Pil Kim
Advisor at POSCO DX
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolPil Ho Kim is an AI and manufacturing technology leader with 27 years of hands-on experience translating human expertise into digital systems and currently advising POSCO DX on a Smart Cognition Platform for autonomous factories and worker safety. He blends deep academic credentials (Ph.D. from Georgia Tech) with industry leadership across POSCO, Samsung Display, and AWS, driving applied research into production-ready AI for manufacturing. Known for back-end cognitive system design and ML deployment, he has practical experience using cloud ML services—evidenced by contributions to an AWS Korean AI/ML workshop that applied SageMaker transfer learning for image classification. Pil Ho’s career spans research fellowships in Europe to executive roles in Korea, giving him an uncommon mix of global research rigor and industrial-scale delivery. He often frames human skills as digitizable assets, prioritizing safety and operational autonomy in complex factory environments.
11 years of coding experience
15 years of employment as a software developer
MS Electronic and Electrical Engineering, MS Electronic and Electrical Engineering at Pohang University of Science and TechnologyPh.D Electrical and Computer Engineering, Ph.D Electrical and Computer Engineering at Georgia Institute of TechnologyBS Electronic Engineering, BS Electronic Engineering at Pusan National University
Korean, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
deeplearning-ai10
transfer-learning10
machine-learning10
deep-learning10
ai10
ml10
sagemaker10
aws9
algorithms9
jupyter-notebook8
python8
Programming languages (4)
Github contributions (5)
aws-samples/aws-ai-ml-workshop-kr
Sep 2018 - Oct 2019
A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.
Role in this project:
ML Engineer
ML EngineerContributions:36 commits, 11 PRs, 19 pushes in 1 year 1 month
Contributions summary:Pil's commits focus on image classification tasks within the context of the AWS AI/ML workshop. They modified a Jupyter Notebook file to incorporate transfer learning using the Amazon SageMaker image classification algorithm. Their work included modifying the existing code for training, specifically updating training parameters and data upload configurations. The commits indicate a hands-on approach to applying image classification techniques and utilizing SageMaker for model training and deployment.
sagemakerhands-onmxnetai-mlworkshop-materials
pilhokim/ai-ml-workshop
Apr 2018 - Oct 2018
Contributions:58 commits, 1 PR, 49 pushes in 6 months
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