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I am Xindi Wu, a 3rd year 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 machine learning, developing data-centric approaches that trace model performance back to training data composition and introduce data-driven capabilities to optimize learning. 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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2024
12/2024: Attended NeurIPS 2024 and gave a poster presentation on ConceptMix (Poster).
10/2024: Our paper Corgi: Cached Memory Guided Video Generation is accepted to WACV 2025.
09/2024: Attended ECCV 2024 and gave a spotlight talk on ConceptMix (Slides) at Knowledge in Generative Models Workshop; and our Vision-Language Dataset Distillation received best paper award at Dataset Distillation Workshop.
09/2024: Our paper ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty is accepted to NeurIPS D&B 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!
2023
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.
05/2023: Started my internship at Meta Reality Lab in Redmond, WA on multimodal generative models.
02/2023: One paper accepted to CVPR 2023: Pix2Map: Cross-modal Retrieval for Inferring Street Maps from Images.
2022
08/2022: Started my PhD journey at Princeton University! 💪
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NeurIPS Datasets & Benchmarks 2024, ECCV Knowledge in Generative Models Workshop (Spotlight)
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WACV 2025
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TMLR 2024, ECCV Dataset Distillation Workshop (Best Paper)
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CVPR 2023
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KDD 2022
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CVPR 2022
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CVPR 2020 (Oral)
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CVPR Workshop, 2020
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BIBM 2019 (Oral)
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| Computational Biology, Codon Publications, Brisbane, Australia, 2019 | ||||||||||||||||||||||||
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ICIP 2019
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DSP 2018
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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.
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Reviewer: CVPR 24'/23'/22', ICLR 25'/24', ICCV 23', ECCV 24'/22', 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. |
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Website source from Jon Barron
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