Half-Hop: A graph upsampling approach for slowing down message passing.
ICML, Jul 2023.
Mehdi Azabou - ML PhD Student @ Georgia Tech
I am actively working on developing methods for self-supervised representation learning for different modalities, and researching new models to learn from neural activity and behavior.
Sep 2023 | Two papers accepted at NeurIPS 2023 🎉. More details coming soon. | |
Jul 2023 | Half-Hop is the 🏝️ ICML'23 featured research in ML@GT. Read the article here: New Research from Georgia Tech and DeepMind Shows How to Slow Down Graph-Based Networks to Boost Their Performance. | |
May 2023 | I am interning at IBM Research this summer. I will be at the IBM Thomas J. Watson Research Center in New York. | |
Apr 2023 | Half-Hop is accepted at ICML 2023 🎉. More details coming soon. | |
Apr 2023 | Our paper on identifying cell type from in vivo neuronal activity was published in Cell Reports [Link]. | |
Mar 2023 | Check out our latest behavior representation learning model BAMS which ranks first 🥇 on the MABe 2022 benchmark [Project page]. |
I am a forth-year Machine Learning Ph.D. student advised by Dr. Eva L. Dyer. My main areas of interest are 🤖 Deep Learning and 🧠 Computational Neuroscience.
My research focuses on the development of new methods for representation learning. I am particularly interested in expanding the use of these tools to novel domains where the structure of the data can be complex and obscured. Through the development of new approaches for analyzing and interpreting complex modalities, I aim to make an impact in our understanding of the brain, and biological intelligence, and to contribute new tools that facilitate new scientific discoveries.
I am currently working on developing methods for learning representations of neural activity, behavior, and graphs, with the goal of improving our understanding of the brain. If you are interested in collaborating, feel free to reach out!
I love coding and learning new things. I am an enthusiast for dynamic and interactive visualizations that can provide insights into complex data and enable new ways of thinking. I received a MS in Engineering from CentraleSupélec, France in 2019 and a MS in Computer Science from Georgia Tech in 2020.