About the Keynote

In recent years, machine learning (ML) and artificial intelligence (AI) methods have begun to play a more and more enabling role in the sciences and in industry. In particular, the advent of large and/or complex data corpora has given rise to new technological challenges and possibilities. In his talk, Müller will touch upon the topic of ML applications in the sciences, in particular in neuroscience, medicine and physics. He will also discuss possibilities for extracting information from machine learning models to further our understanding by explaining nonlinear ML models. Finally, Müller will briefly discuss perspectives and limitations.

About the Speaker

Prof. Müller has been the chair of the Machine Learning department at Technical University Berlin since 2006 and became director of the Berlin Institute for the Foundations of Learning and Data (BIFOLD) in 2022 after serving as director for its predecessor institutes, the Berlin Big Data Center (BBDC) and the Berlin Center for Machine Learning (BZML) from 2014 and 2018, respectively. He serves in the editorial boards of IEEE Transactions on Neural Networks and Learning Systems and the Journal of Machine Learning Research, amongst others, and was awarded the prestigious Hector Science Award in 2023. Most recently Prof. Müller spent a Sabbatical at Google DeepMind, Berlin as a Principal Scientist.

About the Keynote

Advancements in AI are reshaping medical knowledge and practice, improving diagnostic accuracy and treatment efficiency. However, its integration also raises ethical and societal concerns, particularly regarding bias, fairness, and accountability. This presentation explores trustworthy AI as a key concept, focusing on the human, institutional, and societal dimensions, as well as trust as a dynamic and relational process, to ensure AI systems are not only technically reliable but also ethically robust and socially responsible.

About the Speaker

Dr. Melanie Goisauf is a social scientist specializing in the ethical and social/societal implications of artificial intelligence, biobanking, stakeholder engagement and governance. She is senior scientist at the European Infrastructure for Biobanking (BBMRI-ERIC), where she is involved in multiple research projects and serves on ethical advisory boards. Additionally, she leads the Ethics of AI Lab.

About the keynote

The talk will feature an introduction of digital pathology and its potential, illustrated by examples and challenges of translating research into practice. Specifically highlighting how the impact of AI and foundation models shapes research and product development and giving an outlook on future avenues.

About the Speaker

Maximilian (Max) Alber works in the intersection of artificial intelligence and healthcare. He is the Co-Founder and CTO of Aignostics, an AI company based in Berlin and New York that turns complex biomedical data into transformative insights for leading biopharma companies. Max currently leads the technology organization and overall ML strategy at Aignostics, with a focus on deriving insights for drug discovery, translational research, and clinical trials. Most recently, Max led development for Aignostics’ industry-leading foundation model for histopathology built in collaboration with Mayo Clinic.

About the keynote

Artificial intelligence (AI) approved for use with patients can dramatically improve their treatment while reducing the burden on doctors and nurses and cutting healthcare costs. Prof. Dr. Aldo Faisal aims to drive innovation through research and development in this area to meet the ever-growing needs of the healthcare sector. He wants to drive innovation through research and development in this field to meet our ever-growing healthcare needs. AI for health cannot be developed with “off-the-shelf” concepts, but requires a fundamental rethink. Dr. Faisal argues for a transdisciplinary approach that incorporates the latest developments in AI as well as insights into human decision-making, high levels of medical expertise and in-depth knowledge of regulatory and policy frameworks. In this lecture, he will illustrate his approach based on his current research. His credo is that the regulation of AI must take into account its constant learning, that political decisions must keep an eye on the rapid development in this field and that all those who contribute to AI-based solutions with their data should also benefit from it.

About the Speaker

Professor Aldo Faisal is the Professor of AI & Neuroscience at the Dept. of Computing and the Dept. of Bioengineering at Imperial College London. He was awarded a prestigious UKRI Turing AI Fellowship (£2 Mio including industry partners). Aldo is the Founding Director of the £20Mio. UKRI Centre for Doctoral Training in AI for Healthcare that aims to transform AI for Healthcare research and pioneer training 100 PhD and Clinical PhD Fellows. He also holds a Chair in Digital Health at the University of Bayreuth (Germany).At his two departments, Aldo leads the Brain & Behaviour Lab focussing on AI & Neuroscience and the Behaviour Analytics Lab at the Data Science Institute. He is Associate Investigator at the MRC London Institute of Medical Sciences and is affiliated faculty at the Gatsby Computational Neuroscience Unit (University College London). He was the first elected Speaker of the Cross-Faculty Network in Artificial Intelligence representing AI in College on behalf of over 200 academic members. Aldo serves as an Associate Editor for Nature Scientific Data and PLOS Computational Biology and has acted as conference chair, program/area chair, chair in key conferences in the field (e.g. Neurotechnix, KDD, NIPS, IEEE BSN). In 2016 he was elected into the Global Futures Council of the World Economic Forum. Aldo received a number of awards and distinctions, including Scholar of the German National Merit Foundation (Studienstiftung des Deutsche Volkes; Undergraduate & PhD), a PhD Fellow of the Böhringer-Ingelheim Foundation for Basic Biomedical Research, elections as a Junior Research Fellow at the University of Cambridge (Wolfson College), and a number of research prizes and award such as the Toyota Mobility Foundation $50,000 Research Discovery Prize in 2018, and together with the AI Clinician team the Rosetree Interdisciplinary Award (£300,000) in 2022. Aldo's lab featured regularly across global media (such as BBC, CNN, TED, TEDx, Wall Street Journal, Guardian, Financial Times , WIRED, Scientific American, New Scientist, etc.), e.g. in 2016 Scientific American voted his research on gaze-based control as 1st of 10 most transformative ideas of year. Dr Faisal's labs is operated as a borderless lab across UK and Germany. The UK lab at Imperial is located in the Royal School of Mines building and combine cross-disciplinary computational and experimental approaches to investigate how the brain and behaviour evolved to learn and control goal-directed behaviour. The neuroscientific findings enable the targeted development of novel technology for clinical and research applications (Neurotechnology) for a variety of neurological/motor disorders and amputees. Key techniques include on the computational side are data-driven methods from machine learning & stochastic modelling techniques and experimentally we use sensorimotor experiments, eye-tracking & kinematics (full-body, hands), non-invasive brain imaging (EEG, fNIRS), robotics (hand & arm robots). Dr Faisal's Behaviour Analytics lab located in the Data Science Institute objective is the data-driven analysis of human behaviour and pioneering development of methods & algorithms to move in a principled manner from Big Data to Big Knowledge. Keys goals are, understand and predict human behaviour from ubiquitous sensors & digital data, predict and evaluate human performance, Infer internal or cognitive state (stress, risk) of individuals from behavioural dynamics, develop behavioural biomarkers of physiological and psychological well-being and bottom-up analysis of group and social dynamics from the decisions of individuals.