One of the best ways to keep yourself informed about Machine Learning is to follow people who have paved the way for innovation in the field. That’s why we compiled a list of the 11 most influential people to keep on your radar.

  1. Vladimir Vapnik



Vladimir Naumovich Vapnik is one of the main developers of the Vapnik–Chervonenkis theory of statistical learning, and the co-inventor of the support-vector machine method, and support-vector clustering algorithm.


At the end of 1990, Vladimir Vapnik moved to the USA and joined the Adaptive Systems Research Department at AT&T Bell Labs in Holmdel, New Jersey. While at AT&T, Vapnik and his colleagues did work on the support-vector machine. They demonstrated its performance on a number of problems of interest to the machine learning community, including handwriting recognition. The group later became the Image Processing Research Department of AT&T Laboratories when AT&T spun off Lucent Technologies in 1996. In 2000, Vapnik and neural networks expert, Hava Siegelmann developed Support-Vector Clustering, which enabled the algorithm to categorize inputs without labels - becoming one of the most ubiquitous data clustering applications in use. Vapnik left AT&T in 2002 and joined NEC Laboratories in Princeton, New Jersey, where he worked in the Machine Learning group. He also holds a Professor of Computer Science and Statistics position at Royal Holloway, the University of London since 1995, as well as a position as Professor of Computer Science at Columbia University, New York City since 2003.[5] As of February 1, 2021, he has an h-index of 86 and, overall, his publications have been cited 226597 times.[6] His book on "The Nature of Statistical Learning Theory" alone has been cited 91650 times.


On November 25, 2014, Vapnik joined Facebook AI Research,[7] where he is working alongside his longtime collaborators Jason Weston, Léon Bottou, Ronan Collobert, and Yann LeCun.[8] In 2016, he also joined Vencore Labs.


Wikipedia



  1. Andrew Ng 



Andrew Yan-Tak Ng is a British-born American computer scientist and technology entrepreneur focusing on machine learning and AI. Ng was a co-founder and head of Google Brain and was the former Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people.


Ng is an adjunct professor at Stanford University (formerly associate professor and Director of its Stanford AI Lab or SAIL). Also a pioneer in online education, Ng co-founded Coursera and deeplearning.ai. He has successfully spearheaded many efforts to "democratize deep learning" teaching over 2.5 million students through his online courses. He is one of the world's most famous and influential computer scientists being named one of Time magazine's 100 Most Influential People in 2012, and Fast Company's Most Creative People in 2014. Since 2018 he launched and currently heads AI Fund, initially a $175-million investment fund for backing artificial intelligence startups. He has founded Landing AI, which provides AI-powered SaaS products and Transformation Program to empower enterprises into cutting-edge AI companies.


Twitter



  1. Santiago L Valdarrama



Santiago is a software and machine learning engineer who specializes in building enterprise software applications and spearheads for his company’s Computer Vision product team. He has provided engineering leadership on high-profile projects for IBM, Dell, Cisco, and NextEra Energy among others.


After earning his B.S. degree in Information Technology from the University of Camagüey in Cuba, and spending more than 15 years in the industry, he received his Master of Science in Machine Learning from Georgia Institute of Technology.


Santiago spends most of his time thinking and writing on his personal blog about algorithms, Artificial Intelligence, and Software Engineering in general.


Twitter




  1. Cassie Kozyrkov



Cassie Kozyrkov is Google Cloud’s chief decision scientist. Cassie is passionate about helping everyone make better decisions by harnessing the beauty and power of data. She speaks at conferences and meets with leadership teams to empower decision-makers to transform their industries through AI, machine learning, and analytics. 

At Google, Cassie has advised more than a hundred teams on statistics and machine learning, working most closely with research and machine intelligence, Google Maps, and ads and commerce. She has also personally trained more than 15,000 Googlers (executives, engineers, scientists, and even non-technical staff members) in machine learning, statistics, and data-driven decision-making. 

Previously, Cassie spent a decade working as a data scientist and consultant. She’s a leading expert in decision science, with undergraduate studies in statistics and economics at the University of Chicago and graduate studies in statistics, neuroscience, and psychology at Duke University and NCSU. When she’s not working, you’re most likely to find Cassie at the theatre, in an art museum, exploring the world, playing board games, or curled up with a good novel.


LinkedIn



  1. Andrej Karpathy



Andrej Karpathy is the director of artificial intelligence and Autopilot Vision at Tesla. He specializes in deep learning and computer vision.


Andrej Karpathy was born in Slovakia and moved with his family to Toronto when he was 15. He completed his Computer Science and Physics bachelor's degree at the University of Toronto in 2009 and completed his master's degree at the University of British Columbia in 2011, where he worked on physically simulated figures. He graduated with Ph.D. from Stanford University in 2015 under the supervision of Fei-Fei Li, focusing on the intersection of natural language processing and computer vision, and deep learning models suited for this task. He joined the artificial intelligence group OpenAI as a research scientist in September 2016 and became Tesla's director of artificial intelligence in June 2017.


