The application of artificial intelligence (AI) and machine learning to business and IT, from intelligent IT operations (AIOps) to service management to software testing, is keeping the data revolution moving at lightning speed.
That’s why data science remains a popular concentration for computer science students who have the talent for math and analytics. And it’s why more organizations are clamoring for data scientists who can help make decisions faster and put their businesses ahead of competitors.
To help you keep up, TechBeacon assembled this list of leading data scientists to follow on Twitter.
[ Enterprise Service Management brings innovation to the enterprise. Learn more in TechBeacon’s new ESM guide. Plus: Get the 2019 Forrester Wave for ESM. ]
Follow the leader
Dean Abbott
Co-founder and chief data scientist, SmarterHQ
@deanabb
Also founder and president of Abbott Analytics, Abbot is the author of Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst and co-author of the IBM SPSS Modeler Cookbook. Since 1987, he has developed and applied techniques in data mining, data preparation, and data visualization methods to business and research problems.
Kenneth Cukier
Senior editor, The Economist
@kncukier
Cukier is the data editor for The Economist and a co-author of the book Big Data: A Revolution That Will Transform How We Live, Work, and Think. A popular speaker and a member of the World Economic Forum’s council on data-driven development, Cukier is a regular guest on the BBC, CNN, and NPR. From 2002 to 2004, he was a research fellow at Harvard’s Kennedy School of Government. He is also a fellow at Oxford’s Saïd Business School, where he conducts AI research.
Nando de Freitas
Scientist lead for the machine learning team, Google DeepMind
@NandoDF
Professor of computer science at Oxford University, de Freitas is a specialist in machine learning with emphasis on neural networks, Bayesian optimization and inference, and deep learning. As the principle scientist at Google DeepMind, he helps the organization in its mission to use technologies for widespread public benefit and scientific discovery, while ensuring safety and ethics. His work in machine learning has earned him numerous awards, including best-paper awards at the International Conference on Machine Learning and the International Conference on Learning Representations, both in 2016.
John Elder
Founder, Elder Research, Inc.
@johnelder4
As the founder of data mining consultancy Elder Research, Dr. Elder is a frequent keynote speaker and co-author of three books: the Handbook of Statistical Analysis and Data Mining Applications, Ensemble Methods in Data Mining, and Practical Text Mining. His company focuses on investment, commercial, and security applications of advanced analytics, text mining, image recognition, and biometrics. He is an adjunct professor at the University of Virginia, where he teaches the optimization of data mining.
Fei-Fei Li
Professor of computer science, Stanford University
@drfeifei
Also co-director of Stanford’s Human-Centered AI Institute, Li is one of the pioneers in AI, machine learning, and cognitive neuroscience. She is a prolific writer and researcher, having published about 180 peer-reviewed papers. In 2007, as an assistant professor at Princeton University, she led a team of researchers to create the ImageNet project, a massive visual database to be used with software that recognizes visual objects. That work influenced the “deep learning” revolution over the next decade. While serving as director of the Stanford Artificial Intelligence Lab (SAIL) from 2013 to 2018, she co-founded the nonprofit AI4ALL, which strives to increase diversity and inclusion in the field of AI.
Bernard Marr
Founder and CEO, Bernard Marr & Co.
@BernardMarr
Marr is an author, futurist, frequent keynote speaker, and strategic advisor on data insights to businesses and governments. He advises and coaches many of the world’s best-known organizations and was voted by LinkedIn as one of the top five business influencers in the world and the No 1 influencer in the UK. He is a contributor to the World Economic Forum, and the author of many articles and books, including Big Data: Using SMART Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance.
Hilary Mason
Former general manager for machine learning, Cloudera
@hmason
Mason founded Fast Forward Labs, and served as chief scientist at Bitly for four years. Currently on the board at the Anita Borg Institute for Women and Technology, she co-founded HackNY, and is a member of NYCResistor, a hacker collective in Brooklyn.
