Jeffrey A. Chan-Santiago

How much data is really necessary for strong performance?

Orlando, Fl

Hello, my name is Jeffrey Chan. I’m a third-year Ph.D. student in Computer Vision at the University of Central Florida (UCF), where I work under the supervision of Dr. Mubarak Shah in the Center for Research in Computer Vision (CRCV). I am a proud GEM Fellow and an ORC Fellow at UCF.

My research focuses on dataset distillation and improving the efficiency of deep learning training—particularly in settings with limited computational resources. I’m especially interested in rethinking how we use data and supervision to develop models that are smaller, faster, and just as effective as their larger counterparts.

Before UCF, I earned a B.Sc. in Computer Science with a double concentration in Mathematics at the University of Puerto Rico, Río Piedras (2019). During my undergraduate studies, I was a Puerto Rico LSAMP Bridge to the Doctorate Fellow and contributed to the BigDBee Project, where I developed self-supervised models for robust honeybee re-identification in natural environments. My early research interests included self-supervised learning, representation learning, and reducing human supervision in computer vision pipelines.

I also competed as an ICPC contestant, where my team qualified for the Caribbean Finals in both 2016 and 2017.

Outside of research, I enjoy experimenting in the kitchen. While I’m no Gordon Ramsay, I love reimagining recipes and blending Puerto Rican, Peruvian, and Chinese flavors. Some of my favorite creations include pesto fettuccine with ribeye steak, Peruvian Lomo Saltado, and my own take on chicken chow mein with fried plantains.

news

Jul 13, 2025
Excited to announce our paper MGD³: Mode-Guided Dataset Distillation using Diffusion Models was accepted as an oral presentation (Top 1.0%) at ICML 2025! Read the paper
May 21, 2022
Honeybee re-identification in video, new datasets and experimental study of the impact of self-supervision, has been accepted for Poster Presentation at Track 2 of CV4Animals Workshop at CVPR2022.
Dec 27, 2021
Automated Video Monitoring of Unmarked and Marked Honey Bees at the Hive Entrance, has been accepted at Frontiers in Computer Science.
Nov 17, 2021
Honeybee re-identification in video, new datasets and experimental study of the impact of self-supervision, has been accepted as a Short Paper at the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.
May 7, 2021
Accepted to participate in Eastern European Machine Learning Summer School will be held virtually on July 7-15, 2021.