Faculty Directory
Madhav Mani

Associate Professor of Engineering Sciences and Applied Mathematics

Contact

2145 Sheridan Road
Tech
Evanston, IL 60208-3109

Email Madhav Mani

Website

Madhav Mani Research

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Departments

Engineering Sciences and Applied Mathematics

Affiliations

PhD Program in Interdisciplinary Biological Sciences

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Education

Ph.D Applied Mathematics, Harvard University, Cambridge, MA

S.M. Engineering Sciences, Harvard University, Cambridge, MA

Masters of Advanced Studies in Mathematics and Theoretical Physics, Cambridge University, England

M.A. in Mathematics and Theoretical Physics, Trinity Hall, Cambridge University, England

B.A. in Mathematics and Theoretical Physics, Trinity Hall, Cambridge University, England


Research Interests

Vision: Mathematics is an almost unreasonably powerful language to describe and dissect natural phenomena. Wigner's article poetically conveys the sense of awe that many of us feel as mathematical scientists. However, it is remarkable, by and large, how ineffectively mathematics has been leveraged in furthering our understanding of Life. Mathematics isn't just a convenient language to communicate models of how some little corner of Life works, at its most powerful it provides a general framework that organizes and illuminates a vast diversity of phenomena. Mathematics, and mathematical scientists, achieve this through abstraction. And it is through abstraction that general and simplifying principles can be distilled -- As with Picasso's Bulls. What new abstractions must we seek out to deepen our understanding of Life?

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What we do: Our group pursues lines of inquiry where we attempt to develop novel mathematical abstractions that provide insights into biological phenomena and data. Precisely by virtue of our pursuit of discovering general mathematical abstractions, we are compelled to work on a diversity of biological phenomena that have been classified by the community into distinct and unrelated categories. These include organismal development, cellular physiology and structure, and ecological dynamics. 

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How we do it: These mathematical abstractions are pursued working closely with modern biological data. And, thus, data-driven and AI approaches are a large part of the algorithms we use and develop. Pairing these approaches with the aesthetics and sensibilities of mathematics and theoretical physics is the middle ground we strive to inhabit. All our work is conducted within the context of long-term collaborations with experimental biology groups. 

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Our scientific vision is a corollary to a human vision of helping young scientists enjoy the pursuit of mathematics and science, developing their talents and tastes.  



Significant Recognition

  • Simons Postdoctoral Fellowship, 2010 - 2013
  • Derek Bok Undergraduate Teaching Award, Harvard University, 2009
  • Robert L. Wallace Prize Fellowship, Harvard University, 2007 - 2008

Selected Publications

  • Pham, An T.; Mani, Madhav; Wang, Xiaozhong; Vafabakhsh, Reza, Multiscale biophysical analysis of nucleolus disassembly during mitosis, Proceedings of the National Academy of Sciences of the United States of America (2024).
  • Rogers, Crystal D.; Amemiya, Chris; Arur, Swathi; Babonis, Leslie; Barresi, Michael; Bartlett, Madelaine; Behringer, Richard; Benham-Pyle, Blair; Bergmann, Dominique; Blackman, Ben; Brown, C. Titus; Browne, Bill; Camacho, Jasmin; Chabu, Chiswili Yves; Chow, Ida; Cleaver, Ondine; Cool, Jonah; Dennis, Megan Y.; Dickinson, Alexandra Jazz; Di Talia, Stefano; Frank, Margaret; Gillmor, Stewart; Haag, Eric S.; Hariharan, Iswar; Harland, Richard; Husbands, Aman; Jerome-Majewska, Loydie; Koenig, Kristen; Labonne, Carole; Layden, Michael; Lowe, Chris; Mani, Madhav; Martik, Megan; McKown, Katelyn; Moens, Cecilia; Mosimann, Christian; Onyenedum, Joyce; Reed, Robert; Rivera, Ajna; Rokhsar, Dan; Royer, Loic; Rutaganira, Flora; Shahan, Rachel; Sinha, Neelima; Swalla, Billie; Van Norman, Jaimie M.; Wagner, Daniel E.; Wikramanayake, Athula; Zebell, Sophia; Brady, Siobhán M., Pluripotency of a founding field, Development (Cambridge) (2024).
  • Razo-Mejia, Manuel; Mani, Madhav; Petrov, Dmitri, Bayesian inference of relative fitness on high-throughput pooled competition assays, PLoS computational biology (2024).
  • Farrell, Spencer; Mani, Madhav; Goyal, Sidhartha, Inferring single-cell transcriptomic dynamics with structured latent gene expression dynamics, Cell Reports Methods (2023).
  • Freedman, Simon L.; Xu, Bingxian; Goyal, Sidhartha; Mani, Madhav, A dynamical systems treatment of transcriptomic trajectories in hematopoiesis, Development (Cambridge) (2023).
  • Johnson, Eric M.; Kath, William; Mani, Madhav, EMBEDR, Patterns (2022).
  • Gowda, Karna; Ping, Derek; Mani, Madhav; Kuehn, Seppe, Genomic structure predicts metabolite dynamics in microbial communities, Cell (2022).
  • Gallagher, Kevin D.; Mani, Madhav; Carthew, Richard W., Emergence of a geometric pattern of cell fates from tissue-scale mechanics in the Drosophila eye, eLife (2022).