The Machine Intelligence and Neural Technologies lab, MINT, at Vanderbilt University pursues fundamental research in mathematical machine learning and geometric deep learning. We develop next-generation machine learning algorithms grounded in computational optimal transport and geometric methods, with a focus on building efficient, robust, and continually adaptive AI systems.
Chayne presented our work on Zero-Sum SVD at ICML 2026.
Our Collaborative NSF proposal with Prof. Rocío Martín titled, “Generalized Slicers for Efficient and Versatile Computation of Transport-Based Dissimilarities and Assignments,” is funded by the DMS office.
The Phase 1 of our STTR project with YRIKKA titled, “MIRAGE Diffusion – Minimax Inference for Realistic Adversarial Generation” was funded by AFWERX.
Ali presented two papers at the CVPR Workshop SynData4CV in Denver, Colorado.
Eva defended her dissertation with stellar comments from her committee members. We have a new doctor in the house!
Our paper “EMPEROR: Efficient Moment-Preserving Representation of Distributions” was accepted at ICASSP2026! Congratulations, Eva and Shansita.
Congratulations to Eva for acceptance of her paper on Policy Search, Retrieval, and Composition via Task Similarity in Collaborative Agentic System to AAAI 2026.
Congratulations to Ashkan and Ela for acceptance of their paper on Neural-Augmented Kelvinlet for Real-Time Soft Tissue Deformation Modeling to AAAI 2026.
Welcome to our newest lab member, Ping He!
Abi was selected as the Banner Bearer for Vanderbilt School of Engineering.
Ashkan’s paper on doubly stochastic attention got accepted to ICML 2025.
Eva passed her Qualifying Exam with stellar feedback from the committee.
Chayne got an internship from Apple for Summer 2025.
Abi was selected as a finalist for the CRA Outstanding Undergraduate Researcher Award.
One of Eva’s two papers, accepted at ICLR, was selected as a Spotlight paper!
Ali passed his Qualifying Exam with stellar feedback from the committee.
Congratulations to Huy and the team for acceptance of their paper, “Stereographic Spherical Sliced Wasserstein Distances”, to ICML 2024.
Our paper titled, “Statistical Context Detection for Deep Lifelong Reinforcement Learning” got accepted to CoLLAs 2024.
Abi won the university-wide research poster award in Engineering, Computer Science, Data Science, and Mathematics.
Our collaborative paper on “A Collective AI via Lifelong Learning and Sharing at the Edge” is now published at Nature Machine Intelligence.
Ali’s paper, titled “BrainWash - A Poisoning Attack to Forget in Continual Learning” got accepted to CVPR 2024!
Eva’s paper, titled “Teaching Networks to Solve Optimization Problems” got published in IEEE ACCESS!
Our paper titled, “LCOT - Linearized Circular Optimal Transport” got accepted to ICLR 2024.
Our paper titled, “NOLA - Compressing LoRA using Linear Combination of Random Basis” got accepted to ICLR 2024.
Eva presented our paper titled SLoSH - Set Locality Sensitive Hashing via Sliced-Wasserstein Embeddings at WACV 2024.
Soheil received the NSF CAREER Award!
Congratulations to Dr. Yikun Bai for acceptance of his paper, titled “Sliced Optimal Partial Transport”, at CVPR 2023!
Congrats to Harry and Huy for acceptance of their paper, titled “Is Multitask Learning an Upper Bound for Continual Learning,” at ICASSP 2023!
A big congratulations to Ali for acceptance of his paper, titled “Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations,” at CoLLAs 2022!
Our paper on “Generalized Sliced Probability Metrics” received the Best Paper Award from IEEE ICASSP 2022.
A big congratulations to Harry for his selection to the Vanderbilt Institute for Surgery and Engineering (VISE) Summer Fellows Program!
Ali’s new preprint, titled “Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations” is now available online. This is a joint work with UC-Davis and Johns Hopkins University.
02/08/2022 - Bryan’s new preprint, titled “SLOSH: Set LOcality Sensitive Hashing via Sliced-Wasserstein Embeddings” is now available online.
02/08/2022 - Eva’s new preprint, titled “Teaching Networks to Solve Optimization Problems” is now available online. This is a joint work with UT-Austin.
Our paper on “Lifelong Learning with Sketched Structural Regularization,” is accepted to ACML 2021. (In collaboration with JHU and HRL Laboratories)
Our paper on “Pooling by Sliced-Wasserstein Embedding” is accepted to NeurIPS 2021. (In collaboration with UPenn and HRL Laboratories)
We have an opening for a postdoctoral researcher focusing on lifelong/continual learning.
We have multiple open positions for Ph.D. students.
Soheil Kolouri delivered a talk at the One World Seminar on the Mathematics of Machine Learning focused on “Wasserstein Embeddings.” (Video)
09/24/2021 - We have an opening for a postdoctoral researcher focusing on computational optimal transport.
06/23/2021 - We have openings for PhD, MS, and BS students.
06/21/2021 - MINT Lab was born.
Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
ICML, 2026
Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation
CVPR Workshop SynData4CV, 2026
One category one prompt: Dataset distillation using diffusion models
CVPR Workshop SynData4CV, 2026
Neural-Augmented Kelvinlet: Real-Time Soft Tissue Deformation with Multiple Graspers
AAAI, 2026
Policy search, retrieval, and composition via task similarity in collaborative agentic systems.
AAAI 2026
Knowledge distillation and dataset distillation of large language models: Emerging trends, challenges, and future directions.
Artificial Intelligence Review, 2025
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