About Me

Cristobal Eyzaguirre

Ph.D. student in Stanford's Vision and Learning Lab (SVL) studying efficient video understanding where I'm co-advised by Juan Carlos Niebles and Jiajun Wu. Prior to this I was a M.Sc.Eng. Student at Pontificia Universidad Católica de Chile, where I researched for over 2 years, with emphasis in Machine Reasoning, Meta Learning and Adaptive Computation Time models. Additionally I was a teaching assistant for the courses Artificial intelligence, Deep Learning, and the Capstone for Software Engineering majors, as well as teacher in the same institution's AI diploma course. I'm passionate about the outdoors (ultra-running, skiing, hiking, etc!) and scientific innovation.

My Career

Stanford University

Ph.D. student in Stanford Vision and Learning Lab (SVL) co-advised by Juan Carlos Niebles and Jiajun Wu.

Fall 2021 - Present
Ph.D. Student

Toyota Research Institute

Characterizing question complexity in video question answering.

Summer 2023
Research Intern

Google Research

Multimodal algorithms for video understanding.

Oct. 2020 - Jan. 2021
Research Intern

Zippedi

Research and implementation of computer vision algorithms for the automatic recognition of products in store shelves.
Models run locally on embedded devices, or on cloud GPU instances.

Winter 2019
Research Intern

Pontificia Universidad Católica de Chile

Worked on Adaptive Computation Time on recurrent and non-recurrent models (and ensembles).
Graduated with highest distinction.

July 2019 - June 2021
M.Sc. Engineering

IALab

Worked on DL models pertaining to Visual Reasoning, Adaptive Computation Time, Natural Language Processing and Action Recognition.

July 2017 - June 2021
Student Researcher

Pontificia Universidad Católica de Chile

Majored in Software Engineering (minor Data Science).
Graduated with distinction.

Jan. 2015 - Dec. 2019
B.Sc. Engineering

Publications

Streaming Detection of Queried Event Start
Cristobal Eyzaguirre and Eric Tang and Shyamal Buch and Adrien Gaidon and Jiajun Wu and Juan Carlos Niebles
Neural Information Processing Systems (NeurIPS), 2024
[arXiv] / [GitHub] / [Webpage] / [Blog] / [Poster] / [bibtex]

IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos
Yunong Liu and Cristobal Eyzaguirre and Manling Li and Shubh Khanna and Juan Carlos Niebles and Vineeth Ravi and Saumitra Mishra and Weiyu Liu and Jiajun Wu
Neural Information Processing Systems (NeurIPS), 2024
[arXiv] / [GitHub] / [Webpage] / [bibtex]

HourVideo: 1-Hour Video-Language Understanding
Keshigeyan Chandrasegaran and Agrim Gupta and Lea M. Hadzic and Taran Kota and Jimming He and Cristobal Eyzaguirre and Zane Durante and Manling Li and Jiajun Wu and Fei-Fei Li
Neural Information Processing Systems (NeurIPS), 2024
[arXiv] / [GitHub] / [Webpage] / [bibtex]

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?
Rylan Schaeffer and Dan Valentine and Luke Bailey and James Chua and Cristobal Eyzaguirre and Zane Durante and Joe Benton and Brando Miranda and Henry Sleight and John Hughes and Rajashree Agrawal and Mrinank Sharma and Scott Emmons and Sanmi Koyejo and Ethan Perez
Preprint, 2024
[arXiv] / [bibtex]

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
Rylan Schaeffer and Mikail Khona and Tzuhsuan Ma and Cristobal Eyzaguirre and Sanmi Koyejo and Ila Fiete
Conference on Neural Information Processing Systems (NeurIPS), 2023
[arXiv] / [Webpage] / [Poster] / [bibtex]

Revisiting the ''Video'' in Video-Language Understanding
Shyamal Buch and Cristobal Eyzaguirre and Adrien Gaidon and Jiajun Wu and Li Fei-Fei and Juan Carlos Niebles
(Oral) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
[arXiv] / [GitHub] / [Webpage] / [Blog] / [Poster] / [bibtex]

DACT-BERT Differentiable Adaptive Computation Time for an Efficient BERT Inference
Cristobal Eyzaguirre and Felipe del Rio and Vladimir Araujo and Alvaro Soto
(ACL Workshop) NLP Power! The First Workshop on Efficient Benchmarking in NLP, 2022
[arXiv] / [GitHub] / [bibtex]

Differentiable Adaptive Computation Time for Visual Reasoning
Cristobal Eyzaguirre and A. Soto
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
[arXiv] / [GitHub] / [Blog] / [bibtex]


Minor Contributions in Other Fields

Lagrangian scale decomposition via the graph Fourier transform
MacMillan, Theodore and Ouellette, Nicholas T
The Eurographics Association, 2022
[pdf] / [bibtex]

Evaluating Interactive Comparison Techniques in a Multiclass Density Map for Visual Crime Analytics
Svicarovic, Lukas and Parra, Denis and Lobo, Maria Jesus
The Eurographics Association, 2020
[pdf] / [bibtex]