Machine Learning (ML) is emerging as one of the hottest fields today. It has penetrated into numerous aspects of our everyday life—be it Siri or Alexa, Facebook/Instagram friend suggestions, Gmail spam filters, traffic congestion predictions, customer support chatbots, and much more. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% from 2019 to 2025, reaching up to an estimated evaluation of USD 96.7 billion by the end of 2025.
Consequently, there has been a significant increase in the number of Machine Learning enthusiasts across the globe. While there are scores of ML-related resources available across platforms, it might get quite overwhelming for beginners. Given this scenario, the first step should be to religiously follow ML/AI leaders, in order to seek advice and get insights on current trends and technologies.
We have curated a list of 20 influencers in ML/AI, inclusive of industry experts, thought leaders, academic professionals, and the likes.
1. Adam Coates
Follow @adampaulcoates
A Deep Learning leader, Adam Coates is currently the Director of Apple’s Special Projects Group. He has also served as the Director at Baidu’s Silicon Valley AI Lab, where his team worked on various technologies such as Deep Learning, Natural Language Processing (NLP), and High-Performance Computing (HPC). The team also created an end-to-end Deep Learning speech system, Deep Speech, and a multi-speaker text-to-speech engine, Deep Voice.
Follow @alexjc
With an experience of over twenty years in the Artificial Intelligence (AI) space, Alex Champandard is the co-founder of Creative.ai, a startup that aims at building AI/ML-powered tools for designers and artists. He has also co-organized Nucl.ai, one of the largest conferences dedicated to the use of AI technology in the creatives industry. Earlier in his career, he worked in computer entertainment and simulation industries for many years. He is also the author of AI Game Development: Synthetic Creatures with Learning and Reactive Behaviors, discussing various techniques and theories involved in the AI-based game development.
Follow @amuellerml
Andreas Mueller is a Research Scientist at the Data Science Institute at Columbia University. He is also one of the core developers of scikit-learn—a Machine Learning library for Python. In addition, he has also co-authored Introduction to Machine Learning with Python, elaborating on practical approaches to Machine Learning using Python. Early on, he worked as an Assistant Research Scientist at the Center of Data Science at New York University and as a Machine Learning Scientist at Amazon. He is extremely passionate about open source and open science and is on a mission to make high-quality ML methods and applications that are easily applicable and available for everyone.
Follow @AndrewYNg
Andrew NG is one of the most sought-after leaders in the Machine Learning arena. He co-founded Coursera and launched a Deep Learning specialization course—deeplearning.ai. He is also the founder and CEO of Landing AI, an organization that helps businesses become entirely AI-driven. Additionally, he is an adjunct professor for Computer Science and leads an AI research group at Stanford University. Formerly, he founded and led Google’s Deep Learning project, Google Brain, which was later deployed in numerous products such as object detection, speech recognition, street view, and more.
Follow @DrDataScientist
With over thirty years of experience in working on multiple technological projects across all industries, Dr. Craig Brown is a technology expert and a thought leader. Primarily, his thought leadership is focused on leveraging Big Data, Machine Learning, and Data Science to drive and enhance an organization’s business, address business challenges, and lead innovation.
Follow @drfeifei
Dr. Fei-Fei Li is a Computer Science professor at Stanford University and the co-director of the Stanford University Human-Centered AI Institute. She is also the co-founder of a non-profit organization, AI4ALL, which aims at educating the next generation of AI enthusiasts. Prior to this, Dr. Fei-Fei Li served as the Chief Scientist of AI/ML and Vice President at Google Cloud, overseeing research, engineering, and development efforts for all AI/ML products of Google Cloud.
Follow @GaryMarcus
Gary Marcus is the CEO and founder of Robust.ai that offers a cognitive platform at an industrial level to enable smart, robust, and safe robots. He has recently co-authored Rebooting AI: Building Artificial Intelligence We Can Trust along with Ernest Davis. He is a cognitive scientist and a professor of Psychology and Neural Science at New York University. Prior to that, he served as a Director at the Uber AI Labs.
Follow @geoffreyhinton
Fondly known as the Godfather of Deep Learning, Geoffrey Hinton is a professor in the Department of Computer Science at the University of Toronto. He recently joined Google’s AI research team, Google Brain, as a researcher. His expertise lies in artificial neural networks. Along with Yoshua Bengio and Yan LeCun, he has been termed as one of the Godfathers of AI, and co-received the 2018 ACM A.M. Turing Award. Furthermore, he has authored Neural Network Architectures for Artificial Intelligence.
