Fueling innovative software
July 15-18, 2019
Portland, OR
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Romeo Kienzler

Romeo Kienzler
Chief Data Scientist, IBM Center for Open Source Data and AI Technologies


Romeo Kienzler is chief data scientist at the IBM Center for Open Source Data and AI Technologies (CODAIT) in San Francisco, owning the strategy lead for AI model training, and he’s a member of the IBM technical expert council and the IBM academy of technology—IBM’s leading brain trusts. He’s an associate professor for artificial intelligence at the Swiss University of Applied Sciences Berne. His current research focus is on cloud-scale machine learning and deep learning using open source technologies including TensorFlow, Keras, DeepLearning4J, Apache SystemML, and the Apache Spark stack. He’s the lead instructor of the advance data science specialization on Coursera with courses on scalable data science, advanced machine learning, signal processing, and applied AI with deep learning. He contributes to various open source projects and regularly speaks at international conferences, including significant publications in the area of data mining, machine learning, and blockchain technologies. His latest book Mastering Apache Spark V2.X has been translated into Chinese. He earned an MSc (ETH) in computer science with specialization in information systems, bioinformatics, and applied statistics from the Swiss Federal Institute of Technology Zurich.


2:35pm3:15pm Wednesday, July 17, 2019
Location: F151
Romeo Kienzler (IBM Center for Open Source Data and AI Technologies)
Average rating: ****.
(4.80, 5 ratings)
TensorFlow 2.0 successfully addressed the complaints of TensorFlow’s initial release and promises to become the go-to framework for many AI problems. Romeo Kienzler explores the most prominent changes in TensorFlow 2.0 and explains how to use the new features in your projects. He also examines TensorFlow Extended (TFX) and contrasts it with existing de facto standard frameworks like Apache Spark. Read more.