Alex Tong

Phd Student

Department of Computer Science Yale University

About Me

I’m a PhD Candidate in computer science at Yale University advised by Dr. Smita Krishnaswamy. My current research interests are in machine learning and optimal transport. I’m working on applying ideas from optimal transport and graph signal processing to understand and adapt deep learning models.

I grew up in Seattle, Washington, and graduated from Tufts University in 2017 with a B.S. and M.S. in computer science. I love sailing and trail running.

Interests

Machine Learning
Optimal Transport
Anomaly Detection
Graph Signal Processing
Single Cell Transcriptomics

Education

PhD in Computer Science focus on Machine Learning, 2017-Present
Yale University
MS in Computer Science, 2017
Tufts University
BS in Computer Science, 2017
Tufts University

Publications

Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy (2020). Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. In IEEE Big Data.

Daniel B. Burkhardt, Jay S. Stanley, Alexander Tong, Ana Luisa Perdigoto, Scott A. Gigante, Kevan C. Herold, Guy Wolf, Antonio J. Giraldez, David van Dijk, Smita Krishnaswamy (2020). Quantifying the effect of experimental perturbations in single-cell RNA-sequencing data using graph signal processing. To appear in Nature Biotechnology.

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

PDF Code Slides Video Yale Daily Article Best Paper Award

Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy (2020). TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. In ICML.

Code Slides Video Arxiv ICML Page

Alexander 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.

PDF Code Slides Video DOI

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

PDF Code DOI Arxiv

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

Workshops

without proceedings

Alexander Tong, Manik Kuchroo, Guillaume Huguet, Ronald Coifman, Guy Wolf, Smita Krishnaswamy (2020). Fast Diffusion Optimal Transport for Manifold-of-Manifold Embeddings. NeurIPS LMRL Workshop.

Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf (2020). Scattering Priors for Graph Neural Networks. DeepMath.

Poster Conference

Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy (2020). Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. ICML 2020 GRLB Workshop.

Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf (2020). Data-Driven Learning of Geometric Scattering Networks. NeurIPS ML4M Workshop.

Alexander Tong, Smita Krishnaswamy (2020). Interpolating Optimal Transport Barycenters of Patient Manifolds. ISMB.

Poster Slides Video

Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy (2019). Modeling Cellular Dynamics with Continuous Normalizing Flows. NeurIPS LMRL Workshop.

Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy (2019). Graph Spectral Regularization for Neural Network Interpretability. ICLR RLGM Workshop.