About Me

Starting July 2025, I will be joining Duke University as an assistant professor in the departments of computer science, cell biology, and biostatistics and bioinformatics. I’m looking to recruit phd students for Fall 2025! If you are a prospective student interested in working with me, please apply through the Computer Science PhD program (Deadline Dec. 16) or the Computational Biology and Bioinformatics PhD program (Deadline Dec. 2) and mention me.

I am a postdoc with Yoshua Bengio working on efficient machine learning algorithms with applications to cell and molecular biology at Mila in Montreal.

I completed my PhD in the computer science department at Yale University in 2021 where I was advised by Smita Krishnaswamy. My dissertation can be found here. My research interests are in generative modeling, deep learning, and optimal transport. I’m working on applying ideas from generative modeling, causal discovery, optimal transport, and graph signal processing to understand how cells develop and respond to changing conditions. I’m also interested in generative models for protein design and cofounded Dreamfold to work on these problems.

I grew up in Seattle and graduated from Tufts University in 2017 with a BS and MS in computer science. Outside of work, I love sailing and running. I am the 2019 junior North American champion in the 505 class, and I recently ran my first 50 mile race the Vermont 50!

Recent News

Interests
  • Generative Modeling
  • Optimal Transport
  • Single Cell Dynamics
  • Protein Design
  • Graph Signal Processing
  • Causal Discovery
Education

  • PhD in Computer Science, 2021

    Yale University

  • MPhil in Computer Science, 2020

    Yale University

  • MS in Computer Science, 2017

    Tufts University

  • BS in Computer Science, 2017

    Tufts University

Preprints

Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Chenghao Liu, Sarthak Mittal, Nouha Dziri, Michael Bronstein, Yoshua Bengio, Pranam Chatterjee, Alex Tong, Avishek Joey Bose (2024). Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. Preprint.

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Malte Luecken, Scott Gigante, Daniel Burkhardt, Robrecht Cannoodt, Daniel Strobl, Nikolay Markov, Luke Zappia, Giovanni Palla, Wesley Lewis, Daniel Dimitrov, Michael Vinyard, Daniel Magruder, Alma Andersson, Emma Dann, Qian Qin, Dominik Otto, Michal Klein, Olga Botvinnik, Louise Deconinck, Kai Waldrant, Bastian Rieck, Constantin Ahlmann-Eltze, Eduardo Da Veiga Beltrame, Andrew Benz, Carmen Bravo González-Blas, Ann Chen, Benjamin DeMeo, Can Ergen, Swann Floc'hlay, Adam Gayoso, Stephanie Hicks, Yuge Ji, Vitalii Kleshchevnikov, Gioele La Manno, Maximilian Lombardo, Romain Lopez, Dario Righelli, Hirak Sarkar, Valentine Svensson, Alex Tong, Galen Xing, Chenling Xu, Jonathan Bloom, Angela Pisco, Julio Saez-Rodriguez, Drausin Wulsin, Luca Pinello, Yvan Saeys, Fabian Theis, Smita Krishnaswamy (2024). Defining and Benchmarking Open Problems in Single-Cell Analysis. Preprint.

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Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alex Tong, Andrea Dittadi, Fabian Theis (2024). Generating Multi-Modal and Multi-Attribute Single-Cell Counts with CFGen. Preprint.

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Trang Nguyen, Alex Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu (2023). Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. arXiv.

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Alex Tong, Manik Kuchroo, Shabarni Gupta, Aarthi Venkat, Beatriz P. San Juan, Laura Rangel, Brandon Zhu, John G. Lock, Christine L. Chaffer, Smita Krishnaswamy (2023). Learning Transcriptional and Regulatory Dynamics Driving Cancer Cell Plasticity Using Neural ODE-Based Optimal Transport. BioRxiv.

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Publications

Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alex Tong (2024). Trajectory Flow Matching with Applications to Clinical Time Series Modeling. In NeurIPS (Spotlight).

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Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alex Tong, Avishek Joey Bose (2024). Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. In NeurIPS.

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Kacper Kapusniak, Peter Potaptchik, Teodora Reu, Leo Zhang, Alex Tong, Michael Bronstein, Avishek Joey Bose, Francesco Di Giovanni (2024). Metric Flow Matching for Smooth Interpolations on the Data Manifold. In NeurIPS.

