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Our research at the Krishnaswamy Lab focuses on applying machine learning methods to high-throughput high dimensional biological data. Our research projects aim to study and develop algorithmic approaches to naturally process data, visualize it, understand progressions, find phenotypic diversity, and infer patterns.  Below are our key research areas and priorities, along with some relevant projects:


Unsupervised Deep Learning

Manifold Learning and Data Geometry

Diffusion Maps, MAGICPHATE

Graph Signal Processing and Filtering

Information Theory and Gene Logic

Single-Cell, High-Throughput, and High-Dimensional Data

Single-cell RNA sequencing (e.g. 10x genomics) 


Biological Systems

Developmental (Embryoid Bodies, Brain organoids, Mouse Brain, Hematopoiesis)

Immunology (Dengue, Zika, HIV, Cancer Immunotherapy, Lupus, Type 1 Diabetes)

Cancer (EMT, Immunotherapy)

Latest Preprints


Gigante S, Charles AS, Krishnaswamy S, Mishne G. Visualizing the PHATE of Neural Networks. arXiv:1908.02831 [cs.LG]. 2019 Aug 7.

Burkhardt DB*, Stanley JS*, Pertigoto AL, Gigante S, Herold KC, Wolg G, Giraldez A, van Dijk D, Krishnaswamy S. Enhancing experimental signals in single-cell RNA-sequencing data using graph signal processing. bioRxiv Bioinformatics. 2019 Jan 28.

Chen WS, Zivanovic N, van Dijk D, Wolf G, Bodenmiller B, Krishnaswamy S. Embedding the single-cell sample manifold to reveal insights into cancer pathogenesis and disease heterogeneity. bioRxiv Bioinformatics. 2018 Oct 29.

Stanley JS, Gigante S, Wolf G*, Krishnaswamy S*. Manifold Alignment with Feature Correspondence. arXiv:1810.00386 [cs.LG]. 2018 Sep 30.

Tong A*, van Dijk D*, Stanley JS, Amodio M, Wolf G, Krishnaswamy S. Graph Spectral Regularization for Neural Network Interpretability. arXiv:1810.00424 [cs.LG]. 2018 Sep 30.

Amodio M, van Dijk D, Montgomery R, Wolf G, Krishnaswamy S. Out-of-Sample Extrapolation with Neuron Editing. 2018 May 30. arXiv:1805.12198 [q-bio.QM]. 2018 May 30.

Lindenbaum O*, Stanley JS*, Wolf G, Krishnaswamy S. Geometry-Based Data Generation. arXiv:1802.04927 [cs.LG]. 2018 Feb 14.

Amodio M*, van Dijk D*, Srinivasan K*, Chen WS, Mohsen H, Moon KR, Campbell A, Zhao Y, Wang X, Venkataswamy M, Desai A, Ravi V, Kumar P, Montgomery R, Wolf G, Krishnaswamy S. Exploring Single-Cell Data with Deep Multitasking Neural Networks. bioRxiv Bioinformatics. 2017 Dec 17.

Moon KR*, van Dijk D*, Wang Z*, Gigante S, Burkhardt D, Chen WS, van den Elzen A, Hirn MJ, Coifman RR, Ivanova NB, Wolf G, Krishnaswamy S. Visualizing Transitions and Structure for Biological Data Exploration. bioRxiv Bioinformatics. 2017 Mar 24.


Selected Publications


Gigante S*, van Dijk D*, Moon KR, Strzalkowski A, Wolf G, Krishnaswamy S. Modeling Global Dynamics from Local Snapshots with Deep Generative Neural Networks. Sampling Theory and Applications. 2019 Jul.

Gigante S*, Stanley JS*, Vu N, van Dijk D, Moon KR, Wolf G, Krishnaswamy S. Compressed Diffusion. Sampling Theory and Applications. 2019 Jul.

Amodio A, Krishnaswamy S. TraVeLGAN: Image-to-image Translation by Transformation Vector Learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019 Jun.


Krishnaswamy S, Zivanovic N, Sharma R, Pe’er D, Bodenmiller B. Learning time-varying information flow from single-cell epithelial to mesenchymal transition data. PLOS One. 2018 Oct 29. PMID 30372433.

Amodio M and Krishnaswamy S. MAGAN: Aligning Biological Manifolds. Proceedings of the 35th International Conference on Machine Learning. 2018 Jul 10-15.

van Dijk D, Sharma R, Nainys J, Yim K, Kathail P, Carr A, Burdziak C, Moon KR, Chaffer CL, Pattabiraman D, Bierie B. Recovering Gene Interactions from Single-Cell Data Using Data Diffusion. Cell. 2018 Jun 28. PMID 29961576.

Moon KR, Stanley JS, Burkhardt D, van Dijk D, Wolf G, Krishnaswamy S: Manifold learning-based methods for analyzing single-cell RNA-sequencing data. Current Opinion in Systems Biology. 2018 Feb.



Yao Y, Welp T, Liu Q, Niu N, Wang X, Britto CJ, Krishnaswamy S, Chupp GL, Montgomery RR: Multiparameter Single Cell Profiling of Airway Inflammatory Cells. Cytometry B Clin Cytom. 2017 Jan. PMID: 27807928.


Lowther DE, Goods BA, Lucca LE, Lerner BA, Raddassi K, van Dijk D, Hernandez AL, Duan X, Gunel M, Coric V, Krishnaswamy S, Love JC, Hafler DA: PD-1 marks dysfunctional regulatory T cells in malignant gliomas. JCI Insight. 2016 Apr 21. PMID: 27182555.


Zunder ER, Finck R, Behbehani GK, Amir el-AD, Krishnaswamy S, Gonzalez VD, Lorang CG, Bjornson Z, Spitzer MH, Bodenmiller B, Fantl WJ, Pe'er D, Nolan GP: Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm. Nat Protoc. 2015 Feb; 2015 Jan 22. PMID: 25612231.


Krishnaswamy S, Spitzer MH, Mingueneau M, Bendall SC, Litvin O, Stone E, Pe'er D, Nolan GP: Systems biology. Conditional density-based analysis of T cell signaling in single-cell data. Science. 2014 Nov 28; 2014 Oct 23. PMID: 25342659.

Mingueneau M, Krishnaswamy S, Spitzer MH, Bendall SC, Stone EL, Hedrick SM, Pe'er D, Mathis D, Nolan GP, Benoist C: Single-cell mass cytometry of TCR signaling: amplification of small initial differences results in low ERK activation in NOD mice. Proc Natl Acad Sci U S A. 2014 Nov 18; 2014 Oct 31. PMID: 25362052.

Amir el-AD, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe'er D: viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol. 2013 Jun; 2013 May 19. PMID: 23685480.

Finck R, Simonds EF, Jager A, Krishnaswamy S, Sachs K, Fantl W, Pe'er D, Nolan GP, Bendall SC: Normalization of mass cytometry data with bead standards. Cytometry A. 2013 May; 2013 Mar 19. PMID: 23512433.




Design, Analysis and Test of Logic Circuits Under Uncertainty

Krishnaswamy S, Markov IL and Hayes, JP. Springer, 2013.