Who Are the Top Data Scientists at Machine Learning’s Top Conference?

Ranking The Most Published Researchers at NeurIPS/NIPS

James Kotecki
Mar 20, 2019 · 2 min read

The Conference on Neural Information Processing Systems (NeurIPS, formerly NIPS) started in 1987, long before machine learning was cool. These days, it’s a “recruiting frenzy for tech giants, banks, and hedge funds.” The event attracts top minds from companies like Google and Microsoft, and from institutions like MIT and Stanford. It is, in other words, “the world’s biggest and most important AI conference.”

Amid all the business interest, NeurIPS remains an academic gathering where success can be measured in terms of accepted papers. With an acceptance rate of <21% for 2018, NeurIPS is a showcase of the most innovative, cutting-edge research in the field of machine learning.

So who contributes the most papers? We asked Arshita Gupta from the Infinia ML data science team to comb through the annals of the event’s publishing history. After all, evaluating the world’s top data scientists should be a matter of, well, data.

Let’s start with the last five conferences (2014–2018). This is the period in which machine learning has had the biggest impact on the world and loomed the largest in the public consciousness, as a Google Trends search illustrates. It’s also a time of “skyrocketing attendance,” to quote a 2018 NeurIPS press release.

NeurIPS/NIPS Papers, 2014–2018

1. Lawrence Carin (28)
2. Michael I. Jordan (24)
2. Pradeep K. Ravikumar (24)
4. Josh Tenenbaum (22)
4. Yoshua Bengio (22)

The top spot here belongs to Infinia ML’s Chief Scientist: Larry Carin of Duke University. Close behind is Michael I. Jordan, who has been called “the Michael Jordan of machine learning” (seriously).

Rounding out the top five are Pradeep K. Ravikumar of Carnegie Mellon, Joshua Tenenbaum of MIT, and Yoshua Bengio, whom Wired called “one of the leading figures behind the rise of deep learning.” That’s pretty good company!

Now, let’s zoom out for the all-time standings:

NeurIPS/NIPS Papers, 1987–2018 (all-time)

1. Michael I. Jordan (109)
2. Yoshua Bengio (65)
3. Bernhard Schölkopf (64)
4. Geoffrey E. Hinton (59)
5. Zoubin Ghahramani (52)
6. Terrence J. Sejnowski (49)
7. Peter Dayan (48)
8. Lawrence Carin (44)
8. Pradeep K. Ravikumar (44)
10. Tong Zhang (42)

Carin, Jordan, Ravikumar, and Bengio are all still on the list, albeit in a different order. Other names are no surprise: Wired dubbed Geoff Hinton, who ranks number four on this list, as one of deep learning’s “founding fathers.” Zoubin Ghahramani is Uber’s Chief Scientist. Tong Zhang was previously the Executive Director of Tencent’s AI Lab.

It’s fun to look back at the past — but of course, NeurIPS is all about creating the future. There are surely more innovative research papers — and innovative researchers — yet to be celebrated. Then again, 109 papers is a tough number to beat. Better get writing!

Machine Learning in Practice

Practical insights for executives, managers, and project managers eager to deploy machine learning inside their company.

James Kotecki

Written by

Director of Marketing & Communications for Infinia ML, a machine learning company. Speaker from North Carolina to South Korea.

Machine Learning in Practice

Practical insights for executives, managers, and project managers eager to deploy machine learning inside their company.

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