Hi and welcome! I am Fabian - great to have you here!

I am a third year PhD student in Statistical Machine Learning in the OxCSML group at University of Oxford, supervised by Prof. Chris Holmes and Prof. Arnaud Doucet. I am also a Graduate Teaching and Research Scholar in Computer Science at Oriel College, University of Oxford, teaching maths courses.

My research interests lie in probabilistic deep learning, generative modelling, causal inference, and applications in health.

Recently, I have worked on analysing the regularisation property of U-Nets, which are widely used in generative modelling, and hierarchical variational autoencoders (NeurIPS 2022 oral). I also studied generalising the propensity score theory to balancing scores in matching for treatment effect estimation in causal inference (AISTATS 2022), and variational autoencoders for clustering to find multiple partitions of high-dimensional data (NeurIPS 2021). In summer 2022, I interned with the Amazon Web Services AI Lab in Berlin, Germany, advised by Dr. Jan Gasthaus and Richard Kurle.

Before joining Oxford for my PhD, I worked with Prof. Andrew Davison in computer vision and robotics at the Dyson Robotics Lab, and with Dr. Petar Kormushev at the Robot Intelligence Lab, both at Imperial College London. I also worked with Prof. Artur Dubrawski on machine learning for health at the Auton Lab at Carnegie Mellon University. Selected publications include a comparison of view-based and map-based semantic labelling in real-time SLAM systems (ICRA 2020), an exoskeleton for teleoperation called DE VITO (TAROS 2019 - the UK’s largest robotics conference, Best Paper Award), a software architecture and play fetch demo for Robot DE NIRO (journal Frontiers in Robotics and AI; IROS workshop (spotlight)) and haemorrhage diagnosis with recurrent neural networks at the NeurIPS 2018 ML4H workshop (spotlight).

I studied Computer Science (MSc) at Imperial College London, and Engineering (BSc+MSc) at Karlsruhe Institute of Technology in Germany. During my degrees, I studied at and visited Tsinghua University (清华大学) in Beijing, Shanghai Jiao Tong University (上海交通大学), the University of Oxford, Singapore Management University, and Carnegie Mellon University in the US.

I enjoy playing the guitar, singing and racket sports. I speak German, English and Chinese.

Do reach out to me if my research is of interest to you - I’m always happy to chat about potential collaborations!

Contact: fabian.falck ‘at’ stats.ox.ac.uk

News

• Our paper on U-Nets and hierarchical VAEs has been accepted at NeurIPS 2022 (oral). I’m really excited about this work with fantastic collaborators!
• I received an Enrichment Award at The Alan Turing Institute, the UK’s national institute for AI. Looking forward to spending part of my PhD studies in London!
• In summer 2022, I will intern at Amazon Web Services AI Labs in Berlin, Germany, working with Jan Gasthaus and Richard Kurle.
• Our paper on a theory extending propensity score matching via balancing scores has been accepted at AISTATS 2022.
• I’m delighted to serve as workflow chair for ML4H 2021 together with Yuyin Zhou, working on all things submissions.
• Our paper on multi-partition clustering of high-dimensional data through variational autoencoders with a structured prior has been accepted at NeurIPS 2021.