Karpathy was named one of MIT Technology Review's Innovators Under 35 for the year 2020.


Twitter


  1. Gregory Piatetsky-Shapiro



Gregory I. Piatetsky-Shapiro is a data scientist and the co-founder of the KDD conferences, and co-founder and past chair of the Association for Computing Machinery SIGKDD group for Knowledge Discovery, Data Mining, and Data Science. He is the founder and president of KDnuggets, a discussion and learning website for Business Analytics, Data Mining, and Data Science.


In 1993, Piatetsky started Knowledge Discovery Nuggets (KDnuggets) as a newsletter to connect researchers who attended the KDD-93 workshop. With the emergence of the Internet and Mosaic, he and Chris Matheus eventually created the website: Knowledge Discovery Mine, hosted at GTE Labs. The newsletter served as an unofficial publication of KDD workshops. When Piatetsky left GTE Labs, he created the KDnuggets website, with the mission of covering the field with short, concise "nuggets". The resource started as a directory for the subjects of data mining and data science, including Software, jobs, academic positions, CFP (calls for papers), companies, courses, datasets, education, meetings, publications, and webcasts.


KDnuggets' main focus is to cover the fields of Business Analytics, Data Mining, and Data Science, including interviews with key leaders. It offers a free data mining course for advanced undergraduates or first-year graduate students.


LinkedIn


  1. Yann LeCun



Yann André LeCun is a French computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics, and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University, and Vice President, Chief AI Scientist at Facebook.


He is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN) and is a founding father of convolutional nets. He is also one of the main creators of the DjVu image compression technology (together with Léon Bottou and Patrick Haffner). He co-developed the Lush programming language with Léon Bottou.


LeCun received the 2018 Turing Award, together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. The three are sometimes referred to as the "Godfathers of AI" and "Godfathers of Deep Learning"


Twitter


  1. Fei-Fei Li



Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018. And during her sabbatical from Stanford from January 2017 to September 2018, she was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors and her Ph.D. degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She joined Stanford in 2009 as an assistant professor. Prior to that, she was on faculty at Princeton University (2007-2009) and the University of Illinois Urbana-Champaign (2005-2006).

Dr. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision, and AI+healthcare especially ambient intelligent systems for healthcare delivery. In the past, she has also worked on cognitive and computational neuroscience. Dr. Li has published more than 200 scientific articles in top-tier journals and conferences


Twitter



  1. Fabio Moioli



Fabio Moioli is a passionate advocate for Artificial Intelligences and Human Intelligences, with 270.000+ followers on Linkedin & Twitter, where he shares opportunities and challenges raised by Artificial Intelligence and exponential technologies, including societal and ethical perspectives.


He currently holds a position as Consulting and Services Head at Microsoft, with 20+ years general management experience in bringing innovation to diversified industries and markets.


Previously Vice President and Head of BU Telecom & Media at Capgemini, Associate at McKinsey, Account and Delivery Manager at Ericsson.


His major areas of expertise include Artificial Intelligence, Digital Platforms, Transformational programs, Lean Operations, Product & Services Innovation (including Blockchain).


Faculty at Singularity University, Harvard BR, and Extended Faculty at MIP Politecnico di Milano and Luiss.


Twitter



  1. Oriol Vinyals


Oriol Vinyals is a Research Scientist at Google DeepMind, working in Deep Learning. Prior to joining DeepMind, Oriol was part of the Google Brain team. He holds a Ph.D. in EECS from the University of California, Berkeley, and is a recipient of the 2016 MIT TR35 innovator award. His research has been featured multiple times at the New York Times, BBC, etc., and his articles have been cited over 17000 times. His academic involvement includes program chair for the International Conference on Learning Representations (ICLR) of 2017, and 2018. He has also been an area chair for many editions of the NIPS and ICML conferences. At DeepMind he continues working on his areas of interest, which include artificial intelligence, with particular emphasis on machine learning, deep learning, and reinforcement learning.


When he was 15 years old, Oriol Vinyals became obsessed with StarCraft, a video game in which three factions vie for control of the map—like chess if it were played not only with black and white pieces but also with red ones. Vinyals soon became the top-ranked player in Spain. “I almost knew the game would return later in my life,” he says. “I was fascinated by the artificial-intelligence problems it presents.”


It was more than a decade before Vinyals’s premonition came to pass. While he was studying at UC Berkeley, he helped to create an AI bot that was able to play StarCraft unassisted. The bot, forebodingly dubbed Overmind, represented a triumph in machine learning.


Twitter


  1. Pratham Prasoon



Pratham is a 16-year high school student who is interested in the fields of machine learning and finance. His goal is to help as many people as he can in a positive way by sharing his thoughts with more than 74K followers. 


Pratham decided to learn ML back in 2018 and at 16-years old, he got his first job in this field. 


Twitter