ADS Highlights Event 2020
2020 has been a challenging year for all, but with it’s Highlights Event, Amsterdam Data Science aims to showcase the many ways the ecosystem has overcome these challenges and has been further incentivised to do world-class research in the fields of Data Science and AI.
You can re-watch the whole event or read the presentation slides.
Keynote: Elissa Redmiles
The event featured a keynote from Elissa Redmiles with her talk on:
Learning from the People – Responsibly Encouraging Adoption of Contact Tracing Apps.
Elissa presented an empirically-validated framework of user’s decision inputs to adopt COVID-19 contact tracing apps, including app accuracy, privacy, benefits, and mobile costs. Using predictive models of users’ likelihood to install COVID-19 apps based on quantifications of these factors, she showed how high the bar is for achieving adoption and suggests user-driven directions for ethically encouraging users to adopt. See Elissa’s presentation slides.
We gave our partners the opportunity to showcase their cutting-edge research, each speaker had four minutes to present. You can view their presentations here.
- Paul Groth – IvI, UvA
The UvA Data Science Center – Furthering Research with Data Science
- Mark Siebert – Elsevier
Advancing AI to better support researchers
- Clarisa Sánchez Gutiérrez – ICAI Amsterdam
AI For Oncology: Breast cancer
- Diederik Fokkema & Drona Kandhai – ING
Future of Banking
- Michel Klein – CS, VU
Stimulating healthy behavior via AI technology
- Nanda Piersma – AUAS ECAAI
Start of Expertise centre Applied AI
- Tamas Madl – Amazon Web Services
Cloud Machine Learning in Genomic Testing for Cancer
- Laura Hollink – CWI
Cultural AI: A Lab for Culturally Valued AI
- Sila Ozen Guclu – VodafoneZiggo
AI in VodafoneZiggo
- Stevan Rudinac – Amsterdam Business School
So, how was your 2020 over there at the ABS?
- Ivan Ortega – Qualogy
Disaster Prediction, Preparedness and Response & Standardisation in AI
ADS Thesis Awards
The ADS Thesis Awards aim to promote excellence in Data Science and AI from students at the Bachelor and Master level in all Amsterdam-based knowledge institutes.
The goals of the awards:
- Reward and champion high-quality thesis work;
- Promote women and underrepresented minorities and encourage them to continue their education;
- Encourage diversity in Data Science and AI research;
- Advance Amsterdam and the ADS network as an innovation hub by showcasing excellent theses.
During the highlights event we announced the 2020 BSc and MSc winners:
Bachelor Thesis Award
Johanna A.E. Heddes
The automatic detection of dataset names in scientific articles
University of Amsterdam
Supervisor: Dr. M. J. Marx
This thesis tackles the problem of automatically extracting datasets used in experimental evaluation from scientific papers in Machine Learning, Data Mining, Information Retrieval, and Computer Vision. In her work, Johanna contributed to the creation of a huge manually annotated dataset; she further crafted very good and explicit annotation guidelines, based on existing work, which resulted in high quality gold standard data.
Evaluating Performance Characteristics of the PMDK Persistent Memory Software Stack
Vrije Universiteit Amsterdam
Supervisor: Dr. ir. Animesh Trivedi and Ir. Sacheendra Talluri
This thesis investigates the performance of non-volatile memory, i.e., data is not lost when electric power is lost. The thesis uncovers several performance issues of such systems through a thorough performance evaluation.
Master Thesis Award
Lexical Semantic Change Analysis with Contextualised Word Representations
University of Amsterdam
Supervisors: Dr. Raquel Fernandez and Marco del Tredici
This thesis presents a novel approach that allows the detection and analysis of word-meaning and how this changes over time. It is the first unsupervised approach for this task that obtains word representations from a Transformer-based neural language model. This approach is domain-independent, data-driven, automatic, and easily reproducible.
What does it mean to be language-agnostic? Probing multilingual sentence encoders for typological properties
University of Amsterdam
Supervisor: Dr. Ekaterina Shutova
In her MSc thesis Rochelle Choenni focuses on the interpretation of popular multilingual sentence encoders, investigating which linguistic typological properties they encode and how. Rochelle’s thesis work contributes to a better understanding of modern natural language processing techniques and makes an important step in making them more accessible to low-resource languages.
At the 2019 Highlights Event, ADS announced it would be awarding up to five Research Coupons to help forge new public-private research partnerships. This year, there will be five more Research Coupons up for grabs! Given it’s so difficult to network, ADS will be helping with the match-making. Fill out the match-making form with your research interests for the chance to receive a €5000 research coupon to hire a research assistant for one year.
8th January 2021: Submit match-making form
12th Feb 2021: Submit the collaboration proposal
26th Feb 2021: ADS announces the successful applications
Watch the 2020 ADS Highlights Event or see the presentation slides.
The Institute for Advanced Study (IAS) and Data Science Center (DSC) of the University of Amsterdam (UvA) are joining forces in a new joint fellowship for (teams of) researchers interested in exploring the intersection of data science and other disciplines. The first fellow of the new program, Dr. Davide Ceolin, will start his fellowship at the IAS on June 17. Ceolin is currently affiliated with CWI.
Nanda Piersma, lecturer at the University of Applied Sciences (AUAS), has been appointed as a crown member of the Social and Economic Counsil (SER). This is the first time that a lecturer has been appointed as member of the SER. Nanda Piersma was approached because of her expertise in the field of digitisation.
The ADS Thesis Awards aim to promote excellence in Data Science and AI from students at BSc and Master level. The Awards are open to students from all Amsterdam-based knowledge institutes.