Anthony Christidis, PhD

Anthony Christidis is a computational scientist at the Core for Computational Biomedicine, where he is a member of multiple research teams. Originally from Canada, he earned his PhD in Statistical Machine Learning from the University of British Columbia (UBC) and a MSc in the same field from the University of Toronto. During his doctoral studies, he developed a new ensemble learning framework to model high-dimensional data which resulted in multiple publications in computational statistics journals. Following his PhD, Dr. Christidis was a Postdoctoral Research Fellow in the Department of Statistics at UBC where he developed new robust computational methods for the analysis of multi-omics data. He has also taught undergraduate and graduate courses in probability, statistics, data science and signal processing at UBC. Dr. Christidis regularly publishes software libraries implementing the statistical and computational methods he develops, and he has held various software development jobs in research institutes and in collaboration with the private sector. His research interests include machine learning, optimization, scientific computing, and the application of computational methods to single-cell and RNA-seq data.