I am Haiwen Huang, my Chinese name is 黄海文. I am a PhD student at University of Tübingen, co-supervised by Prof. Andreas Geiger and Dr. Dan Zhang, starting in Jan. 2022. I am also an ELLIS PhD student.

My PhD research focuses on improving the generalization of vision and multimodal models, enabling them to perform robustly across diverse tasks and domains. For example, I have developed methods that leverage 3D priors to enhance 2D object detection in GOOD (ICLR 2023) and use self-distillation to upsample features in Vision Foundation Models in LoftUp (coming soon). I have also contributed to building more reliable evaluations of open-vocabulary generalization in RENOVATE (NeurIPS 2024).

I envision my work through a three-tiered “research pyramid”: (1) Method Development, (2) Performance Evaluation, and (3) Normative Meta-Evaluation. My PhD projects focus on the first two levels, but my long-term goal is to address all three to ensure that AI truly benefits society.

🔴 I am curently seeking internships starting from Sept/Oct 2025 onward where I can explore methods for understanding and evaluating the generalization and capabilities of VLMs, as well as the scientific principles behind designing robust benchmarks for them.

Before my PhD studies, I completed my MSc in CS at University of Oxford, advised by Prof. Yarin Gal, and my undergrad study in Mathematics at Peking University, advised by Prof. Bin Dong. I have also worked as a researcher for a year at Megvii (previously known as Face++) with Xinyu Zhou as my group leader, studying large-scale annotation and OoD detection methods.

My CV is here.

Highlighted Research

• Renovating Names in Open-Vocabulary Segmentation Benchmarks
  • Haiwen Huang, Songyou Peng, Dan Zhang, Andreas Geiger
  • NeurIPS 2024.
  • OpenReview, Project Page
• Multimodal Dataset Upgrading: a New Challenge for Data Annotation
  • Haiwen Huang, Dan Zhang, Andreas Geiger
  • ICLR 2024 DPFM workshop
  • Paper
• GOOD: Exploring Geometric Cues for Detecting Objects in an Open World
  • Haiwen Huang, Andreas Geiger, Dan Zhang
  • ICLR 2023.
  • OpenReview, Code
• Decomposing Representations for Deterministic Uncertainty Estimation
  • Haiwen Huang, Joost van Amersfoort, Yarin Gal
  • 6th Bayesian Deep Learning workshop at NeurIPS 2021.
  • Poster
• Feature Space Singularity for Out-of-distribution Detection
  • Haiwen Huang, Zhihan Li, Lulu Wang, Sishuo Chen, Xinyu Zhou, Bin Dong
  • Safe AI 2021 workshop at AAAI-21.
  • Code, Poster

Teaching

• Computer Vision (summer term 2023)
• Seminar: Large-scale Generative Models: Prospects and Limitations (summer term 2023)