Publications

2026

1. ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics

   Siddharth Viswanath, Xingzhi Sun, Lucas Lee, Danqi Liao, Hiren Madhu, David R Johnson, João Felipe Rocha, Egbert Castro, Jackson D Grady, Michael Perlmutter, Dhananjay Bhaskar, and Smita Krishnaswamy

   Learning on Graphs Conference (LoG), 2026

   Code
2. Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity

   Dhananjay Bhaskar, Yanlei Zhang, Jessica Moore, Feng Gao, Bastian Rieck, Guy Wolf, Firas Khasawneh, Elizabeth Munch, J Adam Noah, Helen Pushkarskaya, Christopher Pittenger, Valentina Greco, and Smita Krishnaswamy

   Neurocomputing (to appear), 2026
3. 140 Years of mathematical modeling in oncology through AI-assisted curation

   Franco Pradelli, Maximilian Strobl, Sadegh Marzban, François Kermenguy, Ari Barnett, Katyayni Ganesan, David A Hormuth, Sara Hamis, Dhananjay Bhaskar, Guillermo Lorenzo, Alexander R A Anderson, and Jeffrey West

   bioRxiv, 2026
4. MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data

   Xingzhi Sun, João Felipe Rocha, Brett Phelan, Dhananjay Bhaskar, Guillaume Huguet, Yanlei Zhang, Alexander Tong, Ke Xu, Oluwadamilola Fasina, Mark Gerstein, Natalia Ivanova, Christine L Chaffer, Guy Wolf, and Smita Krishnaswamy

   arXiv:2603.22564, 2026

   Code
5. Physical contact reveals a hidden layer of cortical architecture

   Jordan K Matelsky, Hannah Martinez, Michael S Robinette, Katharine Merfeld, Daniel Xenes, Cara J Cavanaugh, Sarah E Emerson, Dhananjay Bhaskar, Benjamin Clark, Caitlyn Bishop, Konrad P Körding, Daniel Colón-Ramos, Patricia Rivlin, Cody J Smith, and Brock Wester

   bioRxiv, 2026
6. scShapeBench: Discovering geometry from high dimensional scRNAseq data

   Andrew J Steindl, João Felipe Rocha, Brian Tshilengi Di Bassinga, Zachary Warren, Matthew Scicluna, César Miguel Valdez Córdova, Shabarni Gupta, Leire Torices, Daniel Neumann, Timothy J Mann, Ihuan Gunawan, Dhananjay Bhaskar, John G Lock, Christine L Chaffer, Guy Wolf, and Smita Krishnaswamy

   Advances in Neural Information Processing Systems (to appear), 2026
7. BrainDyn: A Sheaf Neural ODE for Generative Brain Dynamics

   Siddharth Viswanath, Panayiotis Ketonis, Chen Liu, Michael Perlmutter, Dhananjay Bhaskar, and Smita Krishnaswamy

   arXiv:2605.19324, 2026

   Code
8. SPINET: Sheaf Protein Inverse Folding Network

   Jens Lundsgaard, Colin Mikulski, Zhixuan Yan, and Dhananjay Bhaskar^#

   arXiv:2609.34153, 2026

   Code
9. T-SNN: Temporal Simplicial Neural Network for EEG Decoding

   Nikita Malik, Shubhajit Roy, Mohit Kataria, Isuru Herath, Suraj Yadav, Inés Garcı́a-Redondo, and Dhananjay Bhaskar^#

   arXiv:2609.34002, 2026

   Code
10. HiPoNet: A Multi-View Simplicial Complex Network for High Dimensional Point-Cloud and Single-Cell data

    Siddharth Viswanath, Hiren Madhu, Dhananjay Bhaskar, Jake Kovalic, Dave Johnson, Christopher Tape, Ian Adelstein, Rex Ying, Michael Perlmutter, and Smita Krishnaswamy

    Advances in Neural Information Processing Systems, 2026

    Code

2025

1. Revealing dynamic temporal trajectories and underlying regulatory networks with Cflows

   Xingzhi Sun, Shabarni Gupta, Alexander Tong, Manik Kuchroo, Dhananjay Bhaskar, Chen Liu, Aarthi Venkat, Beatriz Perez San Juan, Laura Rangel, Vanina Rodriguez, John G Lock, Christine Chaffer, and Smita Krishnaswamy

   bioRxiv, 2025
2. Latent representation learning for multimodal brain activity translation

