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Smita Krishnaswamy

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Smita Krishnaswamy
Alma mater
Scientific career
FieldsComputer Science, Genetics, Machine Learning, Electronic Design Automation
InstitutionsIBM, Yale University
Thesis Design, Analysis and Test of Logic Circuits under Uncertainty  (2008)
Doctoral advisorIgor L. Markov, John P. Hayes

Smita Krishnaswamy is an American scientist and associate professor in genetics and computer science[1] at Yale University. She specializes in the development of machine learning techniques to analyze high-dimensional high-throughput biomedical data with applications in immunology, immunotherapy, cancer, neuroscience, developmental biology and health outcomes. She organized the Open Problems in Single-Cell Biology effort with the Chan Zuckerberg Initiative and remains a scientific advisor for the project.[2]

Education and early career

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Krishnaswamy obtained her Ph.D. in computer science and engineering from University of Michigan in 2008.[3] She then joined IBM's T.J. Watson Research Center as a scientist in the systems division, where she researched formal methods for automated error detection. Her Deltasyn algorithm was utilized in IBM System p and IBM System z high-performance server chips.[4]

Krishnaswamy switched her research efforts to biology and completed postdoctoral training in 2015 at Columbia University in the Department of Systems Biology, where she focused on learning computational models of cellular signaling from single-cell mass cytometry data.[5]

Awards and honors

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In 2022, Krishnaswamy's research, teaching and community work were honored by a FASEB Excellence in Science Award (Early-Career Investigator Award) from the Federation of American Societies for Experimental Biology funded by Eli Lilly and Company.[6]

In 2009, Krishnaswamy was the recipient of the European Design Automation Association's Outstanding Dissertation Award in the category "new directions in circuit and system test".[7]

In 2005, Krishnaswamy received a best-paper award from the Design Automation and Test in Europe conference for the paper of which she was the lead author.[8]

Publications

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Krishnaswamy co-authored a book published by Springer Verlag[9] and over 50 peer-reviewed publications, including journal papers in Nature Biotechnology,[10] Nature Protocols,[11] Nature Methods[12] Science,[13] Cell[14] and conference papers in International Conference on Machine Learning.[15]

References

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  1. ^ "Smita Krishnaswamy". Yale School of Engineering and Applied cience. Retrieved August 28, 2023.
  2. ^ "Meet the Team". Open Problems. Retrieved August 28, 2023.
  3. ^ "Smita Krishnaswamy". Mathematics Genealogy Project. Retrieved August 28, 2023.
  4. ^ Krishnaswamy, Smita; Ren, Haoxing; Modi, Nilesh; Puri, Ruchir (November 2009). "DeltaSyn: An efficient logic difference optimizer for ECO synthesis". ICCAD: 789–796. doi:10.1145/1687399.1687546. S2CID 5473395.
  5. ^ "Smita Krishnaswamy, Ph.D." Simons Foundation. 2017.
  6. ^ "Past Recipients". Federation of American Societies for Experimental Biology. Retrieved August 28, 2023.
    - "Krishnaswamy receives Excellence in Science Award". Yale Computer Science Department. September 8, 2022.
  7. ^ "EDAA Outstanding Dissertation Award recpients". EDAA. Retrieved August 28, 2023.[dead link‍]
  8. ^ Krishnaswamy, Smita; Viamontes, George F.; Markov, Igor L.; Hayes, John P. (2005). "Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices". DATE: 282–287.
    - "Best Paper Awards" (PDF). Retrieved August 12, 2023.
  9. ^ Krishnaswamy, Smita; Markov, Igor L.; Hayes, John P. (2012). Design, Analysis and Test of Logic Circuits Under Uncertainty. Springer. ISBN 978-90-481-9643-2.
  10. ^ ED Amir; KL Davis; MD Tadmor; EF Simonds; JH Levine; SC Bendall (2013). "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia". Nature Biotechnology. 31 (6): 545–552. doi:10.1038/nbt.2594. PMC 4076922. PMID 23685480.
    - KR Moon; D van Dijk; Z Wang; S Gigante; DB Burkhardt; WS Chen; K Yim (2019). "Visualizing structure and transitions in high-dimensional biological data". Nature Biotechnology. 37 (12): 1482–1492. doi:10.1038/s41587-019-0336-3. PMC 7073148. PMID 31796933.
  11. ^ ER Zunder; R Finck; GK Behbehani; ED Amir; S Krishnaswamy (2015). "Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm". Nature Protocols. 10 (2): 316–333. doi:10.1038/nprot.2015.020. PMC 4347881. PMID 25612231.
  12. ^ M Amodio; D Van Dijk; K Srinivasan; WS Chen; H Mohsen; KR Moon (2019). "Exploring single-cell data with deep multitasking neural networks". Nature Methods. 16 (11): 1139–1145. doi:10.1038/s41592-019-0576-7. PMC 10164410. PMID 31591579.
  13. ^ S Krishnaswamy; MH Spitzer; M Mingueneau; SC Bendall; O Litvin (2014). "Conditional density-based analysis of T cell signaling in single-cell data". Science. 346 (6213): 1250689. doi:10.1126/science.1250689. PMC 4334155. PMID 25342659.
  14. ^ D Van Dijk; R Sharma; J Nainys; K Yim; P Kathail; AJ Carr; C Burdziak (2018). "Recovering gene interactions from single-cell data using data diffusion". Cell. 174 (3): 716–729. doi:10.1016/j.cell.2018.05.061. PMC 6771278. PMID 29961576.
  15. ^ Matthew Amodio; Smita Krishnaswamy (2018). "MAGAN: Aligning Biological Manifold". ICML. 2018: 215–223. arXiv:1803.00385.
    - Alexander Tong; Jessie Huang; Guy Wolf; David van Dijk; Smita Krishnaswamy (2020). "TrajectoryNet : A Dynamic Optimal Transport Network for Modeling Cellular Dynamics". ICML. 2020: 9526–9536. arXiv:2002.04461.
    - Alexander Tong; Guillaume Huguet; Amine Natik; Kincaid MacDonald; Manik Kuchroo; Ronald R. Coifman; Guy Wolf; Smita Krishnaswamy (2021). "Diffusion Earth Mover's Distance and Distribution Embeddings". ICML. 2021: 10336–10346. arXiv:2102.12833.
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