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Tandy Warnow

Tandy Warnow
Tandy Warnow

Tandy Warnow

Founder Professor in Engineering
(217) 300-3087
3235 Siebel Center for Comp Sci

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Biography

Professional development: Warnow received her PhD in Mathematics at UC Berkeley (1991) under the direction of Gene Lawler, and did postdoctoral training with Simon Tavare and Michael Waterman at USC (1991-1992). After spending a year in the Discrete Algorithms Group at Sandia National Laboratories in Albuquerque, NM, she joined the Computer and Information Sciences Department faculty at the University of Pennsylvania. Tandy joined the faculty at the University of Texas in 1998, where she was the David Bruton Jr. Centennial Professor of Computer Science. She joined the Uniersity of Illinois at Urbana-Champaign as a Founder Professor of Engineering, and is now Associate Head for Computer Science; she also has affiliate faculty appointments in s Bioengineering, Electrical and Computer Engineering, Mathematics, Statistics, and several biology departments.

Awards: She received the National Science Foundation Young Investigator Award in 1994, the David and Lucile Packard Foundation Award in Science and Engineering in 1996, a Radcliffe Institute Fellowship in 2006, and a Guggenheim Foundation Fellowship for 2011. She was elected a Fellow of the Association for Computing Machinery (ACM) in 2015 and of the International Society for Computational Biology (ISCB) in 2017.

Teaching: At the undergraduate level, Warnow teaches courses in discrete mathematics and algorithm design and analysis, and use problems from computational biology to demonstrate the applications of these skills and techniques to real world problems. At the graduate level, Warnow teaches CS 581: Algorithmic Computational Genomics. The main focus of CS 581 is on phylogeny (evolutionary tree) estimation, but the course also covers the related problems of computing multiple sequence alignments, genome assembly, and analyzing microbiomes. Students will learn the mathematical and computational foundations in these areas, read the current literature, and do a team research project. The techniques involved include discrete algorithms, graph theory, simulations, and probabilistic analysis of algorithms. Course website: http://tandy.cs.illinois.edu/581-2018.html.

Leadership roles: Warnow has had several leadership roles in international consortia, including Genome 10K, the Avian Phylogenomics Project and the Thousand Plant Transcriptome Initiative. She was also the Director of the CIPRES (Cyber-Infrastructure for Phylogenetics Research) project (funded by a large ITR grant from NSF), which had more than 10 universities around the country, trained more than 50 PhD students (including many of the computer scientists now working in computational biology), and led to the establishment of the CIPRES Gateway. She also chaired the NIH study section for Biodata Management and Analysis (BDMA), and was the main program officer at NSF for the BIg Data solicitation.

Research contributions: Warnow's main research is in algorithms for statistical estimation problems in computatiional biology and historical linguistics. Among her major contributions are SATe, PASTA, and UPP, three different methods for multiple sequence alignment that provide high accuracy on large datasets (up to 1,000,000 sequences). She also contributed ASTRAL, a method for species tree estimation from multi-gene datasets, that provides high accuracy in the presence of gene tree heterogeneity due to incomplete lineage sorting; ASTRAL is now the dominant method for species tree estimation on large datasets that provides statistical guarantees (i.e., statistical consistency under the multi-species coalescent model). Another major contribution was the development of the "short quartet methods" (with Peter Erdos, Laszlo Szekely, and Mike Steel) for phylogeny estimation, which provided the first methods with polynomial sample complexity for phylogeny estimation. Warnow also developed a phylogenetically-based ensemble method using profile Hidden Markov Models that improves accuracy (both precision and recall) for a number of different bioinformatics problems, including protein sequence classification, metagenomic taxon identification, and ultra-large multiple sequence alignment. Finally, Warnow's collaboration with linguist Don Ringe (Univ of Pennsylvania) led to a rigorous approach to inferring evolutionary histories (both trees and networks) for natural languages, and settled several outstanding conjectures for Indo-European.

Current research: Warnow's current work is developing novel machine learning and statistical learning approaches for large-scale phylogenomics (i.e., species tree estimation using genome-scale datasets), metagenomics, protein classification, and bibliometrics.  An exciting new development in her lab is the divide-and-conquer approach, using Disjoint Tree Merger methods, that enable computationally intensive methods to scale to large datasets. The best of these methods (e.g., TreeMerge and GTM) are the work of her current PhD students, and have been shown to dramatically reduce running time without reducing accuracy.

Courses Taught

  • BIOE 298 - Intro Bioinformatics for BIOE
  • BIOE 498 - Intro Bioinformatics for BIOE
  • BIOE 540 - Algorithmic Genomic Biology
  • BIOE 598 - Algorithmic Genomic Biology
  • CS 173 - Discrete Structures
  • CS 196 - Freshman Honors
  • CS 466 - Introduction to Bioinformatics
  • CS 581 - Algorithmic Genomic Biology
  • CS 598 - Algorithmic Genomic Biology