Weikai Huang

Hi, I am an undergrad at the University of Washington, advised by Prof. Ranjay Krishna, PhD student Jieyu Zhang, and PhD student Zixian Ma at UW CSE RAIVN Lab. Currently I am also a student collaborator at Allen Institute for AI working on VLM training and data generation.

Research Interests:

2D and 3D Grounding and Tracking: Developing robust object detection, grounding and tracking systems that can understand spatial relationships and temporal dynamics across different modalities, with applications in autonomous systems and embodied AI.
Controllable Generative Models: Building controllable and interpretable generative models for visual content creation, enabling precise control with more fine-grained control signal.
Compositional and Scalable Synthetic Visual Data Generation: Creating programmable and scalable synthetic data generation pipelines for Vision Foundation Model includes: VLMs, VLAs, Detectors, Generative models.
Vision and Spatial centric VLM: Advancing vision-language models to better understand complex spatial reasoning, multi-step visual tasks, and multimodal tool-use scenarios, bridging the gap between visual perception and actionable intelligence.

📝 Publications

(* denotes equal contribution)

University of Washington
B.S. in Computer Science, Minor in Applied Mathematics and Music
2023 – 2027 (Expected)

[2024-9] Our work Task Me Anything is accepted to NeurIPS 2024.
[2024-7] Our work m&m’s: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Tasks is accepted to ECCV 2024.

Organizer of the Synthetic Data for Computer Vision Workshop at CVPR 2024 and CVPR 2025 (website)
TA for UW CSE 455: Computer Vision, Autumn 2025 (course page)
TA for UW CSE 493G: Deep Learning, Spring 2025 (course page)

Email: weikaih@cs.washington.edu
Twitter (X): @weikaih04
Instagram: @weikaih04
Linkedin: Weikai Huang
Wechat: hwk18105962347