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Mo T

- Research Program Mentor

PhD Doctor of Philosophy candidate


Artificial intelligence, machine learning, statistical learning, deep learning

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Optimizing a state-of-the-art k-medoids algorithm in C++

We've developed a state-of-the-art clustering algorithm for the k-medoids problem (similar to k-means, but where the cluster centers must be actual datapoints). Our work was accepted to Neural Information Processing Systems (NeurIPS) 2020. We have also released a Python package, written in C++, to enable others to use our algorithm. We are looking for someone to optimize this package. Experience with multithreading, caches, and profiling code is a plus.

Learning the best data augmentations

Data augmentation in machine learning is currently a bag of tricks. Very little work exists regarding what is the "best" form of data augmentation; most people try everything and keep what sticks. Our work aims to learn the best data augmentations from the training data itself. We have promising initial results and are looking for someone who can help contribute to the research. We expect this research will result in a publication. To see if you'd be a good fit for this project, you should test your understanding of the AutoAugment paper. Experience with Bayesian Optimization or reinforcement learning is a plus.

Coding skills

Python, C++, PHP, Java

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