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Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alex Tong (2024). Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. In ICML.

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Kirill Neklyudov, Rob Brekelmans, Alex Tong, Lazar Atanackovic, Qiang Liu, Alireza Makhzani (2024). A Computational Framework for Solving Wasserstein Lagrangian Flows. In ICML.

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Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael Bronstein, Alex Tong (2024). SE(3)-Stochastic Flow Matching for Protein Backbone Generation. In ICLR (Spotlight).

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Alex Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio (2024). Simulation-Free Schrodinger Bridges via Score and Flow Matching. In AISTATS.
Also presented at Frontiers4LCD Workshop @ ICML 2023.

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Alex Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf (2024). Learnable Filters for Geometric Scattering Modules. In IEEE Transactions on Signal Processing.

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María Ramos Zapatero, Alex Tong, Jahangir Sufi, Petra Vlckova, Ferran Cardoso Rodriguez, Callum Nattress, Xiao Qin, Daniel Hochhauser, Smita Krishnaswamy, Christopher J. Tape (2023). Trellis tree-based analysis reveals stromal regulation of patient-derived organoid drug responses. Cell.

PDF Cite DOI code reproducible code Tutorial Cancer Research Spotlight Yale News News-Medical

Guillaume Huguet, Alex Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy (2023). A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. In NeurIPS.

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Lazar Atanackovic, Alex Tong, Jason Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio (2023). DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks. In NeurIPS.
Also presented at Frontiers4LCD Workshop @ NeurIPS 2022.

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Michael Perlmutter, Alex Tong, Feng Gao, Guy Wolf, Matthew Hirn (2023). Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms. In SIMODS.

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Guillaume Huguet, Alex Tong, María Ramos Zapatero, Christpher J. Tape, Guy Wolf, Smita Krishnaswamy (2023). Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds. In IEEE MLSP.

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Oluwadamilola Fasina, Guillaume Huguet, Alex Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy (2023). Neural FIM for Learning Fisher Information Metrics from Point Cloud Data. In ICML.

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Guillaume Huguet, Alex Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew Hirn, Guy Wolf, Smita Krishnaswamy (2023). Time-Inhomogeneous Diffusion Geometry and Topology. In SIMODS.

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Manik Kuchroo, Marcello DiStasio, Eric Song, Eda Calapkulu, Le Zhang, Maryam Ige, Amar H. Sheth, Abdelilah Majdoubi, Madhvi Menon, Alex Tong, Abhinav Godavarthi, Yu Xing, Scott Gigante, Holly Steach, Jessie Huang, Guillaume Huguet, Janhavi Narain, Kisung You, George Mourgkos, Rahul M. Dhodapkar, Matthew J. Hirn, Bastian Rieck, Guy Wolf, Smita Krishnaswamy, Brian P. Hafler (2023). Single-Cell Analysis Reveals Inflammatory Interactions Driving Macular Degeneration. Nature Communications.

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Alex Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio (2023). Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport. In TMLR
Also presented at Frontiers4LCD Workshop @ ICML 2023.

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Sam Leone, Alex Tong, Guillaume Huguet, Guy Wolf, Smita Krishnaswamy (2023). Graph Fourier MMD for signals on data graphs. In SAMPTA.

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Guillaume Huguet, D. S. Magruder, Alex Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy (2022). Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. In NeurIPS.

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Alex Tong, Guillaume Huguet, Dennis Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy (2022). Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. In ICASSP.

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Ana Luisa Perdigoto, Songyan Deng, Katherine C. Du, Manik Kuchroo, Daniel B. Burkhardt, Alex Tong, Gary Israel, Marie E. Robert, Stuart P. Weisberg, Nancy Kirkiles-Smith, Angeliki M. Stamatouli, Harriet M. Kluger, Zoe Quandt, Arabella Young, Mei-Ling Yang, Mark J. Mamula, Jordan S. Pober, Mark S. Anderson, Smita Krishnaswamy, Kevan C. Herold (2022). Immune Cells and Their Inflammatory Mediators Modify Beta Cells and Cause Checkpoint Inhibitor-Induced Diabetes. JCI Insight.

