Scholar

Alexander (Sasha) Sax

Google Scholar ID: PIq7jcUAAAAJ

FAIR (Meta AI)

computer visiongenerative AIembodied agents

Citations & Impact

All-time

Citations

4,847

H-index

i10-index

Publications

Co-authors

Contact

Resume

Academic Achievements

- CVPR Best Paper Award Nomination (X-Task Consistency, 2020)
- CVPR Best Paper Award (Taskonomy, 2018)
- NVIDIA Pioneering Research Award (Gibson Environment, 2018)
- Stanford University Distinction in Research (Computational Evidence for Structure in the Space of Tasks, 2018)
- Winner of CVPR Habitat Embodied Agents Challenge (Mid-Level Representations, RGB track, 2019)
- Outstanding Reviewer (ICLR '24, CVPR '22)
- Published several key papers, including Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D, etc.

Research Experience

- Senior Research Scientist at Meta FAIR
- Focuses on large-scale training for predictive and generative models using supervised learning and RL
- Develops multimodal 3D datasets, simulators, and techniques for efficient pretraining and finetuning

Education

- PhD: University of California, Berkeley, advised by Jitendra Malik and Amir Zamir (EPFL)
- MS and BS: Stanford University, advised by Silvio Savarese, graduated with an Erdős number of 3
- Interned at FAIR in the summer of 2022, mentored by Georgia Gkioxari

Background

Research Interests: Building multimodal foundation models to enable embodied agents that can perceive, act in, and communicate about the physical world.

Miscellany