Keynotes and Panels
Keynote speeches introduce the main topic and clear the ground for further discussion. Selected expert panelists discuss together the related issues and afterwards answer questions from the audience during the panel discussions.
After the official opening and welcome notes, during the two-day womENcourage 2020 conference you will join our distinguished speakers to learn about The Big Promise of Big Data Analytics and to explore The Artificial Intelligence: from Algorithms to Ethics.
Welcome Note from the ADA University Patron
Dr. Vafa Kazdal
|Vafa currently serves as the Vice-Rector of Academic Affairs at ADA University. She provides strategic leadership for guiding the academic programs into the future, and ensures enhancement of their effectiveness and quality. Since 2009, she was appointed to different positions at ADA, such as Dean of the School of Arts and Humanities in 2012 and Dean of the School of Education in 2014. |
Vafa holds a master’s degree in English Language Studies and Methods from the University of Warwick, UK and a doctorate in Pedagogy from the Azerbaijan University of Languages. Her teaching and research are in the areas of educational policy and administration, teacher education, program design, implementation, and evaluation, as well as language and identity.
She received professional development awards to work on various projects at Indiana University, Bloomington and University of Michigan, Ann Arbor in the USA, and at Oxford University, UK.
Welcome Note from the ACM President
Dr. Gabriele Kotsis
|Gabriele is the ACM President and a Full Professor in Computer Science at Johannes Kepler University in Linz, Austria. She has organized ACM conferences and workshops, and in 2016 received an award in appreciation of her accomplishments regarding the ACM womENcourage conference series. |
Gabriele is a founding member of the ACM Europe Council, serving from 2008 to 2016. In 2014, she became an ACM Distinguished Member for her contributions to workload characterization for parallel and distributed systems, and for founding ACM Europe. Since 2016, she has been an elected Member-at-Large of the ACM Council.
ACM has elected Gabriele Kotsis as President for a two-year term beginning 1 July 2020.
Welcome Note from the ACM-W Europe Chair
|Ruth is the Chair of the ACM-W Europe as well as the Academic Advisor to the ACM-LYIT and ACM-W-LYIT Student Chapters. She has organized or been on the program committee for many ACM events. She has been lecturer with Letterkenny Institute of Technology for 20 years but spends much of her time working with industry in conferences or on research.|
Ruth Lennon is an educator and evangelist for DevOps. She currently focuses on Software as a Service particularly the development of Web Services for large-scale secure software development. Ruth actively works on course development to meet both the long and short term needs of industry. She is a member of the ACM, IEEE, NSAI and is member of the IEEE P2675 DevOps Standard Working Group, as well as the ISO/IEC JTC 1/SC 38 Working Group.
After presenting their topics the keynote speakers will get together in a live panel discussion to provide a glimpse of the wide spectrum of Big Data research and applications, as well as to answer questions from the audience.
▼ Data Science to Fight the COVID-19 Pandemic: the Valencia Case
Since March 2020, Dr. Nuria Oliver has been appointed Commissioner for the President of the Valencian Region on Artificial Intelligence Strategy and Data Science applied to the fight against COVID-19. She is leading a team of over 20 data scientists, who work on large-scale modeling to answer public policy questions. As part of this work, they have launched covid19impactsurvey, one of the largest anonymous citizens’ surveys to date related to COVID-19. This talk will describe the initial results of the large-scale human mobility modeling and computational epidemiological modeling.
Dr. Nuria Oliver
|Nuria is Chief Data Scientist at Data-Pop Alliance, Chief Scientific Advisor at the Vodafone Institute and co-founder of ELLIS (The European Laboratory for Learning and Intelligent Systems). She was the first female Scientific Director at Telefonica R&D and the first Director of Research in Data Science at Vodafone globally.|
With over 25 years of research experience in Artificial Intelligence, Human Computer Interaction and Mobile Computing at MIT, Microsoft Research, she advise universities, governments and institutions like the European Commission and the World Economic Forum on Artificial Intelligence and Big Data. Her work is well known with over 160 scientific publications that have received more than 18,000 citations. She is co-inventor of over 40 filed patents and a regular keynote speaker at international conferences.
