Jue Guo
"We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard." – John F. Kennedy
301 Davis Hall Desk 12
12 Capen Hall
Buffalo, New York 14260-1660
Jue Guo is a Ph.D. candidate in Computer Science at the University at Buffalo, advised by Prof. A. Erdem Sariyüce. His teaching portfolio spans core areas in machine learning, with a focus on deep learning and pattern recognition, where he has guided and inspired the next generation of computer scientists.
His research explores advanced machine learning methodologies across a range of domains, including image classification, natural language processing, continual learning, and adversarial machine learning.
Technically, Jue is proficient in Python, PyTorch, and JavaScript, and adept at bridging theory with practice—developing scalable, research-grade models while maintaining strong algorithmic rigor. His ability to integrate complex ML frameworks with domain-specific challenges positions him as a creative and forward-looking contributor to the field.