Maxwell Libbrecht
Associate Professor
Computing Science
Areas of interest
Research Interests:
machine learning
probabilistic modeling
unsupervised learning
submodular optimization
genomics
gene regulation
Teaching Interests:
machine learning
probability and statistics
data structures and algorithms
discrete math
Education
- PhD, Computer Science, University of Washington, 2016
- BSc, Computer Science, Stanford University, 2011
Courses
This instructor is currently not teaching any courses.
Selected Recent Publications
- Maxwell W. Libbrecht, William S. Noble. Machine learning applications in genetics and genomics. Nature Reviews Genetics, 16: 321-332, 2015. http://dx.doi.org/10.1038/nrg3920
- Maxwell W. Libbrecht, Ferhat Ay, Michael M. Hoffman, David M. Gilbert, Jeffrey A. Bilmes, and William S. Noble. Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression. Genome Research, 25: 544-557, 2015. http://doi.org/10.1101/gr.184341.114
- Maxwell W. Libbrecht, Michael M. Hoffman, Jeffrey A. Bilmes, William S. Noble. Entropic graph-based posterior regularization. Proceedings of the International Conference on Machine Learning (ICML) 2015. http://jmlr.org/proceedings/papers/v37/libbrecht15.html
- Maxwell W. Libbrecht, Jeffrey A. Bilmes, William S. Noble. Eliminating redundancy among protein sequences using submodular optimization. http://dx.doi.org/10.1101/051201