Nuria is a Distinguished Scientist of the ACM and an ACM Fellow. She is also a Fellow of the European Association of Artificial Intelligence (eurAI) and an IEEE Fellow. Her many other honors include membership of the Spanish Royal Academy of Engineering, CHI Academy and the Academia Europaea.
▼ Health Diagnostics through Audio Signals Collection and Analysis
Audio signals generated by the human body (e.g., sighs, breathing, heart, digestion, vibration sounds) have routinely been used by clinicians as diagnostic or progression indicators for diseases and disease onset. However, until recently, such signals were usually collected through manual auscultation at scheduled visits. Research has now started to use digital technology to gather bodily sounds (e.g. from digital stethoscopes) for cardiovascular or respiratory examination, which could then be used for automatic analysis. In this talk Dr. Cecilia Mascolo will describe the initial progress in using sounds for diagnostics and the challenges this poses. She will also describe their effort to collect and analyze data over a large-scale crowdsourced dataset of respiratory sounds collected to aid diagnosis of COVID-19.
Dr. Cecilia Mascolo
|Cecilia is Co-Director for the Centre for Mobile, Wearable Systems and Augmented Intelligence and a Full Professor of Mobile Systems in the Department of Computer Science and Technology and at Cambridge University in the UK. Her interests are in the study of mobile systems, the learning from their data offline and on device and their applications, especially in terms of mobile health. She is a Fellow of Jesus College and also Director of Studies for Computer Science in there. |
She is a recipient of Google Faculty Research Award 2019 and member of the editorial boards of number of journals, including the ACM Transactions on Computing for Healthcare, Royal Society Open Science, the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies and the ACM Transactions on Sensor Networks.
Cecilia regularly delivers keynotes and invited talks at conferences and workshops. A comprehensive list can be found here.
▼ Democratizing Data Access through Intelligent Data Exploration Tools
Many different data sets, generated by users, systems and sensors, are continuously being collected. These data sets contain information about scientific experiments, health, energy, education etc., and they are highly heterogeneous in nature, ranging from highly structured data in tabular form to unstructured text, images or videos. These data can potentially benefit many types of users, from analysts exploring data sets for insight, scientists looking for patterns, to dashboard interactors and consumers looking for information. While the benefit of data exploration becomes increasingly more prominent, the limitations of existing tools make accessing and combining data from different sources a non-trivial, time-consuming, and often fruitless endeavor. In this talk Dr. Georgia Koutrika will discuss about what it takes to bridge the gap between users and data, and the new generation of intelligent data exploration tools.
Dr. Georgia Koutrika
|Georgia is Research Director at Athena Research Center in Greece. She has more than 15 years of experience in multiple roles at HP Labs, IBM Research – Almaden, and Stanford University. |
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 the VLDB Journal, associate editor for the IEEE Transaction on Knowledge and Data Engineering, and an ACM Distinguished Speaker. She has served or serves as a program committee member or co-chair of many conferences, including Demo Program Committee chair of ACM SIGMOD 2018 and General Chair of ACM SIGMOD 2016.
|Chinara is a Data Scientist at PASHA Bank in Baku, Azerbaijan. She is working in digital underwriter and risk engine projects for improved decision making processes. |
She obtained her MSc in Computational Finance from University College London in 2016. While studying in there, her main research focus was in analyzing financial data and writing automated trading strategies for optimization by using genetic algorithms.
Prior to this, Chinara had experience in exploratory data analysis using ACL (Audit Command Language) at one of the Big Four companies for detecting any unusual activities in more than 20 organizations.
