Muhammed Hunaid Topiwala
Computer science
Hometown: Bengaluru, Karnataka, India
Graduation date: Spring 2026
FURI | Fall 2024, Summer 2024
Next-Gen Immunotherapies: Analysis of Large TCR Repertoires to Create a TCR Cluster Benchmark Using the catELMO Embedding Technique
Accurate clusters in large-scale TCR datasets provide candidate disease-specific receptors and are vital to repertoire classification for personalized immunotherapy. This study investigates why catElmo, a bidirectional LSTM model, outperforms GIANA, a handcrafted static embedder, through an examination of various metrics, and noise mitigation strategies using one density and one distribution-based algorithm for the Unsupervised Learning task: clustering of TCR-Epitope data.
Mentor: Heewook Lee
It’s hip to be square.
Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future.
Right click the image to save it to your computer.