UBC Computer Science welcomes the latest additions to our department, four new assistant professors.
William J. Bowman earned his PhD from Northeastern University in 2018. Broadly speaking, he is interested in making it easier for programmers to communicate their intent to machines, and preserving that intent through compilation. More specifically, his research interests include secure and verified compilation, dependently typed programming, verification, meta-programming, and interoperability. His recent work examines type-preserving compilation of dependently typed programming language like Coq, a technique that can enable preserving security and correctness invariants of verified software through compilation and statically enforcing those invariants in the low-level (assembly-like) code generated by compilers.
Helge Rhodin was previously a lecturer at EPFL, postdoctoral researcher in the Computer Vision Lab of Pascal Fua, and obtained his PhD in 2016 from Saarland University, working in the GVV group of Christian Theobalt at the Max-Planck-Institute for Informatics. His research interests range from 3D computer vision, over machine learning, to computer graphics and augmented reality. With the aim of enabling tight and rich, yet natural and non-intrusive computer-human interaction, he advances 3D vision algorithms to yield high-quality dynamic reconstructions of our everyday environment from plain video input. The latest VR and AR devices offer incredible display capabilities; his 3D vision projects complement them to aid mutual human-computer interaction in our everyday life.
Andrew Roth was most recently from University of Oxford Big Data Institute with affiliations to the University of Oxford Department of Statistics and Ludwig Institute for Cancer Research, after obtaining his PhD at UBC in the Sohrab Shah Lab for Computational Cancer Biology. He is a joint appointment across the Computer Science and Pathology departments, and is also a scientist in the Department of Molecular Oncology at the British Columbia Cancer Agency. His research is primarily focused on the development and application of statistical and machine learning methods for analysing cancer omics data. The methods he develops leverage probabilistic graphical models and non-parametric Bayesian methods to extract biologically interpretable quantities from complex datasets. He is also interested in developing computationally efficient inference algorithms to fit these models. He is particularly interested in variational and sequential Monte Carlo methods. These two themes support the ultimate goal of his research which is to understand evolutionary cancer biology.
Robert Xiao received his PhD in 2018 from the Human-Computer Interaction Institute at Carnegie Mellon University, advised by Chris Harrison and Scott Hudson, and before that, a BMath in Computer Science and Combinatorics & Optimization at the University of Waterloo. He combines his background in computer science and mathematics to craft novel interactive technologies driven by sensors, machine learning and computer vision. These technologies range from improving touchscreen input, to novel motion tracking systems, on-world projected interfaces, and much more. Alongside his research interests, he routinely competes in DEF CON Capture the Flag (1st place 2016, 2017, 2019) and other security contests.