ML Pipelines for Research: Stop Doing R|D, Start Doing R&D
ML Pipelines for Research: Stop Doing R|D, Start Doing R&D


This workshop will harness the pipeline concept towards manageable high throughput experimentation in ML/DL research. We will distinguish between top-down pipelines used in production and a bottom-up design that we propose for researchers. We will see how to take a “conventional” flower detection example and employ the bottom-up design principle. While integrating typical research steps, we will mitigate some of the problematic aspects of moving from research to development.


Researcher first, developer second, in the last 5 years Ariel worked on various projects from the realms of quantum chemistry, massively-parallel supercomputing and deep-learning computer-vision. With AllegroAi, he helped build an open-source R&D platform (Allegro Trains), and later went on to lead a data-first transition for a revolutionary nanochemistry startup (StoreDot). Answering his calling to spread the word on state-of-the-art research best practices, He recently took up the mantle of Evangelist at ClearML. Ariel received his PhD in Chemistry in 2014 from the Weizmann Institute of Science. With a broad experience in computational research, he made the transition to the bustling startup scene of Tel-Aviv, and to cutting-edge Deep Learning research.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google