Machine learning is an incredibly broad and diverse field, with a non-stop increase on research, along a multitude of applications. Thus writing a list enlisting the best machine learning researchers on the field proves challenging for a number of reasons.
Please mind that this list encompasses researchers who are currently working on the field.
Also, please mind that this list is by no means ranked. Everyone listed below has done extraordinary work to advance humanity’s state of AI further.
Lastly, I will also add a small section below with Honorable Mentions — feel free to add in the comments if you believe that someone should be added to the list, or added in the Honorable Mentions section.
a) Tom Mitchell
Tom M. Mitchell is a E. Fredkin University Professor at Carnegie Mellon University (CMU). He is a former Chair of the Machine Learning Departmentat CMU. Mitchell is known for his contributions to the advancement of machine learning, artificial intelligence, and cognitive neuroscience and is the author of the famous textbook Machine Learning. He is a member of the United States National Academy of Engineering since 2010. He is also a Fellow of the American Association for the Advancement of Science and a Fellow the Association for the Advancement of Artificial Intelligence. In October 2018, Mitchell was appointed as the Interim Dean of the School of Computer Science at Carnegie Mellon University.
b) Geoffrey Hinton
Geoffrey Hinton, also known as The Godfather of AI. Geoffrey Hinton is one of the first researchers in the field of neural networks. While he was a Professor at Carnegie Mellon University, he was one of the first researchers who demonstrated the generalized back-propagation algorithm. This was in 1985. But due to the lack of computational power at that time, not much could be achieved using the novel algorithm. It was later in 2012 that he used he same algorithm to train deep neural networks and created a major milestone in image recognition. Under the guidance of Andrew Ng, Hinton released his neural networks course on Coursera which has been a huge success.
c) Manuela Veloso
Manuela Veloso is the Head of AI Research at J. P. Morgan, former Head of the Machine Learning Department at Carnegie Mellon University & Herbert A. Simon University Professor in the School of Computer Science at Carnegie Mellon University. Veloso served as president of Association for the Advancement of Artificial Intelligence (AAAI) until 2014, and the co-founder and a Past President of the RoboCup Federation. She is a fellow of AAAI, Institute of Electrical and Electronics Engineers (IEEE), American Association for the Advancement of Science (AAAS), and Association for Computing Machinery (ACM). Veloso is an international expert in artificial intelligence and robotics.
Michael I. Jordan is currently a Professor at UC Berkeley, and a former Professor at MIT. His teaching, much like his research interests, is split between Statistics and EECS. He helped to popularize the use of Bayesian networks in machine learning applications, and is often credited as one of the principle thinkers who brought the overlap between statistics and machine learning to popular attention. He is a fellow of AAAI, ACM, ASA, CSS, IEEE, IMS, ISBA and SIAM. His graduate and postdoc students have also gone on to profoundly influence the world of machine learning, several of whom appear on this list- Andrew Ng, David Blei and Zoubin Ghahramani.
e) Fei-Fei Li
Fei-Fei Li is a Professor of Computer Science at Stanford University. She is currently the Co-Director of Stanford University’s Human-Centered AI Institute and the Stanford Vision and Learning Lab. She served as the director of the Stanford Artificial Intelligence Lab (SAIL)from 2013 to 2018. In 2017, she co-founded AI4ALL, a nonprofit organization working to increase diversity and inclusion in the field of artificial intelligence. Her research expertise includes artificial intelligence (AI), machine learning, deep learning, computer vision and cognitive neuroscience. Li is one of the most prolific researchers in the field of AI. She was the leading scientist and principal investigator of ImageNet, a critical group of machine learning datasets and computer vision project that resulted in the recent deep learning revolution.
f) Andrew Ng
Andrew Ng is a Chinese English computer scientist, executive, investor, and entrepreneur. Ng co-founded and led Google Brain and was a former VP & Chief Scientist at Baidu, building the company’s Artificial Intelligence Group into several thousand people. He is an Adjunct Professor (formerly Associate Professor and Director of the AI Lab) at Stanford University. Ng is also an early pioneer in online learning — which led to the co-founding of Coursera and deeplearning.ai. He launched and heads AI Fund, a $175 million investment fund to back artificial intelligence startups.
g) Yann LeCun
Yann LeCun made significant contributions to the understanding and development of convolutional neural networks, particularly in the field of image recognition. He spent much of the late 80’s and early 90’s working with AT&T, first as a researcher and eventually as the Head of their Image Processing Research Department, where was one of the main creators of image compression technology DjVu. He joined NYU as a Professor of Computer Science Neural Science in 2003, and became the head of Facebook’s Artificial Intelligence laboratory on 2013.