Chinara promoted application of Computer Science in Finance at the recent female economists forum in Azerbaijan. She is a data enthusiast and in her free time, when not busy with DataCamp projects, she enjoys playing piano.
Following the presentations a live panel discussion will bring together the keynote speakers to provide an overview of the different aspects of the Artificial Intelligence (AI) research and applications, as well as to answer questions from the audience.
▼ Teaching proficient human interaction to intelligent computer agents
Automated agents that interact proficiently with people can be useful in supporting or replacing people in complex tasks. The inclusion of people presents novel problems for the design of automated agents’ strategies. People do not adhere to the optimal, monolithic strategies that can be derived analytically. Their behavior is affected by a multitude of social and psychological factors. In this talk, Dr. Sarit Kraus will show how combining machine learning techniques for human modeling, human behavioral models, formal decision-making and game theory approaches enables agents to interact well with people. Applications include intelligent agents that help reducing car accidents, triage agent that schedules patients to caregivers in emergency departments, agents that are used for training law-enforcement personnel, and agents that support a human operator in managing a team of low-cost robots in search and rescue tasks.
Dr. Sarit Kraus
|Sarit is a Professor of Computer Science at Bar-Ilan University. She obtained her PhD in Computer Science from Hebrew University in 1989. Her research is focused on intelligent agents and multi-agent systems (including people and robots) integrating machine-learning techniques with optimization and game theory methods. In particular, she studies the development of intelligent agents that can interact proficiently with people and with robots. She has also contributed to the research on machine learning, agent optimization, autonomous vehicles, homeland security, adversarial patrolling, social networks and non-monotonic reasoning. |
For her work she received many prestigious awards. She was awarded the IJCAI Computers and Thought Award, the ACM SIGART Agents Research Award, the ACM Athena Lecturer, the EMET Prize (known as Israel’s Nobel Prize) and was twice the winner of the IFAAMAS Influential Paper Award. She is an ACM, AAAI and ECCAI fellow and a recipient of the advanced ERC grant. She also received a special commendation from the city of Los Angeles, together with Prof. Tambe, Prof. Ordonez and their University of Southern California students, for the creation of the ARMOR security scheduling system.
She has published over 400 papers in leading journals and major conferences and co-authored five books. She is a member of the board of directors of the International Foundation for Multi-agent Systems (IFAAMAS) and was IJCAI 2019 program chair.
▼ Who Makes Wiser Decisions? Men, Women or Machines?
Despite the great opportunities that AI systems offer, the underlying machine learning models are often not resilient enough to avoid manipulation and sometimes do not behave as intended. In more detail, this means that there are specific types of risks for AI systems such as model biases, adversarial attacks and new ways to exploit privacy leakages. To prevent AI models from these risks and to provide safe and fair Al, the Intelligence team at T-Labs led by Claudia Pohlink together with cybersecurity researchers from Ben-Gurion University in Israel and the Berlin-based start-up Neurocat are currently working on an end-to-end ethical and technical assessment of the robustness of AI applications. The envisioned platform will enable defense mechanisms to enrich existing solutions with necessary countermeasures. As a result, this flagship project aims to pave the way for a reliable application of future AI systems.
Dr. Marlene Gerneth
|Marlene is Program Manager for the Artificial Intelligence team at T-Labs (Telekom Innovation Laboratories), the research unit of Deutsche Telekom. The AI team drives the research of AI methods such as machine learning (ML) for Deutsche Telekom and their adaptation across relevant business areas; its main research focus is on the application of Quantum Computing, in the field of Cyber Security as well as around sustainability use cases. Since T-Labs has established AI as a core innovation area in 2017, the research facility of Deutsche Telekom is one of the most active players in AI in Berlin. |
Besides the AI team Marlene serves the T-Labs Blockchain Group as Lead of Operations Office. Before that, she managed the Industrie 4.0 research and development program of T-Labs, T-Labs’ share in the Digital Co-Innovation Labs, various projects in the domain of Ambient Assisted Living, eHealth, and Connected Home, as well as the technology scouting team which published the Deutsche Telekom’s Technology Radar®.