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Brian Palmer Hafler, Manik Kuchroo, Marcello DiStasio, Eric Song, Le Zhang, Maryam Ige, Amar Sheth, Madhvi Menon, Alex Tong, Yu Xing, Scott Gigante, Jessie Huang, George Mourgkos, Smita Krishnaswamy, Rahul Dhodapkar, Guy Wolf (2022). Topological Analysis of Single-Cell Hierarchy Reveals Inflammatory Glial Landscape of Macular Degeneration. Investigative Ophthalmology & Visual Science.

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Manik Kuchroo, Jessie Huang, Patrick Wong, Jean-Christophe Grenier, Dennis Shung, Alex Tong, Carolina Lucas, Jon Klein, Daniel Burkhardt, Scott Gigante, Abhinav Godavarthi, Benjamin Israelow, Tianyang Mao, Ji Eun Oh, Julio Silva, Takehiro Takahashi, Camila D. Odio, Arnau Casanovas-Massana, John Fournier, Yale IMPACT Team, Shelli Farhadian, Charles S. Dela Cruz, Albert I. Ko, F. Perry Wilson, Julie Hussin, Guy Wolf, Akiko Iwasaki, Smita Krishnaswamy (2022). Multiscale PHATE identifies multimodal signatures of COVID-19. Nature Biotechnology.

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Michal Gerasimiuk, Dennis L. Shung, Alex Tong, Adrian J. Stanley, Machael Shultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy (2021). MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. In IEEE Big Data.

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Malte D Luecken, Daniel B Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann T Chen, Louise Deconinck, Angela M Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Joon Kim, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Honey Mekonen, Joaquin Caceres, Maurizio Morri, Michaela Mueller, Norma F Neff, Sheryl Paul, Kaylie Schneider, Scott Steelman, Michael Sterr, Dan J Treacy, Alex Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela O Pisco, Smita Krishnaswamy, Fabian J Theis, Jonathan M Bloom (2021). A sandbox for prediction and integration of DNA, RNA, and protein data in single cells. In NeurIPS Datasets and Benchmarks.

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Alex Tong, Guy Wolf, Smita Krishnaswamy (2021). Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. In Journal of Signal Processing Systems.

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Alex Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf (2021). Data-Driven Learning of Geometric Scattering Networks. In IEEE MLSP.
Also presented at ML4M Workshop @ NeurIPS 2020.

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Manik Kuchroo, Abhinav Godavarthi, Alex Tong, Smita Krishnaswamy, Guy Wolf (2021). Multimodal data visualization and denoising with integrated diffusion. In IEEE MLSP.

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Alex Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald Coifman, Guy Wolf, Smita Krishnaswamy (2021). Diffusion Earth Mover's Distance and Distribution Embeddings. In ICML.
Also presented at LMRL Workshop @ NeurIPS 2020.

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Remi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z Alaya, Aurelie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Leo Gautheron, Nathalie T H Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J Sutherland, Romain Tavenard, Alex Tong, Titouan Vayer (2021). POT: Python Optimal Transport. In JMLR.

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Daniel B. Burkhardt, Jay S. Stanley, Alex Tong, Ana Luisa Perdigoto, Scott A. Gigante, Kevan C. Herold, Guy Wolf, Antonio J. Giraldez, David Van Dijk, Smita Krishnaswamy (2021). Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing. In Nature Biotechnology.

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Egbert Castro, Andrew Benz, Alex Tong, Guy Wolf, Smita Krishnaswamy (2020). Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. In IEEE Big Data.
Also at GRLB Workshop @ ICML 2020.

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Alex Tong, Guy Wolf, Smita Krishnaswamy (2020). Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. In IEEE MLSP.
Best Student Paper Award.

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Alex Tong, Jessie Huang, Guy Wolf, David Van Dijk, Smita Krishnaswamy (2020). TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. In ICML.
Also at LMRL Workshop @ NeurIPS 2019.

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Alex Tong, David Van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy (2020). Interpretable Neuron Structuring with Graph Spectral Regularization. In IDA
Also presented at RLGM Workshop @ ICLR 2019.

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David Van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alex Tong, Guy Wolf, Smita Krishnaswamy (2019). Finding Archetypal Spaces Using Neural Networks. In IEEE Big Data.

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James Aspnes, Bernhard Haeupler, Alex Tong, Philipp Woelfel (2018). Allocate-On-Use Space Complexity of Shared-Memory Algorithms. In DISC.

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