Follow @hmason
Hilary Mason has been in the Data Science field for over twenty years now. With her passion for data, she became the founder and CEO of Fast Forward Labs that aimed at helping organizations use Machine Learning and Data Science advancements for scaling up their businesses. Fast Forward Labs was later acquired by Cloudera, where she went on to become the GM of Machine Learning. She is currently serving as a Data Scientist in Residence at Accel Partners, advising on various data strategies and investing opportunities. She also co-founded hackNY that mentors the next generation of New York’s developers for the creative technology community. Earlier in her career, she served as a Chief Scientist at Bitly.
Follow @goodfellow_ian
Currently employed as the Director of Machine Learning in the Special Projects Group at Apple Inc., Ian Goodfellow has majorly contributed to the Deep Learning space. He is the inventor of generative adversarial networks, an ML technique that is being used by Facebook. Earlier in his career, he worked with Google, playing a key role in Street Smart (Google Maps) and Google Brain (AI Research) teams. Besides that, he has also co-authored a comprehensive book, Deep Learning, alongside Yoshua Beng and Aaron Courville.
Follow @TeachTheMachine
With the aim of ‘making developers awesome at Machine Learning’, Jason Brownlee founded the Machine Learning Mastery—a community offering various collaterals to help developers enhance their skills of applied Machine Learning.
Follow @jhamrick
Currently employed as a research scientist at DeepMind, Jess Hamrick is a cognitive science enthusiast. Her key research area lies in human cognition by combining ML models with cognitive science. She is also one of the key maintainers of Jupyter/nbgrader—an open-source tool used to creating and grading assignments in the Jupyter notebook.
Follow @KirkDBorne
Dr. Kirk Borne, a data scientist and astrophysicist, is one of the leading influencers in the Big Data/Data Science/AI space. He is currently employed as the Principal Data Scientist and Executive Advisor at Booz Allen Hamilton. He has also been a professor of astrophysics and computational science at George Mason University for over twelve years. His work has majorly contributed to various projects including NASA’s Hubble Space Telescope.
Follow @MFordFuture
Martin Ford is a well-acclaimed futurist and a keynote speaker, elaborating on topics such as AI and robotics, and their possible impacts on the market, economy, and society. He is also an author of three books, including the New York Times bestseller, Rise of the Robots: Technology and the Threat of a Jobless Future. He is also the Consulting Artificial Intelligence Expert for the Rise of the Robots Index project for Societe Generale Corporate and Investment Banking.
Follow @MikeTamir
Mike Tamir is currently the Chief Machine Learning Scientist and head of ML/AI at Susquehanna International Group, LLP (SIG). He is also a Data Science faculty member at UC Berkeley. Prior to this, he served as the Head of Data Science at Uber Advanced Technologies Group, and as the Chief Science Officer at Galvanize Inc. Earlier in his career, he was a faculty member at the University of Pittsburgh and Columbia University.
Follow @OriolVinyalsML
Oriol Vinyals is employed as a Principal Research Scientist at Google DeepMind, leading the Deep Learning team there. He has also led the AlphaStar team that developed the first AI that defeats the top professional players of the game, StarCraft. In the past, he was a Senior Research Scientist in the Google Brain team.
Follow @peteskomoroch
Presently serving as a senior executive and investor for numerous ML-driven startups and venture capital funds, Peter Skomoroch has over twenty years of experience in the Data Science industry. Over the years, he has worked as a Senior Research Engineer at the AOL Search Analytics team, Director of Analytics at Juice Analytics, Principal Data Scientist at LinkedIn, CEO and Co-founder of SkipFlag, and Head of AI Automation & Data Products at Workday, among various other roles. At LinkedIn, he played a key role in ideating, creating, and deploying LinkedIn Skills and Endorsements.
Follow @soumithchintala
Soumith Chintala has co-created and led PyTorch, an open-source Machine Learning library developed by the Facebook AI Research lab for Computer Vision and Natural Language Processing applications. Having worked in the past on projects such as Google Street View House Numbers, pedestrian detection, sentiment analysis, and at New York University, he is also an extensive researcher in the ML space.
Follow @ylecun
Yann LeCun is the VP and Chief AI Scientist at Facebook, leading the scientific and technical AI research and development for the organization. In addition, he is a professor at New York University. Early on in his career, he headed the Image Processing Research Department at AT&T Labs Research. Being one of the Godfathers of AI, he has made a huge contribution in the field of Computer Vision and Optical Character Recognition. He is also one of the 2018 ACM A.M. Turing Award laureates for his contribution to the AI domain.
Yoshua Bengio is one of the pioneers in the ML space, owing to his work on artificial neural networks and Deep Learning. He has been a professor in the Department of Computer Science and Operations Research at the Université de Montréal for over twenty-five years. He also heads the Montreal Institute for Learning Algorithms. Yoshua Bengio, Geoffrey Hinton, and Yann LeCun are considered as the Godfathers of AI and have been awarded the 2018 ACM A.M. Turing Award for achieving major breakthroughs in deep neural networks.
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