Welcome! I'm Ceyhun E. Kayan
Graduate Student at Drexel University
I develop intelligent systems at the intersection of machine learning and healthcare. My research explores how AI can learn from biological data to solve core problems. Through innovative approaches to representation learning, I aim to create models that understand concepts at their most essential level, bridging theoretical advances with real-world applications.
Research Areas
Computational Biology
Modeling protein-protein dynamics, predicting treatment responses and multi-omics data integration.
Language Models
Enhancing reasoning performance of Language Models and entropy-oriented sampling.
Machine Intelligence
Developing neuroscience and cognitive science inspired models for more humanistic machine intelligence.
Recent Publications
Intensity and Phase Stacked Analysis of a Φ-OTDR System Using Deep Transfer Learning and Recurrent Neural Networks
Applied Optics 62 (7), 1753-1764 • 2023
Adaptive resizer-based transfer learning framework for the diagnosis of breast cancer using histopathology images
Signal, Image and Video Processing 17 (8), 4561-4570 • 2023