I am a senior staff engineer at Qualcomm working on physical AI and autonomous driving. My research interests lie at the interesetcion of physical AI and generative AI. Specefically I am interetsed in multimodal large language models, world models, and their application for end-to-end autonomous driving.

Prior to joing Qualcomm, I did my PhD in Electrical Engineering at SUTD under supervision of Chau Yuen where I received the best PhD dissertation award for my PhD thesis. I also spent a year Linkoping University as a post doc working with Erik Larsson.

Selected Awards and Grants

• Qualcomm’s IP Achievemnet Award, 2025 (extremely competative).
• Best PhD Thesis Award from Singapore University of Technology and Design, 2019.
• FIRST Indusrty Workshop Outstanding Graduate Research Award, 2017.
• MediaTek Graduate Research Competition Award, 2017.
• Merlion PhD Award, 2014.
• President Graduate Fellowship from Singapore University of Technology and Design, 2013.
• Singapore Graduete Fellowsip Award, 2013.

Selected Publications

Generative Scenario Rollouts for End-to-End Autonomous Driving

What if your autonomous agent had an "internal theater" to rehearse the future? We introduce GeRo: a VLA model augmented with a latent world model for autonomous driving.
Core Idea: World Model 🤝 VLA
The formula: 👁️ + 📝 → N x (🧠 +🔮 → 🎮)

Adversarial Attacks on Deep-Learning Based Radio Signal Classification

As the pioneering work that introduced adversarial attacks to the wireless physical layer, this research exposes a critical vulnerability in DL-based systems. We demonstrate that nearly invisible adversarial perturbations can systematically trick modulation classifiers, outperforming traditional jamming techniques and fundamentally challenging the security of AI-driven communications.