h) Ian Goodfellow
Ian J. Goodfellow is a researcher working in machine learning, currently employed as a Research Scientist at Google Brain. He has made several contributions to the field of deep learning. Goodfellow is best known for inventing generative adversarial networks, an approach to machine learning frequently used at Facebook. He is also the lead author of the textbook Deep Learning. At Google, he developed a system enabling Google Maps to automatically transcribe addresses from photos taken by Street View cars and demonstrated security vulnerabilities of machine learning systems.
i) Roni Rosenfeld
Roni Rosenfeld is head of the Machine Learning Department and professor of machine learning, language technologies, computer science and computational biology, in the School of Computer Science at Carnegie Mellon University.
Rosenfeld has been teaching machine learning and statistical language modeling since 1997. He has taught thousands of undergraduate and graduate students, has been a mentor to four post-doctoral students and an advisor to about a dozen Ph.D. students and a score of Masters and undergraduate students. He is a world renown expert in machine learning, epidemiological forecasting and spoken dialogue technologies
Daphne Koller is an Israeli-American Professor in the Department of Computer Science at Stanford University and a MacArthur Fellowship recipient. She is one of the founders of Coursera, an online education platform. Her general research area is artificial intelligence and its applications in the biomedical sciences. Koller was featured in a 2004 article by MIT Technology Review titled “10 Emerging Technologies That Will Change Your World”  concerning the topic of Bayesian machine learning.
Yoshua Bengio is a world-renowned Canadian computer scientist, most noted for his work on artificial neural networks and deep learning. Along with Geoffrey Hinton and Yann LeCun, Bengio is considered by Cade Metz one of the three people most responsible for the advancement of deep learning during the 1990s and 2000s. Whereas the other two went to work for Google and Facebook respectively, Bengio has stayed in academia. Among the computer scientists with an h-index of at least 100, Bengio is the one with the most recent citations per day, according to MILA. In October 2016, Bengio co-founded Element AI, a Montreal-based business incubator that seeks to transform artificial intelligence (AI) research into real-world business applications. In May 2017, Bengio announced that he was joining Montreal-based legal tech startup Botler AI, as as a strategy adviser.
l) Ilya Sutskever
Ilya Sutskever is a computer scientist working in machine learning and currently serving as the Chief scientist of OpenAI. He has made several major contributions to the field of deep learning. Sutskever is the co-inventor of famous AlexNet, a convolutional neural network, he also invented Sequence to Sequence Learning , together with Oriol Vinyals and Quoc Le. Sutskever is also co-inventor of AlphaGo, and TensorFlow.
Andrej Karpathy is director of artificial intelligence and Autopilot Vision at Tesla. He specializes in deep learning and image recognition and understanding. Karpathy previously worked as a research scientist at OpenAI where he delved into deep learning in computer vision, generative modeling and reinforcement learning. On his spare time, Karpathy works on maintaining deep learning libraries (i.e. ConvNetJS, RecurrentJS, REINFORCEjs, t-sneJS), along a extended library containing machine learning research papers powered by Arxiv with over ~60,000 papers .
Francois Chollet is machine learning and AI software engineer at Google, he is known for being the author of Keras , a leading deep learning framework for Python, with over 250,000 users and over 700 open-source contributors. Chollet has authored “Deep learning with Python” (Manning Publications), with over 20,000 copies sold as of mid-2018. A very interesting read of his is The Implausibility of Intelligence Explosion.
o) Ruslan Salakhutdinov
Ruslan “Russ” Salakhutdinov is a Canadian researcher working in the field of artificial intelligence. He specializes in deep learning, probabilistic graphical models, and large-scale optimization. Salakhutdinov is currently the director of AI Research at Apple, along a tenured professor at Carnegie Mellon University, he is one of the most influential researchers on deep learning.
p) Lex Fridman
Lex Fridman is a research scientist at MIT, working on human-centered artificial intelligence. In particular, Fridman is interested in developing deep learning approaches for perception, planning, and human-robot interaction in the context of real-world shared autonomy systems. He is one of the most influential researchers in AI.
q) Jürgen Schmidhuber
Jürgen Schmidhuber is a computer scientist who works in the field of artificial intelligence. He is a co-director of the Dalle Molle Institute for Artificial Intelligence Research in Manno, in the district of Lugano, in Ticino in southern Switzerland. Since age 15 or so, the main goal of professor Jürgen Schmidhuber has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. His lab’s Deep Learning Neural Networks(since 1991) such as Long Short-Term Memory (LSTM) have transformed machine learning and AI .
