Xindi(Cindy) Wu

I am Xindi Wu, a Ph.D. student in Computer Science at Princeton University, advised by Prof. Olga Russakovsky. Previously I was in Master of Science in Computer Vision at Carnegie Mellon University. I was very fortunate to be advised by Prof. Deva Ramanan and work with Prof. Min Xu and Prof. Haohan Wang and Prof. Kris Kitani. I was admitted to the Honors Youth Program at Xi'an Jiaotong University.

My research focuses on data for efficient multimodal ml, with a particular interest in dataset distillation and generation. I am happy to collaborate and answer questions about my research, feel free to send me an email. I especially encourage students from underrepresented groups to reach out.

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News
08/2024: Our paper Corgi: Cached Memory Guided Video Generation is accepted to AI4VA Workshop at ECCV 2024.
07/2024: Our paper Vision-Language Dataset Distillation is accepted to TMLR 2024.
07/2024: Gave a talk on Compositional Generation Evaluation (Slides) at Google Research.
06/2024: Attended CVPR 2024 and gave a talk on Scaling Down before Scaling Up: Recent Progress on Dataset Distillation (Slides | Video) at CVPR 2024 Dataset Distillation Workshop.
02/2024: Led a discussion on Scaling Law in the PLI Vision-Language Reading Group (Slides).
02/2024: I am TAing for COS 429 Computer Vision in Spring 2024.
01/2024: Passed my general exam (quals)! (Video | Slides | Reading List). Huge thanks to my committee members Olga Russakovsky, Szymon Rusinkiewicz and Adji Bousso Dieng for their support and feedback!
09/2023: I am TAing for COS 597O Advanced Topics in Computer Science: Deep Generative Models, with focus on Methods, Applications & Societal Considerations in Fall 2023.
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06/2023: Attended CVPR 2023 and presented Pix2Map (Poster).
05/2023: Started my internship at Meta Reality Lab in Redmond, WA on multimodal generative models.
08/2022: Started my PhD journey at Princeton University! 💪
Publications & Preprints
NeurIPS Datasets & Benchmarks 2024, ECCV Knowledge in Generative Models Workshop (Spotlight)
ECCV AI4VA Workshop, 2024
TMLR 2024, ECCV Dataset Distillation Workshop (Best Paper)
CVPR 2023
KDD 2022
Kristen Grauman, et al .
CVPR 2022
CVPR 2020 (Oral)
CVPR Workshop, 2020
BIBM 2019 (Oral)
Computational Biology, Codon Publications, Brisbane, Australia, 2019
ICIP 2019
DSP 2018
Education
Princeton University, USA
Ph.D. in Computer Science • Aug. 2022 to Now
Advisor: Prof. Olga Russakovsky
Carnegie Mellon University, USA
M.S. in Computer Vision • Sept. 2020 to Dec. 2021
Advisor: Prof. Deva Ramanan
Xi'an Jiaotong University, China
B.Sc. in Computer Science • Sep. 2016 to July 2020
Advisor: Prof. Jinjun Wang, Prof. Pengju Ren
National University of Singapore, Singapore
Summer session • Human Computer Interaction •July 2017 to Aug. 2017

Experiences
Meta Reality Labs, Meta.
Research Scientist Intern • May. 2023 to Aug. 2023
Mentor: Dr. Shane Moon, Dr. Uriel Singer Dr. Luna Dong, Dr. Zhaojiang Lin, Dr. Paul Crook, Dr. Andrea Madotto Dr. Ethan Xu
Perception ML Team, Snap Inc.
Machine Learning Engineer • Feb. 2022 to July 2022
Research Intern • May. 2021 to Aug. 2021
Mentor: Dr.
Alireza Zareian and Dr. Chen Wang
CMU Argo AI Center for Autonomous Vehicle Research, ArgoAI
Capstone Project • Feb. 2021 to Dec 2021
Advisors: Prof. Deva Ramanan. Mentor: Dr. Aljoša Ošep
Megvii (Face ++) Research, Megvii
Computer Vision Research Intern • June 2020 to Sept. 2020
Mentor: Banghuai Li
Computational Biology Department, Carnegie Mellon University, USA
Research Intern • March 2019 to Feb. 2020
Advisor: Prof. Min Xu
Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, China
Research Intern • Dec. 2017 to Feb. 2019
Advisors: Prof. Pengju Ren and Prof. Jinjun Wang

Teaching
TA: COS 429 Computer Vision, Spring 2024, Princeton, with instructor: Vikram V. Ramaswamy and Felix Heide
TA: COS 597O Advanced Topics in Computer Science: Deep Generative Models:Methods, Applications & Societal Considerations. Fall 2023, Princeton, with instructor: Adji Bousso Dieng.
Professional Activities & Outreach

Reviewer: CVPR 23'/22', ICCV 23', ECCV 22', ICLR 24', Neurips 23', ICRA 24', BMVC 20', IJCAI 20', workshop: ICLR ME-FoMo 23', Neurips Interpolate 22'.
Committee Member: Diversity, Equity and Inclusion Committee at Robotics Institute, CMU.


Website source from Jon Barron and Yaohui Cai