources. On the other hand, “franken-chips” equipped with different types of potent compute units are severely under-utilised when running data analytics, as we’re used to coding with a CPU in mind and other core types are employed opportunistically, as an accelerating luxury. Nevertheless, hardware roadmaps indicate increasing levels of compute heterogeneity, and accelerator-level parallelism (ALP) is indeed the new way to make the best out of any hardware platform. Writing fast as well as programs that are portable to all kinds of microarchitectures, however, is an unsolved tradeoff. Real-time intelligence (ReTINA) makes decisions during execution, when all relevant information is available for optimal utilisation of resources. I will show how just-in-time (JIT) data virtualisation and code generation technologies can achieve ReTINA by and execute queries fast across all kinds of data without costly preparation or heavy installations, as well as enable excellent utilisation of different hardware devices.

Stratos Idreos, Associate Professor of Computer Science, Harvard University

"The periodic table of data structures"

Data structures are everywhere. They define the behavior of modern data systems and data-driven algorithms. For example, with data systems that utilize the correct data structure design for the problem at hand we can reduce the monthly bill of large-scale NoSQL applications on the cloud by hundreds of thousands of dollars. We can accelerate data science tasks by being able to dramatically speed up the computation of statistics over large amounts of data. We can train drastically more neural networks within a given time budget, improving accuracy.

However, knowing the right data structure and system design for any given scenario is a notoriously hard problem; there is a massive space of possible designs while there is no single design that is perfect across all data, queries, and hardware scenarios. We will discuss our quest for the first principles of data structures and system design. We will show signs that it is possible to reason about the design space, heading toward a future of self-designing data systems.

Liuba Shrira, Professor in Computer Science, Brandeis University

"Adversarial commerce and atomic cross-chain deals"

Modern distributed data management systems face a new challenge:how can autonomous, mutually-distrusting parties to co-operate safely and effectively? This challenge presents many questions familiar from classical distributed systems: how to combine multiple steps into a single atomic action, how to recover from failures, how to synchronize concurrent access to data, and what it means for that action to be correct. Nevertheless, each of these notions requires rethinking when participants are autonomous and potentially adversarial.
I will describe the notion of a \emph{cross-chain deal}, a new way to structure complex distributed computations in an adversarial setting. Deals are inspired by classical atomic transactions, but are necessarily different, in important ways, to accommodate the decentralized and untrusting nature of the exchange. I will describe novel safety and liveness properties, along with alternative protocols for implementing cross-chain deals in a system of independent blockchain ledgers..

Geraldine Fitzpatrick, Human Computer Interaction Group, TU Wien

Summary:

Academia can be overwhelming with seemingly never-ending demands, opportunities and pressures. How to make good choices and what powers do we have to craft a good academic life/career? In this mini-workshop we will first explore our personal ‘red threads’ that point to our values, strengths, and what is important to us. We will then discuss practical strategies for how to say yes/no strategically and wisely in line with our red threads and to craft our choices to do more of what matters. We have more powers than we think we do!

Katerina Kalimeri, Cloud Security Lead, Oracle

"Exploring the Benefits of Gender Diversity in Cybersecurity"

Even though men outnumber women in cybersecurity by three to one, more women are joining the field – and they are headed for leadership positions. This gender discrepancy, coupled with the cybersecurity skills shortage, offers women a valuable career opportunity, and gives organizations a means for filling the skills gap that currently plagues the industry. The talk will elaborate on the importance of security to practice in IT Roles, how security knowledge and skills enhance IT careers, how women can help fill the cybersecurity skills gap as well as tips for getting ahead.

Sofia Tsekeridou, Senior Research and Innovation Manager, INTRASOFT International

"Technological trends and innovations in digital security and public safety IT solutions"

The talk will demonstrate recent trends and advancements in methods and tools that will constitute the next generation security IT solutions in diverse application domains. The talk will present in detail distributed ledger technologies for sensitive data exchanges, federated and machine learning paradigms for threat/anomaly detection, visual analytics for effective situational awareness and decision support, among others, demonstrating relevant results and ongoing work in EU-funded research projects.

Ilianna Kollia, Senior Data Scientist / Cognitive Computing Expert, IBM

"How Artificial Intelligence can transform the way we live"

Artificial Intelligence (AI) is transforming the way we live and interact with the environment. New AI applications are constantly being developed and deployed in research and industrial settings. The current coronavirus crisis has increased the demand for such intelligent applications to assist people in their daily tasks, ranging from big data analytics to efficient drug discovery/disease treatment. In this talk I will present an overview of the current AI/Machine Learning landscape and I will discuss how IBM globally and, in particular, IBM in Greece, contributes to this AI/Cognitive era.

Marily Nika, Machine Learning Product Manager, Google

Based in San Francisco, Marily Nika works for Google as a Speech AI Product Manager. Marily holds a Ph.D in Computer Science & Epidemiology from Imperial College London and is also a part-time Teaching Fellow at Harvard Business School’s Analytics Program where she runs a forum series on Product Management. Marily has delivered three TEDx talks and has received international recognition — including the Woman of the Year 2018 Award by everywoman as well as the Women in Science and Engineering (WISE) Influence Award in 2015, for empowering the Women in tech community in various ways. Marily is also actively involved in the startup scene as she serves as an advisor for 2 startups in the EdTech space and a mentor to early stage startups.