Sebastian Thrun is an innovator, entrepreneur educator, and computer scientist from Germany. He is CEO of the Kitty Hawk Corporation, chairman and co-founder of Udacity. Before that, he was a Google VP and Fellow, a Professor of Computer Science at Stanford University, and before that at Carnegie Mellon University. Thrun is also known for his work on probabilistic algorithms for robotics with applications including robotic mapping. In recognition of his contributions, and at age 39, he was elected into the National Academy of Engineering and also into the Academy of Sciences Leopoldina in 2007. In 2011, he received the Max-Planck-Research Award. Thrun’s doctoral advisor was the world-renown AI expert Tom M. Mitchell.
s) Zoubin Ghahramani
Zoubin Ghahramani FRS is a British-Iranian researcher and Professor of Information Engineering at the University of Cambridge. He holds joint appointments at University College London and the Alan Turing Institute. and has been a Fellow of St John’s College, Cambridge since 2009. Ghahramani co-founded Geometric Intelligence company in 2014, with Gary Marcus, Doug Bemis, and Ken Stanley. After Uber’s acquisition of the startup he transferred to Uber’s A.I. Labs in 2016. Just after four months he became Chief Scientist, replacing Gary Marcus.
t) Demis Hassabis
Demis Hassabis CBE FRS FREng FRSA is a British artificial intelligence researcher, neuroscientist, video game designer, entrepreneur, and world-class games player. In 2010 Hassabis co-founded DeepMind  a London-based machine learning AI startup, with Shane Legg and Mustafa Suleyman. DeepMind’s mission is to “solve intelligence” and then use intelligence “to solve everything else”. More concretely, DeepMind aims to meld insights from neuroscience and machine learning with new developments in computing hardware to unlock increasingly powerful general-purpose learning algorithms that will work towards the creation of an artificial general intelligence (AGI).
u) Jeff Dean
Jeff Dean joined Google on 1999. He is currently the lead of Google.ai, Google’s AI division. His research includes large-scale distributed systems, performance monitoring, compression techniques, information retrieval, application of machine learning to search and other related problems, machine intelligence and machine perception.
Dean started and led Google Brain, a team that studies large-scale artificial neural networks, and he has headed Artificial Intelligence efforts since they were split from Google Search.
v) David Silver
David Silver leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo. He graduated from Cambridge University in 1997 with the Addison-Wesley award, and befriended Demis Hassabis whilst there. Silver co-introduced the algorithms used in the first master-level 9x9 Go programs. His version of program MoGo (co-authored with Sylvain Gelly) was one of the strongest Go programs as of 2009.
Jeremy Howard is an Australian data scientist and entrepreneur. He is a founding researcher at fast.ai, a research institute dedicated to make Deep Learning more accessible. Previously, he was the CEO and Founder at Enlitic, an advanced machine learning company in San Francisco, California.
x) Richard S. Sutton
Richard S. Sutton is a Canadian computer scientist. Currently he is professor of Computer Science and iCORE chair at the University of Alberta. Sutton is considered  one of the founding fathers (or pioneering parents) of modern computational reinforcement learning, having several significant contributions to the field, including temporal difference learning, policy gradient methods, the Dyna architecture.
y) Peter Norvig
Peter Norvig is an American computer scientist. He is a director of research at Google Inc., and used to be its director of search quality. Norvig is one of the creators of JScheme. In 2006 he was inducted as a fellow of the Association for Computing Machinery. Norvig is listed under “Academic Faculty & Advisors” for the Singularity University. In 2011, Norvig worked with Sebastian Thrun to develop a popular online course in Artificial Intelligence that had more than 160,000 students enrolled. He also teaches an online course via the Udacity platform.
z) Eric Xing
Eric Xing is a professor at Carnegie Mellon University and researcher in machine learning, computational biology, and statistical methodology . He has won several awards, including recipient of the NSF Career Award and an Alfred P. Sloan Research Fellowship. Xing with his collaborators developed the Petuum  framework for distributed machine learning with massive data, big models, and a wide spectrum of algorithm. On 2016 he was elected as a fellow of AAAI .
This article originally appeared in Towards Data Science