Chao-Hui Huang

About Chao-Hui Huang

Applied research and AI platform leader with 25+ years of experience at the intersection of machine learning, computer vision, generative AI, and medical imaging, spanning academia and large-scale applied research environments. Proven ability to translate frontier AI research into production-grade systems, reusable frameworks, and reference platforms that influence scientific strategy, downstream products, and partner solutions.Deeply hands-on scientist–engineer with sustained contributions across multimodal modeling, spatial biology, medical imaging AI, and LLM-enabled knowledge systems. Widely published in Nature portfolio and venues, with active engagement at flagship conferences including CVPR, and AACR. Recognized for unifying applied research, engineering execution, and scientific credibility in real-world healthcare contexts.

Experience

1. Director, Ai Ml Applications

   辉瑞

   Nov 2024 — Present · San Diego, CA, US

   Built and scaled enterprise AI platforms transforming discovery research from computationally supported to computationally driven workflows across oncology programs. Architected and deployed QuST as a core spatial biology AI platform standardizing end-to-end ML pipelines adopted across research portfolios, enabling quantitative tissue microenvironment analysis and new biological insight. Established WSInsight as a production digital pathology AI platform forming the foundation of enterprise image analytics, reducing analysis cycles from weeks to hours while maintaining regulatory rigor. Owned a discovery AI ecosystem spanning spatial biology, digital pathology, LLM-driven biomarker discovery, and decision-support systems, including QuST/QuST-LLM (Nature npj Precision Oncology, 2025), H-Plot (AACR 2026), and KurtoRank ensemble ranking frameworks. Enabled cross-unit adoption across Oncology, Inflammation & Immunology, and Discovery Sciences, demonstrating scalable impact beyond individual groups. Directed development of production-grade ML infrastructure across cloud and HPC environments, integrating multimodal data sources into unified modeling workflows. Implemented GxP-aware MLOps practices supporting reproducibility, governance, and lifecycle management in regulated R&D. Founded and scaled an enterprise AI adoption organization engaging hundreds of scientists, accelerating cross-portfolio collaboration and digital transformation across R&D.

Education

• Chung Hua University

  Master's degree, Computer Science and Information Engineering

  1999 — 2001

• National Chiao Tung University

  Doctor of Philosophy (PhD), Electrical Engineering

  2001 — 2007

Skills

• R&D
• Software Engineering
• Statistics
• Matlab
• Visual Studio
• Image Analysis
• Machine Learning
• Scientific Computing
• Mathematical Modeling
• Research
• Java
• Cancer
• Data Analysis
• Bioinformatics
• Guitar Playing
• Biostatistics
• C
• Programming
• Computer Vision
• Home-Made Astronomical (Dobsonian) Telescope
• Algorithms
• Life Sciences
• Fpga
• Linux
• Medical Imaging
• Biotechnology
• C++
• Research and Development (R&D)
• Statistical Modeling
• Biomedical Engineering
• Python
• Balloon Sculpting
• Latex
• Automated Microscopy
• Neural Networks
• Simulations
• Statistical Data Analysis
• Microsoft Office
• R
• High Performance Computing