Moderator: Georgia Koutrika, ATHENA Research and Innovation Center

Dr. Georgia Koutrika is Research Director at Athena Research Center in Greece. She has more than 15 years of experience in multiple roles at HP Labs, IBM Almaden, and Stanford. Her work focuses on data exploration, recommendations, and data analytics, and has been incorporated in commercial products, described in 9 granted patents and 18 patent applications in the US and worldwide, and published in more than 80 papers in top-tier conferences and journals. She is Editor-in-chief for VLDB Journal, associate editor for TKDE, and an ACM Distinguished Speaker. She has served or serves as PC member or co-chair of many conferences (including Demo PC chair of ACM SIGMOD 2018 and General Chair of ACM SIGMOD 2016). 

Vicky Charisi, European Commission

Vicky Charisi is a Research Scientist at the Centre for Advanced Studies, Joint Research Centre of the European Commission working at the HUMAINT project with a focus on the impact of Artificial Intelligence on Human Behaviour. Her expertise is on Social Robotics and Human-Robot Interaction and she investigates aspects of human cognition and human social behaviour in the context of intelligent robotic systems. Vicky has a background in Educational Technology (MA, National and Kapodistrian University of Athens, Greece) and in Child-Computer Interaction in the context of music creativity (PhD Candidate, University College London, UK). Before her current position at the European Commission, she was a research associate at the University of Twente, the Netherlands working on Human-Robot Interaction, Depart. Electrical Engineering, Mathematics and Computer Science. Her current research at the JRC is closely related to the scientific support of policy recommendations within the commission and she is actively involved in global initiatives such as Artificial Intelligence and Child’s Rights at UNICEF (NY). Vicky has more than 50 scientific publications in high impact academic journals and conferences. She is a core member of the International Consortium of Socially Intelligent Robotics and she currently serves  as an appointed chair for the IEEE Computational Intelligence Society, Cognitive and Developmental Systems,  TF of Human-Robot Interaction (2019-2021). 

George Giannakopoulos, NCSR "Demokritos"

George Giannakopoulos studied Informatics and Telecommunications in the National and Kapodistrian University of Athens. In 2009, he obtained a PhD on Artificial Intelligence (AI) from the University of the Aegean. His love for information technologies and artificial intelligence led him to several years of research, in Greece and abroad. During the last 10 years he has been working in NCSR "Demokritos" as a research fellow. In parallel, he has been working - for more than 20 years - as an IT consultant and engineer, in domains such as medical informatics, data analysis and artificial intelligence. In 2012 he co-founded the awarded SciFY PNPC, has been applying technology transfer from research institutions to the industry and society in general, while extensively utilizing AI. Since the beginning of 2019, he is a member of the board of the Hellenic AI Society. 

Manolis Koubarakis, National and Kapodistrian University of Athens

Manolis Koubarakis is a Professor in the Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens. He holds a Ph.D. in Computer Science, from the National Technical University of Athens, an M.Sc. in Computer Science, from The University of Toronto, and a diploma (B.Sc.) in Mathematics, from the University of Crete. He is a Fellow of EurAI (European Association for Artificial Intelligence) since 2015 and vice-president of the Hellenic Association for Artificial Intelligence. He has published more than 200 papers that have been widely cited (6310 citations and h-index 42 in Google Scholar) in the areas of Artificial Intelligence (especially Knowledge Representation), Databases, Semantic Web and Linked Geospatial Data. Manolis is currently the coordinator of project ExtremeEarth (2019-2021) which develops deep learning and big data techniques for satellite data from the Copernicus program. Manolis also participates in the project AI4EU (2019-2021), which is the largest H2020 European project in the area of Artificial Intelligence. 

Eirini Ntoutsi, Leibniz University Hannover

Eirini Ntoutsi is an Associate Professor at the Leibniz Universität Hannover (LUH) and member of the L3S research center. Prior to joining LUH in 2016, she was a postdoctoral researcher at the Ludwig-Maximilians-University (LMU) in Munich, Germany which she joined with an Alexander von Humboldt fellowship for postdoctoral studies. She obtained her PhD from the University of Piraeus, Greece (2008) and she holds a diploma (2001) and a master (2003) in computer science from the Computer Engineering & Informatics Department (CEID), University of Patras, Greece.  Her current interests are in the area of data stream mining, covering aspects such as adaptive learning and forgetting, and responsible AI, covering aspects such as fairness-aware learning and proper experimentation/evaluation. Eirini is the network coordinator of the Marie Sklodowska Curie ITN network NoBIAS-Artificial Intelligence without Bias (2020-2024).  She is demo and poster co-chair for CIKM 2020 and co-organizer of the BIAS and Fairness in AI (BIAS)  and Evaluation and Experimental Design in Data Mining and Machine Learning (EDML)  workshops co-located with ECMLPKDD 2020.