Andrew Ng
Founder and CEO, Landing AI
@AndrewYNg
Also the founder of deeplearning.ai, Ng has been the chief scientist at Baidu Research, adjunct professor at Stanford University, and founder and chairman of the board at Coursera, which is why he’s considered a pioneer in online education. He founded the Google Brain project, which developed large-scale artificial neural networks, including one that taught itself to recognize cats in videos. He specializes in deep learning and has published widely in machine learning and other fields.
Lillian Pierson
Business and data strategist, Data-Mania LLC
@Strategy_Gal
Pierson is a data strategist, advisor, and trainer who works with executive teams to offer oversight and recommendations for optimal data science and engineering operations. She focuses on solving business problems with various data technologies and methods that entrepreneurs can put into practice. She has been data strategist at Data-Mania, a provider of data training and advisory services, since 2012.
Kira Radinsky
Chairwoman and CTO, Diagnostic Robotics
@KiraRadinsky
Radinsky started SalesPredict in 2012 to advise salespeople on how to identify and handle promising leads. “My true passion,” she said in an MIT Technology Review article from 2013, “is arming humanity with scientific capabilities to automatically anticipate, and ultimately affect, future outcomes based on lessons from the past.” She is regarded as a pioneer in predictive analytics, has won many awards, and was recognized in 2015 as a rising star of enterprise technology in the “Forbes 30 Under 30” listing.
Richard Socher
Chief scientist, Salesforce
@RichardSocher
Before he began his PhD studies at Stanford University, Socher was a visiting grad student at Princeton University, where his team took first place in the semantic robot vision challenge in 2007. Along with Fei-Fei Li, he worked on the ImageNet project there. Later, his PhD dissertation showed that deep learning could be successfully applied not only to natural-language processing, but also to solving different natural-language processing tasks within a combined machine-learning multi-tasking model.
Chris Surdak
Executive partner, Gartner
@CSurdak
Former rocket scientist Surdak is now focused on the design and implementation of intelligent automation technologies like robotic process automation (RPA), cognitive computing, machine learning, and AI. He is the author of Jerk: Twelve Steps to Rule the World and Data Crush: How the Information Tidal Wave Is Driving New Business Opportunities, which won GetAbstract’s International Book of the Year prize in 2014. With a law degree and MS from Wharton Business School, Surdak applies his broad interests across a variety of industries that are exploring big data and AI.
Sebastian Thrun
Founder and president, Udacity
@SebastianThrun
Thrun founded Google[x] and Google’s self-driving automobile project. His robotic vehicle, “Stanley,” won the 2005 DARPA Grand Challenge, and it has been on exhibit in the Smithsonian Institution’s National Museum of American History. Thrun is an adjunct professor at Stanford University, the recipient of numerous awards and prizes, and the author of or contributor to many books and hundreds of papers. He is well known for his probabilistic algorithms for robotics and robotic mapping.
John Myles White
Engineering manager, Facebook
@johnmyleswhite
White is a data scientist at Facebook, a former Julia developer, and a one-time grad student in psychology. In 2013 he worked as a researcher at MIT’s Computer Science and Artificial Intelligence Lab. A specialist in machine learning, statistics, data science, and the R language for statistics, White is a speaker and the author of Bandit Algorithms for Website Optimization and co-author of Machine Learning for Hackers and Machine Learning for Email. Check out his paper “Interpretational Challenges with Ideal Point Models,” from January of this year.
Share your picks for top data scientists
We chose not to rank here, organizing by alphabetical for these brightest minds in AI and machine learning.
Share your top picks for must-follow data science types in the comments section below.
[ Learn how robotic process automation (RPA) can pay off—if you first tackle underlying problems. See TechBeacon’s guide. Plus: Get the white paper on enterprise requirements. ]
[ Learn how to transform your IT with AIOps in TechBeacon’s guide. Plus: Download the analyst paper on how AI is changing the role of IT. ]
