My name is Jorge Quesada. I am a PhD candidate in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. I work in the OLIVES Lab with Professor Ghassan AlRegib on machine learning for scientific imaging, where my current is focus on seismic interpretation.

My current work at the OLIVES lab centers on building self-supervised and domain-robust representation learning methods and stress-testing them under real distribution shift. In past projects, I have also explored human-in-the-loop systems, such as uncertainty-aware annotations that capture labeler expertise and prompting strategies for the Segment Anything Model in order to make workflows more reliable and interpretable in practice.

Beyond these, I have also worked in representation learning for neuroimaging, as well as inverse problems and mathematical optimization. I’m broadly motivated by questions at the intersection of natural and artificial intelligence—how brains and machines perceive, learn, and generalize—and I’m always excited to collaborate across domains.