Let’s talk experts, shall we?
You could read books and research online to understand what’s trending in machine learning. We know what you’re thinking, who has the time? Everyone’s been there.
There is so much content in the machine learning space, it is impossible to get to the bottom of everything. The easier way is to follow those making these waves. Influencers in every space not only inform enthusiasts but also inspire them to reach their fullest potential.
The best way to stay on track with all developments in the machine learning area is to follow the trailblazers who spend most of their time living and breathing algorithms!
Who are these machine learning maestros and where do I find them?
Machine learning experts are majorly experienced professionals who have devoted years in research and implementation. These people have exhaustive knowledge and are a part of the groundbreaking applications of machine learning worldwide.
Luckily, we decided to put together a list of these aficionados for you. All you need to do now is look them up and follow their accomplishments online:
1. Geoffrey Hinton
Geoffrey Hinton is perhaps as interesting as he is inspiring. After completing his PhD in artificial intelligence in 1978 from Edinburgh, he spent a colossal number of years in academia researching and educating people about the advances and developments in artificial intelligence. One of Hinton’s most recent achievements is winning the Turing award in 2019 but believe us, that is only the tip of the iceberg.
Hinton co-wrote a highly discussed and cited research paper in 1986 on back-propagation algorithms. Hinton popularized a number of theories and findings on neural networks and rightfully called the ‘Godfather of Deep Learning.’
One of the most inspiring incidents about Hinton is when he joined Google as an Intern at the age of 64. He is currently an Engineering Fellow at Google and an Emeritus Distinguished Professor at the University of Toronto.
2. Andrew Ng
Andrew Ng is a known legend in the field. He’s the Founder of Coursera and the Chief Data Scientist at Baidu. Andrew Ng also founded Google Brain deep learning project. One of the brightest minds in artificial intelligence, Andrew Ng launched “AI for everyone” in 2019 to make artificial intelligence accessible and comprehensive for everybody irrespective of their backgrounds.
Some of his intriguing works include developing an autonomous helicopter at Stanford which is yet one of the best autonomous helicopters the world has seen. Another spectacular application was the ‘Google Cat Project’ where he deployed powerful neural networks to identify cats from unlabelled data from YouTube videos.
3. Michael Irwin Jordan
Michael Jordan is a Professor in the Department of Electrical Engineering & Computer Science and the Department of Statistics at UC Berkeley. He has been conferred the ‘Pehong Chen’ distinction is professorship. His areas of expertise include probabilistic graphical models, spectral methods, kernel machines and natural language processing. Jordan has also been distinguished by the Institute of Mathematical Statistics as a Neyman Lecturer and a Medallion Lecturer.
Before his career at the University of California, Berkeley, he was a professor at MIT.
Michael Jordan helped popularized Bayesian networks in machine learning and continues to garner world praise for his skills as a professor. Michael’s students also include the AI maestro, Andrew Ng.
4. Vladimir Vapnik
Vladimir Vapnik is another pillar in the world of machine learning experts. Vapnik’s early works include developing support vector machine with his colleagues in 1963. He later joined AT&T where he worked on handwriting and image recognition using machine learning.
Vapnik is also credited with working on the Vapnik–Chervonenkis theory which is a form of computational learning theory from the point of view of statistics.
Valdimir was also involved with Facebook AI Research and has written a highly regarded book called “Statistical Learning Theory.’’ His work in computer science and statistics has spanned over 30 years. When it comes to machine learning, Vladimir Vapnik is a force to reckon with.
5. Yann LeCun
One of the colleagues of Vladimir Vapnik, Yann LeCun is the Director of Facebook AI Research and a Silver Professor of Computer Science and Neural Science at New York University. LeCun is credited with cracking image recognition using neural networks. Yann LeCun focuses on real world applications of machine learning, an approach which led to him and his friends (yes, including Vladimir Vapnik) to use convolutional networks to identify handwritten characters while at AT&T.
Yann LeCun was also a research associate under Geoffrey Hinton and has been the brains behind the image compression and processing technology Djvu. LeCun’s most recent achievement was winning the Turing Prize in March 2019 along with Geoffrey Hinton. Yann LeCun has focused his work on computer vision, mobile robotics and neural science.
6. Dr. Alexander Johannes Smola
Alex Smola is a distinguished Scientist/ Vice President at Amazon Web Services. His early accomplishments include his extensive body of work on Support Vector Machines and kernel algorithms.
Smola has worked in Yahoo Research and Google Research before progressing as a Professor at Carnegie Mellon University. His stand-out writing is reflected in some of his best books including ‘‘Predicting Structured Data’’ and ‘‘Learning with Kernels.’’ His most recent book, Dive into Deep Learning was released in 2019 as an open-source book with contributions from the entire community.
7. Fei-Fei Li
Fei-Fei Li is a distinguished researcher when it comes to machine learning, artificial intelligence, cognitive neuroscience, computational neuroscience and computer vision. She currently works as a Professor of computer science at Stanford University and Co-Director of the university’s Human-Centered AI Institute. Li also served as the Chief Scientist of machine learning and artificial intelligence at Google Cloud. Fei-Fei Li made solid breakthroughs in machine learning and deep learning by inventing ImageNet and the ImageNet challenge.
