Ron Kohavi, PhD

I am a Microsoft Technical Fellow and corporate VP of the Analysis and Experimentation at Microsoft's Cloud and AI group. I was previously a Distinguished Engineer and GM, Partner Architect at Bing, General Manager for Microsoft's Experimentation Platform, director of data mining and personalization at Amazon.com, and VP of Business Intelligence at Blue Martini Software.

Check out my Linkedin profile , resume, publications, and talks.

Highlights:

Leading a team of about 110 data scientists and developers at Microsoft's Analysis and Experimentation.
The Harvard Businses Review article (10/2017) The Surprising Power of Online Experiments describes much of my work on expermentation
While I have been working in industry since 1995, I continue to publish sporadically. My h-index, a measure of productivity and impact of published work, is 57 according to Google Scholar, with over 42,000 citations to my work. Hirsch, who proposed the metric, suggested that an h-index of 10-12 is considered a useful guideline for tenure decisions at major research universities; a value of about 18 could mean a full professorship; 15-20 could mean a fellowship in the American Physical Society.
MIT CODE (Conference On Digital Experimentation) invited talk October 2016 Pitfalls in Online Controlled Experiments and 20 minutes video.
KDD 2015 Keynote, August 2015 Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 years .
ACM Recommender Systems industry keynote, Sept 2012 Online Controlled Experiments: Introduction, Learnings, and Humbling Statistics and Powerpoint PPTX.
Three of my papers are in the top 1,000 most cited articles in computer science, including the article Wrappers for Feature Subset Selection, which is in the top 300.
I was granted fifteen patents.
MineSet had powerful visualizations of models. Some examples (use quicktime) include: Evidence visualizer (Naive Bayes), Decision Table visualizer, Decision Tree visualizer and powerful data visualizations including: Scatter visualizer and Splat visualizer.
I started the MLC++ project, Machine Learning library in C++, which formed the basis for SGI's MineSet, then Blue Martini's analytics. Documentation includes C++ coding standards, MLC++ coding standards, and utilities.
Keynote at EC 10. A similar keynote at the Analytics Revolution, 2010 was recorded: Online Controlled Experiments: Listening to the Customers, not to the HiPPO (PDF) (PPTX) (video)
The paper Online Experimentation at Microsoft, 2009, was recognized as top 30 Microsoft ThinkWeek paper and an early version of it won 3^rd place at the Third workshop on Data Mining Case Studies and Practice Prize, 2009.
Scientific Advisor to Trusted Opinion, 2007-2008.
Member of Technical Advisory Board, mySimon, 1999-2000 (until they were bought by CNET).
General Chair, KDD 2004.

Short Bio

Ronny Kohavi is a Microsoft Technical Fellow and corporate VP of Microsoft's Analysis and Experimentation at Microsoft's Cloud and AI group. He was previously a Distinguished Engineer and Partner Architect at Bing. He joined Microsoft in 2005 and founded the Experimentation Platform team in 2006. Prior to Microsoft, he was the director of data mining and personalization at Amazon.com, and the Vice President of Business Intelligence at Blue Martini Software, which went public in 2000, and later acquired by Red Prairie. Prior to joining Blue Martini, Kohavi managed MineSet project, Silicon Graphics' award-winning product for data mining and visualization. He joined Silicon Graphics after getting a Ph.D. in Machine Learning from Stanford University, where he led the MLC++ project, the Machine Learning library in C++ used in MineSet and at Blue Martini Software. Kohavi received his BA from the Technion, Israel. He was the General Chair for KDD 2004, co-chair of KDD 99's industrial track with Jim Gray, and co-chair of the KDD Cup 2000 with Carla Brodley. He was an invited speaker at the National Academy of Engineering in 2000, a keynote speaker at PAKDD 2001, an invited speaker at KDD 2001's industrial track, a keynote speaker at EC 10 (2010), a keynote speaker at Recsys 2012, a keynote speaker at Emetrics 2014, a keynote speaker at KDD 2015, and and a keynote speaker at Conversion Hotel 2017. He was an invited speaker at all five MIT Code conferences (Conference On Digital Experimentation) in 2014, 2015, 2016, 2017, 2018. His papers have over 42,000 citations and three of his papers are in the top 1,000 most-cited papers in Computer Science. In 2016, he was named the 5th most influential scholar in AI and the 26th most influential scholar in Machine Learning. He is currently co-authoring a book (due Q4 2019) titled Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing with Diane Tang and Ya Xu.

ronnyk@ live dot com