Hi and welcome! I am Fabian - great to have you here!
I am a final-year 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 interest lies in generative modelling, and intersects with probabilistic deep learning, causal inference, Bayesian inference, unsupervised representation learning and its applications in health.
Recently, my research analysed why U-Nets are a useful inductive bias in diffusion models (NeurIPS 2023), connections between hierarchical variational autoencoders and diffusion processes, as well as U-Nets and Wavelets (NeurIPS 2022 oral), and variational autoencoders with a structured prior for clustering to find multiple partitions of high-dimensional data (NeurIPS 2021). I also studied generalising the propensity score theory to balancing scores in matching for treatment effect estimation in causal inference (AISTATS 2022). In the summers of 2022 and 2023, I interned with the Amazon Web Services AI Lab in Berlin, and Microsoft Research in Cambridge.
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 (Best Paper Award at TAROS 2019 - the UK’s largest robotics conference), 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 industrial 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
PhD in Statistical Machine Learning
University of Oxford
MSc in Computer Science, 2018
Imperial College London
BSc+MSc in Engineering, 2015+2016
Karlsruhe Institute of Technology