Invitation
2 June 2020
Deep learning and artificial intelligence for scientific research are evolving quickly, with new developments appearing continually for analysing data sets, discovering patterns, and predicting behaviour in all fields of science. The AI4Science lab is a joint initiative of the institutes for astronomy (API), biology (IBED), chemistry (HIMS), informatics (IvI), life sciences (SILS) and physics (IoP) of the University of Amsterdam.
Several invited speakers working on the forefronts of combining artificial intelligence techniques with other sciences, e.g. systems biology, particle physics, molecular modelling, and astrophysics, will talk about intriguing scientific challenges and their latest developments to tackle them. The PhD students that started their research projects in the last months will briefly highlight the current state-of-the-art and their future perspective on using AI in their respective scientific domains.
The workshop is free of charge and you can register through this link.
Registered attendees will have the possibility to ask questions after the lectures, present a poster, and join the poster session and breakout rooms for further discussion. The workshop will be an online event with the help of video conferencing tools.
The AI4Science lab is a joint initiative of the institutes for astronomy (API), biology (IBED), chemistry (HIMS), informatics (IvI), life sciences (SILS) and physics (IoP) of the University of Amsterdam. The lab’s aim is to solve scientific data problems with modern machine learning approaches.
The focus will be on five projects from completely different fields: predicting bird migration from radio data (IBED), enhancing chemical discovery procedures (HIMS), finding signals in gravitational waves (IoP), classifying space radio phenomena (API) and unraveling causal relations in gene regulation networks (SILS). But even though these projects cover a wide range of scientific fields, the underlying research question the AI4Science lab aims to answer is basically always the same: How can we detect, classify, and predict relevant patterns in scientific data if they are hidden within large amounts of non-relevant data?
For such interdisciplinary topics the PhD students came with different and/or mixed educational backgrounds. Some of them have a clear AI profile, while others came from the corresponding discipline, while some have mixed degrees in both (e.g. a BSc in Physics and MSc in AI, etc.). Each of the PhD students will need to develop and apply modern AI and Machine Learning techniques to tackle their problem. The appointed PhD students are Fiona Lippert (IBED), Jim Boelrijk (HIMS), David Ruhe (API), Benjamin Miller (IoP) and Teodora Pandeva (SILS).
AI4Science is embedded within the Amsterdam Machine Learning lab (AMLab).
Bernd Ensing is scientific director (HIMS) and Patrick Forré is lab manager (IvI) of AI4Science.