Summary
Yun-da Tsai is an AI/ML research lead and founding member with a decade of experience building generative models, recommendation systems, bandit algorithms, adversarial ML, Bayesian methods, causal inference, and AutoML. He blends deep research (PhD from National Taiwan University and stints at Meta, NVIDIA Research, and UCLA) with hands-on full-stack and ML systems engineering to move prototypes into production. His recent work spans LLaMA-based GenAI, code SFT/RL post-training, and agentic design automation for chip design—reflecting a rare intersection of large-model capability engineering and hardware-aware automation. Comfortable in global remote teams, he has repeatedly bridged research and software engineering to deliver practical agent and LLM-driven solutions. Notably, he has transitioned research ideas into industry impact across Meta, NVIDIA, and startups, bringing Bayesian rigor and causal thinking to system-level ML design. Based in California, he combines academic depth with startup velocity to tackle high-leverage problems in autonomous design and generative AI.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at National Taiwan University
English, Chinese