Romeo Kienzler
Senior Scientific Software Engineer
STSM - Physics & AI for Climate Impact (PHACT) - IBM Research Europe
Säumerstrasse 4, 8803 Rüschlikon, Switzerland
Element/Matrix: @romeokienzler:matrix.org
Mastodon: @[email protected]
PGP-Message: https://encrypt.to/romeokienzler
List of prepared >>Talks<<
Slides of my talks:
https://github.com/romeokienzler/slides/
Recordings of my talks:
https://www.youtube.com/c/RomeoKienzler
Courses I'm teaching (which you can get for free http://ibm.biz/community-coursera):
-
IBM Advanced Data Science Certificate on coursera
https://www.coursera.org/specializations/advanced-data-science-ibm -
Fundamentals of Scalable Data Science
http://coursera.org/learn/ds -
Advanced Machine Learning and Signal Processing
http://coursera.org/learn/advanced-machine-learning-signal-processing -
Scalable Machine Learning on Big Data using Apache Spark part of IBM AI Engineering Professional Certificate https://www.coursera.org/learn/machine-learning-big-data-apache-spark/
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Applied AI using DeepLearning
https://www.coursera.org/learn/ai/ -
Deep Learning (in CAS Practical Machine Learning)
https://www.bfh.ch/ti/de/weiterbildung/cas/practical-machine-learning/ -
Hyperledger (in BlockChain elective)
https://www.fhnw.ch
Romeo is a data scientist working for IBM and an advocate for ethical machine learning, transparency and privacy
PLEASE DON'T USE THE BIO AS SPEAKER ANNOUNCEMENT - IT IS ONLY THERE TO SHOW OFF TO GET PAPERS ACCEPTED - PLEASE USE SPEAKER ANNOUNCEMENT ABOVE
Romeo Kienzler is CTO and Chief Data Scientist of the IBM Center for Open Source Data and AI Technologies (CODAIT) in San Fransisco.
He holds an M. Sc. (ETH) in Computer Science with specialisation in Information Systems, Bioinformatics and Applied Statistics from the Swiss Federal Institute of Technology Zurich.
He works as Associate Professor for Artificial Intelligence at the Swiss University of Applied Sciences Berne and Adjunct Professor for Information Security at the Swiss University of Applied Sciences Northwestern Switzerland (FHNW). His current research focus is on cloud-scale machine learning and deep learning using open source technologies including TensorFlow, Keras, and the Apache Spark stack.
Recently he joined the Linux Foundation AI as lead for the Trusted AI technical workgroup with focus on Deep Learning Adversarial Robustness, Fairness and Explainability.
He also contributes to various open source projects. He regularly speaks at international conferences including significant publications in the area of data mining, machine learning and Blockchain technologies.
Romeo is lead instructor of the Advance Data Science specialisation on Coursera https://www.coursera.org/specializations/advanced-data-science-ibm with courses on Scalable Data Science, Advanced Machine Learning, Signal Processing and Applied AI with DeepLearning
He published a book on Mastering Apache Spark V2.X (http://amzn.to/2vUHkGl) which has been translated into Chinese (http://www.flag.com.tw/books/product/FT363).
He published a book on "What's new in TensorFlow 2.x" with O'Reilly (https://learning.oreilly.com/library/view/whats-new-in/9781492073727/)
Recently, he lead the donation of the JupyterLab/Elyra nocode/locode Data and AI system to the Linux Foundation AI. Elyra democratizes Data and AI Pipeline development, execution and productionization.
He is also main author and contributor to the CLAIMED framework - the Component Library for AI, Machine Learning, ETL and Data Science which further democratizes Data and AI by providing opinionated, coarse grained reusable component for Data and AI including TrustedAI.
Romeo Kienzler is a member of the IBM Technical Expert Council and the IBM Academy of Technology - IBM’s leading brain trusts. #ibmaot