Marlene holds a doctor’s degree in Medical Informatics (Dipl.-Inform. Med., Dr. sc. hum.) and the PMP® (Project Management Professional), as well as Scrum and LeSS certificates. She was a member of the board of the PMI Chapter Berlin/Brandenburg and has been active as a project management trainer and lecturer.
▼ Gender Fairness of Machine Learning Techniques
Gendering ICT does not only imply changing the numbers of women in Computer Science but also addressing the problem of including the gender dimension in its content to develop gendered innovations. Many studies about the fairness of ML algorithms show that they are not gender neutral due to their nature of being bottom-up data driven. For this reason the most common biases diffused in society about gender (and ethnicity) can be captured, subsumed and reinforced by them, as many ML tool applications prove. In this talk Dr. Silvana Badaloni will discuss how learning algorithms can lead to a strong reinforcement of existing social and gender bias. The problem arises mainly since little attention is paid to how data are collected, processed and organized. Transparency and explainability are two central keywords for developing a trustworthy AI.
Dr. Silvana Badaloni
|Silvana is Associate Professor of Artificial Intelligence at the Department of Information Engineering, University of Padova, Italy and Studiosa Senior of Studium Patavinum. She is a Board Member of Elena Cornaro Center on Gender Studies at University of Padova. |
In the field of Gender in Science, she was the scientific coordinator of the Unit University of Padova, partner of the FP7 EU GenderTIME – Transferring Implementing Monitoring Equality from 2013-16. In this framework, a Gender Equality Index for Academic Institutions was developed and implemented.
In March 2019, she was named EPWS woman scientist of the month. She was one of the organizers of the ACM womENcourage 2019 Gendering ICT Workshop held in Rome. Being invited by the Embassy of Italy in Mexico, she held a Lectio Magistralis titled ‘El genero en la investigation cientifica’ as part of the Conference on ‘Igualidad de genero en la Ciencia’ held in Mexico City in November 2019.
Dr. Sabrina Aliyeva
|Sabrina is a Deep Learning Engineer at California-based Synopsys company in the USA. She obtained her PhD in Geophysics from Stanford University in 2018. During her doctoral studies she worked in image processing of large number of high-resolution scanning electron microscope (SEM) images of rocks using machine learning algorithms.|
At Synopsys, Sabrina uses her machine learning and AI skills to analyze SEM images of semiconductors and solve issues associated with the manufacturing of single-digit-nanometer (7 nanometers and below) scale circuits. Her current professional research interests also includes computational perception and robotics.
Sabrina has been promoting the role of women in computing. She was a delegate at the 2018 Grace Hopper Celebration, the world’s largest gathering of women technologists, also supported the Azerbaijan ACM Chapter events, such as annual Ada’s Legacy celebration.
|Gunay is a Doctoral Researcher at the Weizenbaum Institute for the Networked Society (Weizenbaum-Institut für die vernetzte Gesellschaft) in Berlin, Germany. She is a PhD candidate in Computer Science at the Technical University of Berlin (Technische Universität Berlin). Her main research directions are gender and racial bias in AI, inclusiveness in AI, and AI-enhanced education. |
She is a TEDx speaker, given a speech in more than 100 national and international (non-) academic conferences all over the world. In 2019, Gunay was awarded by the German Informatics Society as the “AI Newcomer” of the year in the Computer Science category. In 2020, she has been awarded the Youth Presidential Award in Azerbaijan.
Gunay has publications presented in major academic conferences as ACM AAAI/AI Ethics and Society Conference, Artificial Intelligence in Education Conference, Ethics of Data Science Conference, etc. Currently, she is also managing a social platform “TechCentrum,” which is aiming for knowledge exchange in the Emerging Tech field for underrepresented communities.