Fei-Fei Li believes that the development of artificial intelligence should be humanistic even though being technological. Her works have been published in the New York Times, MIT Technology Review, Wall Street Journal, Financial Times, Fortune Magazine and Wired Magazine. Fei-Fei Li remains one of the most formidable women in Tech.
8. Tom M. Mitchell
Tom Mitchell is a computer scientist and a Professor at Carnegie Mellon University. He is most famous for his lucid, informative and exceedingly helpful book on machine learning called “Machine Learning.” The book has garnered high praise for its comprehensive approach and no prior background assumption of the readers. It has become a must-have for all machine learning buffs.
Artificial intelligence, machine learning and cognitive neuroscience are areas of excellence for Tom Mitchell.
His contributions in the field got him to be selected to the United States National Academy of Engineering in 2010. Mitchell has stressed on the importance of making machine learning accessible for everyone with or without a programming background. Mitchell has been a long standing supporter of making machine learning conversational and popular.
9. Rajeev Rastogi
Rajeev Rastogi started his career at Bell Labs and moved to Yahoo! Labs as a Vice President. Currently, Rastogi is a Director of machine learning at Amazon.
He has authored over 200 research papers and has extensive experience in researching databases, distributed systems, data mining and machine learning. You can check out his body of work here. Rajeev Rastogi has a doctorate from the University of Texas.
10. Bernhard Schölkopf
Bernhard Schölkopf is a Director at the Max Planck Society, Germany. Leading a research organization, Schölkopf focuses on machine learning and inferences from empirical data. He also studies extracting causal and structural regularities from high-dimensional data.
Schölkopf has collaborated with people from diverse backgrounds like photographers and astronomers. He considers this as playing in everybody’s backyard. He is known for his work in kernel methods and support vector machines. He has a number of awards to his credit including the Royal Society Milner Award and holds membership to the LIGO scientific collaboration to detect gravitational waves.
11. Jürgen Schmidhuber
Another neural network pundit on our list, Jürgen Schmidhuber is a highly regarded computer scientist and Co-Director of Dalle Molle Institute for Artificial Intelligence Research, Switzerland. Schmidhuber is touted to be the Father of Modern AI and has an impressive track record of working in deep learning, machine learning and artificial intelligence. Schmidhuber has contributed to recurrent neural networks like Long Short term memory which are used abundantly by the tech empires of Google, Amazon, Facebook for speech recognition.
Jürgen Schmidhuber is the Founder of an AI start-up called Nnaisense and has made businesses easier for many corporate giants. He believes machines overturning human dominance is a very real scenario and has been explicit in his view of the same.
12. Richard Sutton
Richard Sutton is a Professor of computer science at the University of Alberta and a Distinguished Research Scientist at DeepMind in Edmonton. He is one of the founding fathers of modern computational reinforcement learning. His honorable works include temporal difference learning and policy gradient methods.
He gained rich industry experience while working for AT&T and GTE Labs while making his mark in academia at the University of Massachusetts. He also co-authored Reinforcement Learning: An Introduction and his research papers have been cited over 70,000 times!
13. Zoubin Ghahramani
Zoubin Ghahramani is a Professor of Information Engineering at the University of Cambridge. He is also a Chief Scientist at Uber who leads Uber AI Labs and a Deputy Director of the Leverhulme Centre for the Future of Intelligence.
He was a founding Cambridge Director of UK’s national institute for data science- Alan Turing Institute. His areas of focus include statistical machine learning, scalable inference, probabilistic programming and Bayesian non-parametrics. His most noted work was research on building the Automatic Statistician for which he was awarded the $750,000 Google Award. He earned his Ph.D. from the Department of Brain and Cognitive Sciences at MIT, supervised by Michael Jordan (who is also on our list.)
14. Jeff Hawkins
Jeff Hawkins was already famous for his invention of PalmPilot and Treo before he ventured into machine learning. He dove into artificial intelligence and neuroscience after earning his reputation as a Silicon Valley veteran. He believes that in order to best develop artificial intelligence, we need to explain human intelligence to be able to emulate the same in technology.
Hawkins established Numenta, a company focused on mirroring the working of a human brain. Collaborating with other neuro-scientists, Numenta develops and tests theories regarding the functioning of a human brain.
15. Christopher Bishop
Christopher Bishop is a Microsoft Technical Fellow and Director of the Microsoft Research Lab in Cambridge. He is also the Professor of computer science at the University of Edinburgh.
His areas of focus include cloud infrastructure, workplace productivity, security, computational biology, computer vision and healthcare. Bishop has authored two books: Neural Networks for Pattern Recognition in 1995 and Pattern Recognition and Machine Learning in 2006.
These exceptional machine learning wizards are making waves globally. As a machine learning buff, you need to add them to your list to keep track of their accomplishments and new developments in this space.
Start following these machine learning legends online and let us know what interests you about them in the comments section!
