Juan Carlos Niebles earned a degree in Electronics Engineering in 2002 from Universidad del Norte, Colombia. He later received a Master of Science degree in Electrical and Computer Engineering in 2007 from the University of Illinois at Urbana-Champaign, and a Ph.D. in Electrical Engineering from Princeton University in 2011.
Since 2021, Juan Carlos has been a Research Director at Salesforce and an Adjunct Professor of Computer Science at Stanford. He is co-Director of the Stanford Vision and Learning Lab and previously served as Associate Director of Research at the Stanford-Toyota Center for AI Research. He was also a Senior Research Scientist at the Stanford AI Lab from 2015 to 2021.
My expertise
His research interests include computer vision, machine learning, multimodal AI, and autonomous agents. Juan Carlos has published over 100 research articles in top-tier academic conferences and journals.
When I'm not working
I enjoy playing board games with my family or going for a bike ride.
We present TACO, a family of multi-modal large action models designed to improve performance on complex questions that require multiple capabilities and demand multi-step solutions.
Huan Wang, Shelby Heinecke, Juan Carlos Niebles, Caiming Xiong TL;DR: We release xLAM, a series of LLMs optimized for function calling and AI Agents. It offers several variants designed to serve different application…
TL;DR: Imagine a world where machines comprehend 3D objects just as humans do. The ULIP (CVPR2023) and ULIP-2 projects, backed by Salesforce AI, are making this a reality by revolutionizing 3D understanding. ULIP…
TLDR; We introduce the Salesforce CausalAI Library, an open source library for causal analysis of time series and tabular data. The Salesforce CausalAI Library aims to provide a one-stop solution to the various…
