The primary objective of my research is to produce new algorithms and software that can dramatically improve phylogenetic analysis (whether in linguistics or in biology), as tested in simulation or on real data. Theoretical research is often done at the same time, using probability theory to predict performance under Markov models of evolution, but then testing these predictions in simulation. Mathematical modelling is also part of the work. If you are a student who loves to design algorithms, likes the challenge of developing good heuristics for NP-hard optimization problems, loves to program, and enjoys collaborations (especially with scientists!), you may find this research area fun and rewarding. Absolutely no background in biology or linguistics is required. Research in my lab requires strong skills in algorithm design and analysis and software development. In addition, excellent interpersonal skills, oral and written communication skills, and a passion for research are also necessary. Overall, the required technical skills or coursework can be described by:

- Strong programming skills in several programming languages, such as Java, C/C++, Python, Perl and R, and ability to learn others (essential)
- Upper division course in algorithm design and analysis (essential)
- Upper division courses in graph theory, statistics, and probability theory (necessary, but can be obtained after joining)

I work very closely with all of my graduate students. The first semester is a rotation, generally spent on a specific research project in collaboration with other students, so that the new student can find out about the research area. For those students who have not taken my graduate course, the first semester also involves doing the homework problems from the textbook. After a semester as a rotation student, the student can decide about continuing to do a PhD in my lab. Please feel free to talk with my current or former students about working with me; the list of students is available here.

- I am writing a textbook in computational phylogenomics; the current draft is available here.
- Large-scale multiple sequence alignment and phylogeny estimation, T. Warnow, 2013, in Models and Algorithms for Genome Evolution, Springer Computational Biology Series, C. Chauge, N. El-Mabrouk, and E. Tannier, Editors.
- Disk Covering Methods: improving the accuracy and speed of large-scale phylogenetic analyses by T. Warnow (appeared as ``Large-scale phylogenetic reconstruction, in S. Aluru (editor), Handbook of Computational Biology, Chapman & Hall, CRC Computer and Information Science Series, 2005).
- The Computational Phylogenetics in Historical Linguistics webpage.
- My list of papers (most downloadable) is online.