Summary
Lam Ngo is a research-focused software engineer blending 10 years of technical experience with current research internships at Aalto University and City, University of London, where he develops conditional diffusion models for anatomically accurate 3D cardiac surface reconstruction and federated dataset partitioning methods. He combines a strong ML research background—MSc work on deep reinforcement learning published at ISNN 2025—with practical C++/C# industry experience shipping game systems and live-ops features. Proficient in Python, PyTorch and TensorFlow, Lam moves fluidly between research prototypes and production-ready engineering, having implemented entity-component architectures and data-driven AI mechanics at Ubisoft and indie studios. His work uniquely spans spatial intelligence, HCI and agentic AI, applying large vision and language models to simulate realistic non-IID federated splits for computer vision. Based in Finland, he pairs mathematical training with hands-on system design, and brings a playful curiosity to coding (GitHub bio: "Behold a meowtain") that signals a creative, collaborative approach to problem solving.
10 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Games and Programming Skills, Master of Science - MS, Computer Games and Programming Skills at City St George’s, University of London
Bachelor of Science (B.S.), Mathematics, Bachelor of Science (B.S.), Mathematics at The University of the South
English, Vietnamese