Research Experiences for Undergrads in the Warnow Lab

Research Overview

My research is in three areas: computational biology, scientometrics, and historical linguistics. I enjoy working with undergraduates, but I require that students have completed a graduate course in these topics (CS 581: Algorithmic Genomic Biology or CS 598: Computational Scientometrics). Research in my lab for these areas involves algorithm design and implementation, so students who are strong programmers and meticulous experimentalists are welcome. However, in all these cases, there is required coursework that you must have before working with me, as indicated below. Thus, if you have not completed the required coursework, please understand that I will ask you to complete the coursework before we can begin working together. You will also need to provide the information requested in the "How to apply" section, listed below.

Scientometrics. I work with CS Professor George Chacko in method development for scientometrics. Required coursework: CS 598 (Fall 2022) with George Chacko (I am co-teaching). Also: CS 361 and 374, STAT 400 and 410, and at least one of CS 412, 446, 498 (Applied Machine Learning)
Computational biology research. My research combines mathematics, computer science, probability, and statistics, in order to develop algorithms with improved accuracy for large-scale and complex estimation problems in phylogenomics (genome-scale phylogeny estimation), multiple sequence alignment, and metagenomics. Required coursework: CS 581.

Interested in applying?

CS/ECE/Stats/Math students: Note that you do not need to know any biology to do this research! To succeed in this research you should have very strong programming skills (especially in Python), be interested in challenging yourself, good at working with others and also independently, and have strong communication skills (both oral and written).

Biology students: I am also interested in working with biology undergraduate students, as long as you have practical experience in phylogeny estimation or multiple sequence alignment, and your research interests involve doing analyses of this type. Let me know what you would like to do reseach on, and how it fits into my research.

Papers to read: Before you apply to work with me, please first read a few of my recent papers. The following is a good representative of the kinds of work I am doing (the parenthetical numbers refer to the number in my online publication list):

Multiple Sequence Alignment: PASTA (116 and 122), UPP (126), and MAGUS (183)
Ensembles of HMMs: SEPP (106), TIPP (121), UPP (126), and HIPPI (141)
Phylogenomics: ASTRAL (117 and 128), ASTRID (133), FastMulRFS (177), and DISCO (196)
Supertree methods: FastRFS (144) and SuperFine (105); see also a recent unpublished survey paper
Large-scale tree estimation using divide-and-conquer: DACTAL (112), INC (159,166,167), NJMerge (162,169), TreeMerge (168), GTM (175), and two survey papers (192,201)
Community finding in networks (applied to scientometrics): Center-Periphery Communities (203)

Possible research projects: I am open to many different possible research projects, but the most likely ones to succeed would be ones where you would work with one of my current PhD students. However, if you have something specific in mind, please let me know what you would like to do. Here are some types of research projects that I would be glad to support:

Designing new methods and testing existing methods for evolutionary tree estimation on large datasets using simulations
Re-analyzing some important phylogenomic datasets using new computational methods
Comparing divide-and-conquer strategies on ultra-large datasets, and designing new divide-and-conquer strategies
Implementing a GUI for phylogenomic software

Here are two examples of publications done by undergraduate students with me:

Kodi Collins (now Kodi Taraszka) worked on multiple sequence alignment with me, and published PASTA for Proteins. in Bioinformatics 2018. Kodi is now a PhD student in Computer Science at UCLA.
Thien Le worked on gene tree estimation with me, and published Using INC within Divide-and-Conquer in the Proceedings of Algorithms for Computational Biology, 2019. Thien is now a PhD student in EECS at MIT.

Doing a research project with me involves a substantial commitment. Research students have individual meetings (at least weekly, but more often when you are implementing and testing methods, or writing up results for publication) with me and one or more of my graduate students. It will also involve attendance in weekly group meetings. I provide mentoring in learning how to present research results, analyze data, read scientific papers, and design methods. In other words, being a research student involves a substantial effort and time commitment on your part, but also from me and from graduate students in my group.

How to apply

I receive many applications for research positions in my lab, and can only accept students who are serious about the effort involved and where there is a good fit with my group. Also note that I will not consider your application unless you have taken the required courses (CS 581 for students interested in computational biology, and CS 598: Computational Scientometrics for students interested in scientometrics). Please send me an email with your current transcript, and an answer to the following questions:

Have you taken the required courses (CS 581 for computational biology students, and CS 598: Computational Scientometrics) for those interested in scientometrics)? If so, provide your transcript (unofficial is fine).
When do you expect to graduate with your undergraduate degree?
Do you want to go to graduate school? If so, would this be in Computer Science or some other field? Would it be for a PhD or a MS? What are your career goals?
Do you want to do an undergraduate thesis? Are you considering this research as potential thesis project?
Why do you want to do a research project with me?
Which of my papers have you read? (if you haven't read any of the papers, please read some from the last three or so years, and let me know which papers you liked and why.)
Do you prefer theory (and in particular proving theorems about methods) or developing, implementing, and testing methods on data? (If you like both, that's fine.)
What have your favorite courses been so far, and why?
What programming languages are you most comfortable with?
How comfortable are you with learning material on your own?
How comfortable are you with collaborating with others?
How comfortable are you with taking existing codes and fixing errors or refactoring them?
Practical issues:
- Do you need to get paid for your research? Or would getting course credit be enough?
- How many hours a week do you want to work on a research project with me? Would you want to work during the summer?
- Finally, are you a U.S. citizen or permanent resident? (This impacts sources of funding.)

Summer 2019 REU students

During the summer 2019 semester, I worked with 10 undergraduate students (all from UIUC). These REU students learned the mathematical foundations of the material, which is covered in my textbook. In addition, they looked at the lectures for CS 581, and did modified homeworks (suitable for undergrads), which are available at this page. Finally, they did some research projects, which are described in my notes on first projects.

My textbook: Computational Phylogenetics: An introduction to designing methods for phylogeny estimation, published by Cambridge University Press.