If you are an undergraduate student and would like some
research experience, please send email with your transcript and CV, and
indicate which papers of mine you have read and why they
interest you.
If I agree to work with you, the first semester will be a for-credit, unpaid, CS 397 course; the grade for the 397 will be based on what you achieved, and how it is written up in a final report. Note that this grade will be based in part on the writing quality (30%) as well as content (see this page for some advice about writing).
Also see No, You Don't Get an A for Effort.
Finally, please also note that I expect all students who work with me to have strong
programming skills in several languages, and to have completed
CS 222, 225, 361, and 374, with grades not lower than A-.
Research in Bioinformatics
My main research is focused on
algorithmic problems in computational biology with the aim of developing methods that biologists will use and that will have transformative accuracy and scalability.
Some of this work is summarized in
Philosophical Transactions of the Royal Society B, but see also
the extended version in
a preprint, "Recent Progress on Methods for Estimating and Updating Large Phylogenies".
Part of this work involves mathematics (to understand the theoretical guarantees of the methods I develop, and of other methods), but part of it is also empirical (to understand performance on data). So implementation and testing is very important. All of my methods are a combination of graph algorithms and machine learning or statistical learning. My work in machine learning in particular involves the development of novel ensemble methods, using phylogenetic estimation to guide the design of the ensemble. The machine learning I do is largely unsupervised or semi-supervised learning, largely because there is very limited reliable labeled data in my field; as a result, I do not work in deep learning. Mathematical proofs are part of what I do, but my focus on empirical performance (on data, in other words) drives my research.
My current work is on
large-scale and complex estimation problems in
phylogenomics (genome-scale phylogeny estimation),
multiple sequence alignment,
and
metagenomics.
I very much like collaborating with biologists, and have
worked with the Avian Phylogenomics Project and the
Thousand Plant Transcriptome project, among others.
Finally, I will hold a workshop on large-scale phylogenetics and
multiple sequence alignment at the NSF-funded Institute for Mathematical
and Statistical Innovation August 11-14, 2025; see
this page
Research in Network Science
I have a new interest in
Network Science,
and I
collaborate with
George
Chacko.
Our work focuses in two main directions:
(1) understanding the organization of scientific communities, and especially emerging trends in biomedical research and
(2) developing novel clustering methods that enable discovery from citation networks.
Among the highlights of this collaboration with George Chacko are two papers
we published in
Quantitative Science Studies (part of MIT press):
(1)
Bradley et al.
in
in which we identify
model misspecification as a problem for a prior
publication
published in Science, and
Wedell et al.,
where we propose a new model and method for community detection based
on center-periphery structures,
and we apply it to a citation graph for the field of
extracellular vesicles.
We also have a new paper (accepted to PLOS Complex Systems, 2024) about
the failure for clustering methods to produce well-connected
clusters, see Park et al., Well-Connected Communities in Real-World Networks. Preprint available on arXiv (HTML)
Research in Historical Linguistics
Just as species evolve, so do languages, and the inference of the
evolutionary histories of different languages is of great interest to me.
Some of my early work in this area is via collaboration with
Don Ringe (Univ Pennsylvania), Steve Evans (Berkeley), and Luay
Nakhleh (Rice University). See our webpage at
historical linguistics.
|
Computational Phylogenetics:
An introduction to designing methods for phylogeny
estimation, published by Cambridge University Press
(and available for purchase at Amazon and
as an E-book at Google Play).
Errata are posted as I find them.
The image of the Monterey Cypress is there because of
the NSF-funded CIPRES project,
whose purpose was to develop the methods and computational
infrastructure to improve large-scale phylogeny estimation.
Why I wrote this book.
I dedicated the book to
my PhD advisor
Gene Lawler,
who died in 1994; see
this memorium
(published in the Journal of Computational Biology,
10 Jun 2009)
that I co-authored
with Dan Gusfield, David Shmoys, and Jan Karel Lenstra
about Gene.
Bioinformatics and Phylogenetics:
Seminal Contributions of Bernard Moret, published by
Springer.
This book is a
Festschrift for Bernard Moret,
who retired from EPFL in December 2016.
The book contains a collection of self-contained chapters
that can be used for an advanced course in
computational biology and bioinformatics.
Current Funding:
-
Collaborative Research: OAC Core: Cyber-Infrastructure for Community Detection, Extraction, and Search in Large Networks,
NSF CISE/OAC 2402559,
July 15, 2024 to June 30, 2027.
PI: Warnow. Co-PI: George Chacko. (PI at NJIT: David Bader)
Total funding: $398,000 to UIUC.
- IIBR Informatics: Advancing Bioinformatics Methods using Ensembles of Profile Hidden Markov Models,
funded by NSF grant 2006069,
beginning August 15, 2020.
This project (joint with Jian Peng) will
extend the theory and foundations of ensembles of profile HMMs,
and use them for protein structure and function prediction.
-
Collaborative Research: PPoSS: LARGE: General-Purpose Scalable Technologies for Fundamental Graph Problems,
NSF grant 2316233, 2023-2028.
This is a collaborative grant led by UIUC (PI: Torellas,
Co-PIs: Charith Mendis, Hanghang Tong, Karrie Karahalios, and Tandy
Warnow).
Total funding: $3,900,000.
-
Meso-scale Structures in Large Graphs: Finding Communities with Substructure,
PI: Warnow, G. Chacko, C. Kirshman (Insper), and F. Ayres (Insper). 2023-2028. Total
funding: $360k awarded to date.
Supported by the
Insper-Illinois Collaboration.
Recent NSF funding has supported
work in metagenomics,
phylogenomics,
and graph-theoretic algorithms.
All of these are still very active research areas in my group.
I also recently benefited from support
of the John P.
Simon Guggenheim Foundation, and
earlier support from
the
David and Lucile Packard Foundation,
the
Radcliffe
Institute for Advanced Study at Harvard University,
the
Program
for Evolutionary Dynamics at Harvard University,
and Microsoft Research, New England.
The Grainger Distinguished Chair in Engineering is
funded through the
Grainger Engineering Breakthroughs Initiative, which is supporting development of
research in Big Data and Bioengineering at UIUC.
I am grateful to the
National Science Foundation for its
continuous support since 1994.
See
this page
for completed projects funded by NSF, starting in 2001.
"Plus de détails, plus de détails, disait-il à son
fils, il
n'y a d'originalité et de vérité que dans les
détails..."
-- Stendhal, Lucien Leuwen (a quote much loved by my stepfather,
Martin
J. Klein, and an essential guide for all scholarship).
Contact info
