Tony Yang

"AI is cool I guess"

I build human-centered AI systems that expand what people can perceive, understand, and do. I collaborate with researchers around the world to build AI systems that create meaningful impact for people.

I was a Marie Curie Fellow at IMDEA Networks, working with Prof. Dr. Joerg Widmer on efficient multimodal wireless sensing systems as part of the MSCA 6th Sense Project.

Prior, I worked as a full-time AI research engineer at ImPhys TU Delft with Dr. Tao Qian, where I optimized AI models for medical imaging through advanced pruning techniques.

I pursued my Master's at TU Delft, where I worked with Dr. Guohao Lan and Dr. Xucong Zhang on immersive emotion recognition systems using eye-tracking and computer vision.

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News

Research

My research centers on building AI systems that expand human capabilities in the real world. I am interested in multimodal learning, computer vision, natural language processing, and agentic AI, especially where perception, reasoning, and decision-making come together. Across these areas, I care about systems that not only achieve strong technical performance, but also function reliably in practice and create meaningful impact for people. My long-term goal is to turn advances in AI into tools and systems that are genuinely useful, robust, and deployable. Some papers are highlighted.

Reverse Imaging: Any-Sequence Generalization for Cardiac MRI Segmentation
Yidong Zhao, Yi Zhang, Tongyun Yang, Maša Božić-Iven, Ayda Arami, Yuchi Han, Orlando Simonetti, Hui Xue, Petter Kellman, Sebastian Weingärtner, Qian Tao
MICCAI & IEEE Transactions on Medical Imaging, 2025
paper / code / bibTex

A physics-driven framework that estimates tissue properties (M0, T1, T2) from annotated cardiac MRI images using diffusion models, enabling physics-based synthesis of diverse unseen sequences for zero-shot generalization of segmentation models across different MRI contrasts.

Pruning nnU-Net with Minimal Performance Loss
Tongyun Yang, Yidong Zhao, Qian Tao
MIDL, 2025
paper / code / bibTex

Trained nnU-Net models contain substantial weight redundancy, with over 80% of weights removable through simple magnitude-based pruning while maintaining same performance across multiple medical segmentation tasks.

Projects

I enjoy developing AI-powered applications that make everyday life easier, more intuitive, and more efficient.

ScholarHighlights⭐️
Tongyun Yang
Browser Extension for Google Scholar, 2026
github / chrome web store

A browser extension that makes Google Scholar more informative at a glance by surfacing venue-quality badges, author-role signals, and flexible ranking data sources directly in the browsing workflow.

Teaching

A selection of teaching and mentoring roles that I have enjoyed across courses and student support.

Teaching

TU Delft, ET 4310 Supercomputing for Big Data (2024/25 Q1) / TA
TU Delft, CESE 4030 Embedded Systems Lab (2023/24 Q3) / TA
TU Delft, CESE 4000 Software Fundamentals (2023/24 Q1) / TA
TU Delft, CESE 4010 Advanced Computing Systems (2023/24 Q1) / TA
TU Delft, Graduate Student Mentor (2023/24)

Website adopted from Jon Barron