Maxwell Libbrecht

Maxwell Libbrecht is an Associate Professor and Michael Smith Health Research Scholar at the School of Computing Science, Simon Fraser University. His research focuses on machine learning methods for genomics, particularly applying probabilistic graphical models, deep neural networks, and optimization techniques to analyze genomic datasets like DNA sequences, epigenetic data (ChIP-seq, ATAC-seq), and single-cell data (flow cytometry, single-cell genomics). He holds a PhD in Computer Science from the University of Washington (2016) and a BSc from Stanford University (2011).

His research interests include machine learning, probabilistic modeling, unsupervised learning, submodular optimization, genomics, and gene regulation. Teaching interests span machine learning, probability and statistics, data structures, and discrete mathematics. His group actively recruits students at all levels (undergraduate, masters, PhD) and collaborates with SFU's Libbrecht Lab.

Key research contributions include methods like CANDI for genomic data imputation, VSS-Hi-C for chromatin contact analysis, and Segway for chromatin state segmentation. His work has been recognized with the Michael Smith Health Research Scholar award and Best Paper Award.