   Arman Afrasiyabi, Dhananjay Bhaskar, Erica L Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B Turk-Browne, and Smita Krishnaswamy

   ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing), 2025
3. Principal Curvatures Estimation with Applications to Single Cell Data

   Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid Macdonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, and Bastian Rieck

   ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing), 2025
4. Deep multimodal representations and classification of first-episode psychosis via live face processing

   Rahul Singh, Yanlei Zhang, Dhananjay Bhaskar, Vinod Srihari, Cenk Tek, Xian Zhang, J Adam Noah, Smita Krishnaswamy, and Joy Hirsch

   Frontiers in Psychiatry, 2025
5. Exploring neurodevelopment via spatiotemporal collation of anatomical networks with NeuroSCAN

   Noelle L Koonce, Sarah E Emerson, Dhananjay Bhaskar, Manik Kuchroo, Mark W Moyle, Pura Arroyo-Morales, Nabor Vázquez-Martı́nez, Jamie I Emerson, Smita Krishnaswamy, William A Mohler, and Daniel A Colón-Ramos

   eLife, 2025
6. Linearized Optimal Transport for Analysis of High-Dimensional Point-Cloud and Single-Cell Data

   Tianxiang Wang, Yingtong Ke, Dhananjay Bhaskar, Smita Krishnaswamy, and Alexander Cloninger

   arXiv:2510.22033, 2025
7. BDN: Blaschke Decomposition Networks

   Yanlei Zhang, Damien Martins Gomes, Chen Liu, Guy Wolf, Michael Perlmutter, Smita Krishnaswamy, and Dhananjay Bhaskar

   2025
8. DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms

   Dhananjay Bhaskar, Xingzhi Sun, Yanlei Zhang, Charles Xu, Arman Afrasiyabi, Siddharth Viswanath, Oluwadamilola Fasina, Guy Wolf, Michael Perlmutter, and Smita Krishnaswamy

   Proceedings of the 1st Conference on Topology, Algebra, and Geometry in Data Science (TAG-DS), PMLR 321:236–268, 2025

2024

1. Inferring dynamic regulatory interaction graphs from time series data with perturbations

   Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, James Noonan, Guy Wolf, Natalia Ivanova, and Smita Krishnaswamy

   Learning on Graphs Conference, 2024

   Code
2. Dissecting glial scar formation by spatial point pattern and topological data analysis

   Daniel Manrique-Castano, Dhananjay Bhaskar, and Ayman ElAli

   Scientific Reports, 2024

   Code
3. Learnable filters for geometric scattering modules

   Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid Macdonald, Jackson Grady, Michael Perlmutter, Smita Krishnaswamy, and Guy Wolf

   IEEE Transactions on Signal Processing, 2024

   Code
4. Generative modeling of biological shapes and images using a probabilistic α-shape sampler

   Emily T Winn-Nuñez, Hadley Witt, Dhananjay Bhaskar, Ryan Y Huang, Jonathan S Reichner, Ian Y Wong, and Lorin Crawford

   bioRxiv, 2024
5. Exploring the Manifold of Neural Networks Using Diffusion Geometry

   Elliott Abel, Andrew J Steindl, Selma Mazioud, Ellie Schueler, Folu Ogundipe, Ellen Zhang, Yvan Grinspan, Kristof Reimann, Peyton Crevasse, Dhananjay Bhaskar, Siddharth Viswanath, Yanlei Zhang, Tim G J Rudner, Ian Adelstein, and Smita Krishnaswamy

   arXiv:2411.12626, 2024

2023

1. Multiscale geometric and topological analyses for characterizing and predicting immune responses from single cell data

   Aarthi Venkat, Dhananjay Bhaskar, and Smita Krishnaswamy

   Trends in Immunology, 2023
2. Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion

   Dhananjay Bhaskar, William Y Zhang, Alexandria Volkening, Björn Sandstede, and Ian Y Wong

   npj Systems Biology and Applications, 2023
3. Cell cycle controls long-range calcium signaling in the regenerating epidermis

