Female AI influencers in the Data Science world in 2021

analytics-insightThis post was originally published by Monomita Chakraborty at Analytics Insight

Female AI influencers in the Data Science world in 2021

Data science has proven to be successful in addressing a wide range of real-world issues, and it is increasingly being used across industries to enable more intelligent and well-informed decision-making. There is a need for intelligent machines that can understand human actions and job habits as the use of computers for day-to-day business and personal operations expands. This pushes big data analytics and data science to the foreground.

Women have made enormous advances in AI research in recent years. In this article, Analytics Insight presents you the list of Greatest Female AI Influencers in the Data Science World in 2021.

Allie K Miller 

Allie Miller is Amazon’s (AWS) US Head of AI Business Development for Startups and Venture Capital, where she works to advance the world’s best AI businesses. Allie was previously the youngest woman to lead the creation of a large-scale artificial intelligence product at IBM, where she spearheaded large-scale product development across computer vision, conversation, data, and regulation.

Allie is shifting the AI game outside of work. Allie has given talks all over the world about AI and field diversity, addressed the European Commission, drafted foreign AI plans, and created eight guidebooks to help companies develop effective AI projects.

Fei Fei Li 

Fei-Fei Li is an Associate Professor in Stanford’s Computer Science Department and the Director of the Stanford Artificial Intelligence Lab and Stanford Vision Lab, where she collaborates with some of the world’s brightest students and colleagues to develop smart algorithms that allow computers and robots to see and think, and also perform cognitive and neuroimaging experiments to determine how brains see and think. Caltech awarded her a Ph.D. in her field.

Ujjyaini Mitra

Ujjyaini is currently employed by Zee5 as the Chief Data Officer. She has nearly 13 years of leadership experience in large companies developing Data as Culture. She has previously held executive roles with companies such as Airtel, Flipkart, and Mckinsey & Company.

Kim Hazelwood

Kim Hazelwood is a Senior Engineering Manager heading the AI Infrastructure Foundation and AI Infrastructure Research efforts at Facebook, which are responsible for developing and optimizing efficient hardware and software systems for the firm’s many applied machine learning-based products and services. Before joining Facebook, Kim worked as a tenured Associate Professor at the University of Virginia, a Google Software Engineer, and the Director of Yahoo Labs’ Systems Research.

She graduated from Harvard University with a PhD in Computer Science in 2004 and has won several awards, including the NSF CAREER Award, the Anita Borg Early Career Award, the MIT Technology Review Top 35 Innovators under 35 Award, and the ACM SIGPLAN 10-Year Test of Time Award. She is now a member of the CRA Board of Directors and has written more than 50 conference papers and one book.

Cassie Kozyrkov 

Cassie Kozyrkov is a Google data scientist and leader with a quest to democratize Decision Intelligence and safe, reliable AI.  She brings a rare blend of deep technical knowledge, world-class public speaking skills, analytics management experience, and the ability to drive organizational change. She has guided on over 100 projects and designed Google’s analytics program, educating over 20,000 Googlers in statistics, decision-making, and machine learning.

Dr. Geetha Manjunath 

Dr.Geetha Manjunath is the founder, CEO, and CTO of NIRAMAI, a deep tech company working on a new way to diagnose early-stage breast cancer. She has over 25 years of experience in IT research and has been the driving force behind a number of groundbreaking ventures in the fields of healthcare and transportation.

She was a Lab Director at Xerox India, where she was in charge of Data Analytics Research. She spent 17 years as a Principal Research Scientist at Hewlett Packard Laboratories, where she was part of the C-DAC team that developed India’s first commercial supercomputer.

Kate Crawford 

Kate Crawford is a researcher and professor who studies the effect of artificial intelligence on society. She is a leading scholar of the social effects of data systems, machine learning, and artificial intelligence, and is a Distinguished Research Professor at NYU and a Principal Researcher at Microsoft Research. She has written for The New York Times, Harper’s Magazine, and The Wall Street Journal, and has been published in academic journals such as Nature, New Media & Society, and Information, Communication & Society.

Jennifer Tour Chayes

Jennifer Chayes is the Dean of the School of Information and Associate Provost of the Division of Computing, Data Science, and Society. She is Professor EECS, Mathematics, Statistics, and School of Information Professor. She spent over 20 years at Microsoft, before joining Berkeley, where she was a Technical Fellow as well as the founder and managing director of three interdisciplinary labs: Microsoft Research New England, New York City, and Montreal.

Jennifer has achieved several awards for her leadership and research achievements, such as the Anita Borg Institute Women of Vision Leadership Award, the John von Neumann Award of the Society for Industrial and Applied Mathematics, and an honorary doctorate from Leiden University. She is a part of the National Academy of Sciences and the American Academy of Arts and Sciences.

Phase transitions in computer science, as well as structural and dynamical properties of networks, including modelling and graph algorithms, are among Jennifer’s research areas.

Caitlin Smallwood

Caitlin Smallwood is Netflix’s Vice President for science and algorithms, leading predictive decision models, algorithm research, and experimentation science.  Caitlin worked at Intuit, Yahoo!, and other mathematical consulting companies (PwC, SRA) before joining Netflix in 2010. Caitlin has a master’s degree in Operations Research from Stanford University and a bachelor’s degree in Mathematics from The College of William and Mary.

Yael Garten

Apple’s Siri Director of Data Science and Engineering is Yael Garten. She heads a team of engineers and data scientists whose goal is to enhance Siri by using data as the voice of Apple’s customers, and whose aim is to accelerate understanding and effective decision making and modelling within the cross-functional Siri organization through robust data usage and a culture of data excellence.

Yael previously worked at LinkedIn as the Director of Data Science. She excels at transforming data into useful product and business strategy.

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This post was originally published by Monomita Chakraborty at Analytics Insight

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