Hao Dong

I received my Ph.D. from ETH Zurich, co-advised by Prof. Eleni Chatzi and Prof. Olga Fink. I received my Master's degree in Control, Robotics, and Autonomous Systems from Aalto University in 2022. During my Master's, I also spent time at TUM as an exchange student, at CVG through the ETH Robotics Student Fellowship, and at StachnissLab, where I completed my Master's thesis. I received my Bachelor's degree from Xi’an Jiaotong University in 2020.

My long-term research vision is to advance a new generation of multimodal intelligent systems, characterized by robustness, reliability, and adaptability.

I'm always open for discussions or collaborations, feel free to get in touch via email.

New homepage: https://donghao51.github.io/

Selected Publications

Towards Reliable Multimodal Learning for Real-world Systems

Hao Dong

Doctoral Thesis at ETH Zurich, 2026

thesis

Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study

Hao Dong, Hongzhao Li, Shupan Li, Muhammad Haris Khan, Eleni Chatzi, Olga Fink

arXiv, 2026

Hao Dong

Selected Publications

Towards Reliable Multimodal Learning for Real-world Systems

Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study

Adaptive Confidence Regularization for Multimodal Failure Detection

Towards Multimodal Domain Generalization with Few Labels

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models

Adapting Vision-Language Models Without Labels: A Comprehensive Survey

To Trust Or Not To Trust Your Vision-Language Model's Prediction

Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and Segmentation

Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization

MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities

Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation

Unseen Visual Anomaly Generation

DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution Detection

Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework

Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework

SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation

Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors

Online Pole Segmentation on Range Images for Long-term LiDAR Localization in Urban Environments

Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments

Invited Talks

Towards Reliable Multimodal Learning for Real-world Systems

Multi-modal Fusion and Generalization

Robust Robot Perception: From Single-modality to Multimodality

Academic Services