Fu-ming Guo is a Chief Architect in AI/ML with 11 years of industry experience and a strong research pedigree spanning MIT-IBM Watson, Google DeepMind, and multiple top-tier product teams. He specializes in natural language understanding and efficient deployment of large DNNs—delivering papers like a BERT ICLR work and practical systems that scaled to billions of users at Evernote and Baidu. At Visa he accelerated pre-training by 20x through custom CUDA, NCCL, and 4D parallelism and designed an extreme-efficiency MoE payment foundational model, reflecting an uncommon blend of algorithm-system co-design. Equally fluent in Java, Python and C++, he ships production-grade ML on TensorFlow, PyTorch and JAX across GPUs, TPUs and SageMaker. Beyond engineering, he has 10+ publications and domain fluency in finance (Bloomberg-certified), enabling him to bridge ML research, productization and industry-specific constraints.
11 years of coding experience
9 years of employment as a software developer
Graduate Certification Economics and Data Science, Graduate Certification Economics and Data Science at Massachusetts Institute of Technology
Bachelor of Engineering - BE Electrical Engineering and Computer Science, Bachelor of Engineering - BE Electrical Engineering and Computer Science at Nankai University
PhD candidate Computer Science, PhD candidate Computer Science at University of Maryland
Master of Science - MS Electrical and Computer Engineering, Master of Science - MS Electrical and Computer Engineering at Northeastern University
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