Research Experiences for Undergrads in the Warnow Lab

Research Overview

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, metagenomics, and historical linguistics. I am a big fan of Blue Waters, and have benefitted from two allocations. Click here for the 2017 annual report for my Blue Waters allocation on algorithms for big data phylogenomics, proteomics, and metagenomics. Click here or here for more about my research and the students I work with, and here for a brief biosketch. I welcome strong undergraduate students currently enrolled at UIUC from computational disciplines (CS, ECE, Statistics, and Mathematics) who are keenly interested in research, ambitious, and either planning to go to graduate school or considering this seriously. I can supervise projects that include testing and developing new computational methods in phylogenomics, analysis of biological datasets using different methods, etc. However, I do not take students who are in their senior year except under very unusual circumstances (e.g., when there is a record of prior work on very similar projects). Also, although I do sometimes offer summer research opportunities, these are only for students already doing research with me.

Current REU students

I am currently working with 10 undergraduate students (all from UIUC). These REU students learn the mathematical foundations of the material, which is covered in my textbook. In addition, they are looking at the lectures for CS 581, and doing modified homeworks (suitable for undergrads) at this page. Finally, they are doing initial projects, which are described in my notes on first projects.

All REU students should obtain my textbook Computational Phylogenetics: An introduction to designing methods for phylogeny estimation, published by Cambridge University Press.

Interested in applying?

NSF funding: I have some REU funding available for qualified undergraduate students from one of my National Science Foundation grants (see this page). This REU funding can support any research relevant to constructing and using multiple sequence alignments, including for phylogenetic tree (i.e., evolutionary tree) estimation, protein structure and function prediction, metagenomic taxon identification, etc. The only important restriction is that the funding is limited to U.S. citizens, nationals, and permanent residents. If you are a foreign student and not eligible for the REU funding, you can still do research with me.

CS/ECE/Stats/Math students: 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). You should already have completed CS 173 and be enrolled in (or have completed) CS 225. If you have completed 374 and 225, it would be great if you also took my graduate class CS 581, where I teach the basics of discrete algorithm design in computational biology, focusing on phylogenetics, multiple sequence alignment, and the applications of these tools in other problems in biological analysis (e.g., in metagenomics and protein structure prediction).

Biology students: REU support for undergrads in biology is also possible. Let me know what you would like to do reseach on, and how it fits into the overall objectives of my NSF grant (see this page). We might be able to make this work!

My textbook: Most people (even undergrads) who do research with me have taken my graduate course, CS 581, which I teach in the Fall semesters. If you haven't taken this course, you should read the textbook I wrote on Computational Phylogenetics, published by Cambridge University Press.

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 in my three active NSF projects (the parenthetical numbers refer to the number in my online publication list):

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:

As an example of an undergraduate research project, a former student (Kodi Collins) from CS 173 did research with me after completing 173, and published a paper: see PASTA for Proteins. She is now a PhD student in Computer Science at UCLA!

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. Please send me an email with your current transcript, and an answer to the following questions: