Murray Patterson

Murray Patterson is an Assistant Professor in the Department of Computer Science at Georgia State University. His academic journey includes a Ph.D. from the University of British Columbia (2012), followed by postdoctoral research at Inria (France), CWI (Netherlands), Lyon's Evolutionary Biology Lab, and Milan's Experimental Algorithmics Lab. He previously held a visiting position at Fairfield University before joining Georgia State in 2020.

Education:

• B.C.S., Acadia University, 2003
• M.S., Computing Science, Simon Fraser University, 2006
• Ph.D., Computer Science, University of British Columbia, 2012

Research Interests: Focuses on algorithmic approaches to bioinformatics challenges, particularly evolutionary biology and cancer genomics. Key areas include:
- Evolutionary tree construction and dynamics analysis
- Haplotype assembly and cancer cell progression modeling
- Machine learning for molecular sequence classification
- Privacy-preserving federated learning methods
- Interdisciplinary applications of computational geometry and kernel methods.

Research Trends: Recent work emphasizes scalable tools for analyzing long-read sequencing data, developing novel embeddings for biological sequences (e.g., Hist2Vec, Spike2Vec), and integrating geometric approaches (Bezier curves, Poincaré distances) into bioinformatics workflows. The 2025 publications highlight advancements in privacy-enhanced federated learning frameworks and kernel-based sequence analysis techniques.

Awards & Grants: No explicitly listed awards. His work has been supported by grants for tumor phylogeny pipelines and pandemic response initiatives.

Labs & Collaborations: Active in the Experimental Algorithmics Lab (algolab.eu) and affiliated with Georgia State's bioinformatics research community. Develops open-source tools like Plastic for tumor phylogeny benchmarking and PDB2Vec for 3D protein structure analysis.