   Jessica L Moore, Dhananjay Bhaskar, Feng Gao, Catherine Matte-Martone, Shuangshuang Du, Elizabeth Lathrop, Smirthy Ganesan, Lin Shao, Rachael Norris, Nil Campaà Sanz, Karl Annusver, Maria Kasper, Andy Cox, Caroline Hendry, Bastian Rieck, Smita Krishnaswamy, and Valentina Greco

   Journal of Cell Biology, 2023
4. A Flow Artist for High-Dimensional Cellular Data

   Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, and Smita Krishnaswamy

   MLSP (IEEE 33rd International Workshop on Machine Learning for Signal Processing), 2023

   Code

2022

1. Diffusion-Based Methods for Estimating Curvature in Data

   Dhananjay Bhaskar, Kincaid MacDonald, Dawson Thomas, Sarah Zhao, Kisung You, Jennifer Paige, Yariv Aizenbud, Bastian Rieck, Ian M Adelstein, and Smita Krishnaswamy

   Workshop on Geometrical and Topological Representation Learning, ICLR, 2022
2. Diffusion curvature for estimating local curvature in high dimensional data

   Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, and Smita Krishnaswamy

   Advances in Neural Information Processing Systems, 2022
3. Current trends in artificial intelligence in reproductive endocrinology

   Dhananjay Bhaskar, T Arthur Chang, and Shunping Wang

   Current Opinion in Obstetrics and Gynecology, 2022
4. Transformer-based protein generation with regularized latent space optimization

   Egbert Castro, Abhinav Godavarthi, Julian Rubinfien, Kevin Givechian, Dhananjay Bhaskar, and Smita Krishnaswamy

   Nature Machine Intelligence, 2022

   Code
5. Molecular graph generation via geometric scattering

   Dhananjay Bhaskar, Jackson Grady, Egbert Castro, Michael Perlmutter, and Smita Krishnaswamy

   MLSP (IEEE 32nd International Workshop on Machine Learning for Signal Processing), 2022

2021

1. Topological data analysis of collective and individual epithelial cells using persistent homology of loops

   Dhananjay Bhaskar, William Y Zhang, and Ian Y Wong

   Soft Matter, 2021

2019

1. 3D printed self-adhesive PEGDA–PAA hydrogels as modular components for soft actuators and microfluidics

   Thomas M Valentin, Eric M DuBois, Catherine E Machnicki, Dhananjay Bhaskar, Francis R Cui, and Ian Y Wong

   Polymer Chemistry, 2019
2. A methodology for morphological feature extraction and unsupervised cell classification

   Dhananjay Bhaskar, Darrick Lee, Hildur Knútsdóttir, Cindy Tan, MoHan Zhang, Pamela Dean, Calvin Roskelley, and Leah Edelstein-Keshet

   bioRxiv, 2019
3. Motility-limited aggregation of mammary epithelial cells into fractal-like clusters

   Susan E Leggett, Zachary J Neronha, Dhananjay Bhaskar, Jea Yun Sim, Theodora Myrto Perdikari, and Ian Y Wong

   Proceedings of the National Academy of Sciences, 2019
4. Breast cancer cells transition from mesenchymal to amoeboid migration in tunable three-dimensional silk–collagen hydrogels

   Amanda S Khoo, Thomas M Valentin, Susan E Leggett, Dhananjay Bhaskar, Elisa M Bye, Shoham Benmelech, Blanche C Ip, and Ian Y Wong

   ACS Biomaterials Science & Engineering, 2019
5. Analyzing collective motion with machine learning and topology

   Dhananjay Bhaskar, Angelika Manhart, Jesse Milzman, John T Nardini, Kathleen M Storey, Chad M Topaz, and Lori Ziegelmeier

   Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019

   Code

2018

1. Coupling mechanical tension and GTPase signaling to generate cell and tissue dynamics

   Cole Zmurchok, Dhananjay Bhaskar, and Leah Edelstein-Keshet

   Physical Biology, 2018

2017

1. Polarization and migration in the zebrafish posterior lateral line system

   Hildur Knutsdottir, Cole Zmurchok, Dhananjay Bhaskar, Eirikur Palsson, Damian Dalle Nogare, Ajay Chitnis, and Leah Edelstein-Keshet

   PLOS Computational Biology, 2017