LinkedIn Top Voices 2020: Data Science & AI

LinkedIn News is debuting our 6th annual Top Voices list, a collection of hundreds of experts driving today’s professional conversation. As COVID-19 continues to upend our lives, these members are using their voice to help us parse today’s changing world of work, navigate our industries and find balance through it all.

To compile the list, we used a combination of qualitative and quantitative signals — including engagement (including reactions, comments and shares across each member’s content); posting cadence; and follower growth. You can learn more about the methodology at the bottom of this article and can check out all of this year’s Top Voices around the world here. 

Below you’ll find this year’s standout voices in Data Science and Artificial Intelligence, just 10 of the hundreds of Top Voices highlighted around the world. No matter your profession, you will improve your prospects by deepening your understanding of these topics. Whether you’re a machine learning expert looking to find your next opportunity in the field or a novice business analyst trying to discern how you use machine learning to make better decisions, the 2020 #LinkedInTopVoices list in Data Science and AI will connect you to the people who will challenge your thinking and make you smarter.

Check out this year’s #LinkedInTopVoices in Data Science and AI — and follow them to stay plugged into the conversation.

What she talks about: A scientist-turned-entrepreneur, el Kaliouby co-founded MIT spin-off Affectiva. Its AI detects complex emotions, cognitive states, activities and objects people use. This year, el Kaliouby published her memoir, Girl Decoded: A Scientist's Quest to Reclaim Our Humanity by Bringing Emotional Intelligence to Technology. Her 41,000+ followers follow her for insights into AI innovation, data in machine learning and automotive tech updates, as well as reflections on empathetic leadership, women in tech and country of origin, Egypt. She frequently covers topics such as these trends from 53,000 ads tested and brings attention to the importance of diversity in tech.

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What he talks about: Coquillo offers practical tips on how to use data science as a business strategy. His 25,000+ followers tune in to pick up smart, specific advice on what to consider when using a data set (and where to find reliable, free ones) and lessons on how to identify an experienced data science team. Earlier this year, Coquillo joined Amazon, and he also offers smart commentary on Amazon-specific developments like the company’s current revenue model, or the recently announced Amazon One. His conversations with members on his posts are as interesting as the posts themselves.

Follow Greg Coquillo

What he talks about: Ng is among the most significant AI pioneers of our time. His posts on everything from current company projects, like a platform to help manufacturers build and deploy visual inspection systems, to an article about his father, who completed 146 online courses on the platform he helped found, Coursera, receive hundreds of comments from fans as well as other AI practitioners. Ng’s 325,000 followers look to him for broad thought leadership on the field’s future and specific developments like this new course on Generative Adversarial Networks (GANs).

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What she talks about: Kozyrkov notes that the “days of the ‘I'm-not-a-data-person’ are fading fast” and she wants to make decision intelligence available to more people. She draws from her focus on the intersection between information and decision-making to point her 245,000 followers to podcast episodes like this selection on the relationship between analytics and storytelling and short tutorial videos offering, for example, advice on the machine learning skills you should learn. This year, she has focused a good deal of her commentary on bias and its impact on technology.

Follow Cassie Kozyrkov

What she talks about: Huyen posts about how to put machine learning into practice, from landing jobs in the field to what skills to prioritize learning. Having worked at prominent tech companies including Netflix and NVIDIA, Huyen joined the AI startup Snorkel last December. A Stanford graduate, Huyen turned to LinkedIn to find reviewers for the course she’ll start teaching there in January, Machine Learning Systems Design. Before coming to the U.S., Chip helped launch Vietnam’s second most popular web browser, Coc Coc. She’s currently writing a book on how to interview for machine learning roles.

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What he talks about: Malan teaches Harvard’s most popular course, an introduction to computer science course called CS50. It’s so revered that Malan began offering it at Yale, too. His classes are also available online, and his 61,000 followers tune in to catch his charismatic lectures on everything from HTML and javascript to cybersecurity. As classes have moved from room to Zoom, he’s also been offering tips on how to perfect the set-up. Nearly 1,000 people attended a recent session he posted about on how to prepare your resume for technical interviews.

Follow David Malan

What she talks about: After studying computer science at the Vellore Institute of Technology, Srinivasan came to the United States to complete her computer science masters at Columbia University. At IBM, she helps train customers to deploy machine learning smartly. Her 76,000 followers turn to her for updates on important research and also thoughts from important industry figures. She also shares the occasional data scientist job posting.

Follow Aishwarya Srinivasan

What he talks about: As an MIT-trained data scientist who has worked at prestigious companies like DuPont, Microsoft and Facebook, Rohrer believes applied machine learning education should be available to everyone. He posts lectures from the End-to-End Machine Learning courses he teaches, neural networks diagrams and podcasts on which he is invited to speak. For all his posts on his collection of Python incantations and image classification, he also inspires his 80,000 followers with thoughts on tech’s ability to address the world’s challenges.

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What she talks about: Miller’s 800,000 followers look to her for artificial intelligence news and updates, and motivational posts that build community. As the U.S. Head of AI Business Development for Startups and Venture Capital at Amazon Web Services, Miller has transformed her feed into a hub for anyone interested in keeping up on demo days and job openings. This year she’s also shared personal experiences working remotely.

Follow Allie Miller

What he talks about: A polyglot with a Ph.D. in artificial intelligence, Burkov writes a weekly newsletter on AI that is read by more than 214,000 LinkedIn members. His newest book outlines the machine learning project lifecycle, from data collection to putting the model into production. He also shares jobs for which he’s hiring, reviews of relevant books, and the occasional engineering insider joke.

Follow Andriy Burkov

You’ve read about the Top Voices in Data Science and AI this year. Now, check out the #LinkedInTopVoices in Technology, Education, Design and more.

How we compiled the Top Voices is: To compile the list, we use a combination of quantitative and qualitative signals. This includes engagement (including reactions, comments and shares across each member’s content); posting cadence; and follower growth. But engagement is just a start. Our next filter is qualitative. LinkedIn News editors refine and curate the list by looking at an eligible member’s body of work: Are the contributions insightful, conversational and timely? Do they seek to give and get help vs. being self-promotional? Finally, does this list reflect the world we work and live in today? 

All sharing activity measured took place over a 12-month period, from October 1, 2019 through September 30, 2020. As with all LinkedIn Lists, we excluded current LinkedIn and Microsoft employees from consideration, as well as any members who are being or have been paid by LinkedIn to participate in brand campaigns or courses.