Five projects trace the question I keep returning to: how can intelligent systems turn representations into reliable action?
2024—present · Selected work
01 / EMBODIED AI
Hierarchical mobile manipulation with VLN and VLA models
Developing an embodied-AI framework that decomposes language instructions into navigation, search, approach, grasp, and placement. The project studies VLN/VLM planning, VLA or diffusion-policy control, navigation–manipulation hand-offs, recovery, and safety in simulation with limited real-robot validation.
VLN
VLA
PyTorch
ROS
Robot simulation
M.Sc. dissertation
02 / AGENTS
Scientify: autonomous scientific discovery agents
Co-developed an LLM-agent framework that learns from evolving literature and generates research hypotheses. I built API orchestration, figure-digitisation skills, and local inference workflows for large-scale ablations.
Paper result · 72% of topics yielded validated hypotheses · 91% lower token cost
Generative 3D scenes for UAV reinforcement learning
Built an end-to-end pipeline for simulator-ready environments: generated scenes and assets, estimated support surfaces, checked collisions, and composed 3D Gaussian Splatting worlds for a downstream UAV RL loop.
3DGS
World models
SAM 3D
Simulation
Undergraduate thesis
04 / GEO AI
Mars landing-site selection from terrain constraints
Built a geospatial pipeline that combines illumination and slope constraints to rank candidate landing zones, turning Martian DEM evidence into an inspectable selection workflow.
Radar emitter recognition with DBSCAN + Transformer
Designed a two-stage pipeline for clustering pulse streams and classifying emitter types. It reached 89% accuracy, a 12-point absolute improvement over the CNN baseline on the same dataset.
Hotspots and Frontier Analysis of Lunar Exploration Using Knowledge Graph
Wang, Y., Kang, X., Zhang, S. · GRMSD 2024 · First author
2024
Mangrove Birdsong Classification with Unbalanced Data
Chen, W., Zhou, Y., Wang, Y., Zhang, X., Wang, J. · ArtInHCI 2024
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About
I’m an M.Sc. student in Computer Control and Automation at Nanyang Technological University, working on hierarchical mobile manipulation with VLN and VLA models. I received my B.Eng. in Automation from Beijing Institute of Technology.
My work moves between embodied AI, scientific agents, generated 3D environments, and control. I care about the point where a convincing model becomes a system that can make useful decisions under real constraints.
Nanyang Technological UniversityM.Sc. · Computer Control & Automation
Australian National UniversityExchange · AI & Control
Beijing Institute of TechnologyB.Eng. · Automation
04
Questions I’m exploring
A
Can software keep learning from a changing body of knowledge?
Research agents, evolving literature, memory, and the gap between retrieval and reasoning.
B
When does a generated world become useful rather than merely convincing?
3D representations, simulation, spatial constraints, and environments for autonomous systems.
C
How should navigation and manipulation become one reliable system?
Language-conditioned task decomposition, VLN–VLA hand-offs, recovery, and safety under real sensor and physics constraints.
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Contact & links
If our interests overlap, I’d be glad to compare notes, explore a research idea, or contribute to an ambitious prototype.
Open to research collaboration and lab opportunities