ATLANTA, Oct 30: Machine learning PhD students from across Georgia Tech showed off their work on Friday, October 16, 2026, at the ML@GT Student Conference. The Machine Learning Center hosted the event, which brought together faculty and students from labs and disciplines across campus.
The conference had three goals: to showcase research by ML@GT's PhD students, to show students what's happening in other labs and fields, and to build more collaboration across the Center.
The program included 12 student presentations across four research themes. More than 20 posters were on display during the poster session. Topics ranged from efficient prediction and protein modeling to brain-computer interfaces, seizure detection, and acoustic perception.
Attendees, including Georgia Tech faculty and students, voted for their favorite presentations and posters. Prizes went to the top three in each category.
Presentation Awards
- 1st Place: Hangyu Zhou, "Learning Computational Structure for Sample-Efficient Prediction" - School of Computer Science, advised by Steve Mussmann
- 2nd Place: Darin Tsui, "Protein Circuit Tracing via Cross-layer Transcoders" - School of Electrical and Computer Engineering, advised by Amirali Aghazadeh
- 3rd Place: Pranav Deevi, "FETTUCCINE: Fast and efficient brain-to-text decoding on mobile devices" - School of Biomedical Engineering, advised by Chethan Pandarinath
Poster Awards
- 1st Place: Hyunju Kim, "Spatiotemporal Hyperedges for EEG Seizure Detection and Prediction" - School of Computational Science and Engineering, advised by Nabil Imam
- 2nd Place: Benjamin Burns, "When, why, and how do diffusion posterior samplers fail? A finite-sample lens" - School of Electiral and Computer Engineering, advised by Sara Fridovich-Keil
- 3rd Place: Tianwei Jiang, "Intelligent Acoustic Perception: From Sound Recognition to Multimodal Spatial Understanding" - School of Electrical and Computer Engineering, advised by David Anderson
The winning projects show the range of machine learning research at Georgia Tech. They include basic work on sample efficiency and generative models as well as applications in neuroscience, healthcare, biology, and audio.
The ML@GT Student Conference gives students a chance to share their research and make connections across the Center. ML@GT congratulates all of this year's presenters and award winners.
