Summary
Frank Kornet is a machine learning engineer in the Greater Houston area combining 30+ years of IT leadership with recent hands-on AI/ML expertise from a Georgia Tech Master’s in Analytics (4.0 GPA). He designs and ships production ML systems—from a farmhouse audio pipeline that assesses chicken health to diffusion models for chirp quantification—while drawing on deep domain experience in oil & gas, finance, healthcare, and genetic counseling. Previously he led cloud microservices and quantitative tools at JPMorgan Chase and has a track record of scaling programs and teams across global enterprises like Shell and T-Systems. Comfortable translating business goals into technical roadmaps, he blends project leadership, financial modeling, and practical data science to deliver measurable outcomes. Passionate about sharing work, he maintains a GitHub portfolio of predictive modeling, deep learning and NLP projects that reflect his preference for applied, noisy real-world datasets.
10 years of coding experience
28 years of employment as a software developer
Master of Business Administration - MBA, Master of Business Administration - MBA at Rotterdam School of Management, Erasmus University
Master's degree, Analytics (including AI and ML), 4.0, Master's degree, Analytics (including AI and ML), 4.0 at Georgia Institute of Technology
Immersive Data Science Program, Immersive Data Science Program at Flatiron School
Bachelor of Science in Computer Science - BS, Bachelor of Science in Computer Science - BS at Gemeentelijke HTS
English, Dutch, German