Summary
Doug Jung is a Senior Principal ML Engineer in the San Francisco Bay Area with 11 years of experience building scalable machine learning and signal-processing solutions for IoT and cyber-physical systems. He blends deep academic training (PhD in Computer Engineering) with hands-on leadership at Palo Alto Networks, PARC, and SK Telecom to deliver interpretable, fast algorithms for anomaly detection, root-cause analysis, and predictive maintenance on noisy, high-dimensional sensor streams. His work spans advanced deep learning (RNN/LSTM/GRU, CNN, GAN, VAE) combined with Bayesian inference, active learning, and human-in-the-loop design to make models both accurate and actionable. Doug has led teams to productionize parallel approximation methods and causal inference pipelines for large-scale industrial and building-energy deployments. He’s especially skilled at turning ill-posed, unlabeled time-series data into human-interpretable analytics—an often-overlooked bridge between research models and operational CPS deployments.
10 years of coding experience
3 years of employment as a software developer
Master of Science (M.Sc.), EECS : Systems Science, Master of Science (M.Sc.), EECS : Systems Science at University of Michigan - Rackham Graduate School
Doctor of Philosophy (PhD), Computer Engineering, Doctor of Philosophy (PhD), Computer Engineering at Yale University
Bachelor of Science (B.S.), Electrical, Electronics and Communications Engineering, Bachelor of Science (B.S.), Electrical, Electronics and Communications Engineering at Yonsei University