Have you ever wanted to own a robot?
Imagine a scenario where a robot asks a woman if she wants help with the dishes while handing a man a beer. Where you can crib about your in-laws and neighbours to your robot and she becomes an active participant of your personal space at home. Exciting, no?
Or a scenario where your favourite TV serial actresses look real and be able to talk to you.
All the above mentioned situations appear a bit feminine, right? Well, today I am going to talk about the extraordinary “she bosses” who are changing the face of AI.
I have seen that AI is often portrayed as female – Alexa, Siri, Cortana, Lucy, Her, Tay, you name it. An AI's capabilities embody those traditionally found in solutions and products developed by more male programmers than female. Microsoft researcher Margaret Mitchell called domain of AI a “Sea Of Dudes”.
I think the sea needs to be in an equilibrium state with equivalent Dudettes.
Else, either it may flood or may lead to drought. As women augment and join their qualities with AI, they can together form better items that fulfill profound human needs. And that inspires me to get to know the leading women in AI.
Let’s shed some light on the prominent and remarkable profiles of the young talented ladies who want to tap out the same talent inside you!
1. Fei Fei Li
A prestigious scholarly in Computer Vision, Dr. Fei Fei Li joined Google Cloud as Chief Scientist of Artificial Intelligence and Machine Learning to propel her central goal of “Democratizing AI ”.
She is an Associate Professor at Stanford, where she coordinates both the Stanford AI Lab and Stanford Vision Lab.
Since getting a B.A. in Physics from Princeton and a PhD in Electrical Engineering from Caltech, Dr. Li has distributed more than 150 research papers in top level diaries and meetings and assembled ImageNet, a 15 million picture dataset that added to the most recent advancements in profound learning and AI.
She also co-founded AI4ALL, a platform to educate young people on AI.
Amid her 18 years as a Professor of Computer Science at Stanford, Dr. Daphne Koller composed more than 200 publications in top scientific journals and won an innumerate number of honors for scholastic achievements and perfection in training.
She went ahead to help establish Coursera, world's biggest online instruction stage, and now fills in as Chief Computing Officer at Calico Labs, an Alphabet (Google) R&D organization examining the science of maturing and creating mediations for more and more advantageous lives.
Dr.Koller was seen as one of the Fast Company's Most Creative People in 2014, and Time Magazine's 100 Most Influential People for 2012.
Dr. Koller is making an arrangement of computational apparatuses for manmade brainpower that can be utilized by researchers and architects to do things like foresee car influxes, enhance machine vision and comprehend the way disease spreads.
Her methods have been utilized to enhance computer vision frameworks and in understanding natural language, and later on they are relied upon to prompt an enhanced era of Web Search.
3. Cynthia Breazeal
Dr.Cynthia Breazeal is an Associate Professor of Media Arts and Sciences at Massachusetts Institute of Technology (MIT) where she established and coordinates the Personal Robots Group at MIT Media Lab.
She is additionally an author and Chief Scientist of Jibo (a personal robotics company with over $85 million in funding). Jibo, Inc. brings the innovations, plans bits of knowledge, & client experience of social robots to the home as the world's first family robot.
Dr.Breazeal is a pioneer of Social Robotics and Human-Robot Interaction. She authored a book - Designing Sociable Robots, and she has distributed more than 100 research papers on Autonomous Robotics, Human-Robot Interaction, and Robot Learning.
She serves on several editorial boards in the areas of Autonomous Robots, Affective Computing, Entertainment Technology and Multi-Agent Systems.
4. Marie DesJardins
Dr. Marie DesJardins is a Professor of Computer Science and Associate Dean for Academic Affairs, College of Engineering and Information Technology, at the University of Maryland, Baltimore County (UMBC), USA. At UMBC, she is the 2014-17 Presidential Teaching Professor and a member of the first cohort of UMBC's Hrabowski Academic Innovation Fellows.
Dr. DesJardins has been passionate about AI since its inception. During her Ph.D. at Berkeley, she worked on “Goal Driven Machine Learning” where she designed methods an intelligent agent can use to figure out what and how to learn. She has published around 120 research papers and got appreciated for the same.
She is also the Maryland team leader for the Exploring Computing Education Pathways (ECEP) Alliance, an NSF-funded initiative that is coordinating state-level CS education efforts.
Dr.DesJardins was also a founding member of the Maryland chapter of the Computer Science Teachers Association, and serves as the University liaison for the Chapter.
5. Nikita Johnson
Nikita Johnson is Founder of RE.WORK, an All Female run events organising company. RE.WORK consolidates enterprise, innovation, and science to re-work the future to explain a portion of the world's most noteworthy difficulties utilizing rising innovation.
She has already functioned as an International Events Director for Innovation Enterprise, which is also known as IEG, and has been involved in organizing Startup Weekend events.
She says, “If AI systems are built primarily by men only, then they are more likely to create biased results and the representation of the builders will dominate”.
Nikita helped to establish The London School of Economics & Political Science (LSE) Alumni Entrepreneurs Group, offering help to LSE Alumni beginning and developing their businesses.
6. Corianna Cortes:
Head, Google Research NY at Google
Corinna Cortes is the Head of Google Research, NY, where she is working on a broad range of theoretical and applied large-scale machine learning problems. Prior to Google, Corinna spent more than ten years at AT&T Labs - Research, formerly AT&T Bell Labs, where she held a distinguished research position. Corinna's research work is well-known in particular for her contributions to the theoretical foundations of support vector machines (SVMs), for which she jointly with Vladimir Vapnik received the 2008 Paris Kanellakis Theory and Practice Award, and her work on data-mining in very large data sets for which she was awarded the AT&T Science and Technology Medal in the year 2000. Corinna received her MS degree in Physics from University of Copenhagen and joined AT&T Bell Labs as a researcher in 1989. She received her Ph.D. in computer science from the University of Rochester in 1993.
Corinna is also a competitive runner, and a mother of two.
7. Raia Hadsell
She is a research scientist at Google DeepMind in London, UK. She brings robots to life using advances in deep learning and reinforcement learning, using principles and fundamentals derived directly from neuroscience.
She says, “I came to AI research obliquely. After an undergraduate degree in religion and philosophy from Reed College, I veered off-course (on-course?) and became a computer scientist. My PhD with Yann LeCun, at NYU, focused on machine learning using Siamese neural nets (often called a 'triplet loss' today) and on deep learning for mobile robots in the wild. My thesis, 'Learning Long-range vision for offroad robots', was awarded the Outstanding Dissertation award in 2009. I spent a post-doc at CMU Robotics Institute, working with Drew Bagnell and Martial Hebert, and then became a research scientist at SRI International, at the Vision and Robotics group in Princeton, NJ.
My research at DeepMind focuses on a number of fundamental challenges in AGI, including continual and transfer learning, deep reinforcement learning, and neural models of navigation (see full publications).
8. Cordelia Schmid
Cordelia Schmid is computer vision researcher, currently Head of the THOTH project team at INRIA (French Institute for Research in Computer Science and Automation), Montbonnot, France.
Schmid obtained a degree in Computer Science from the University of Karlsruhe, and her doctorate from the Institut National Polytechnique de Grenoble, with a prizewinning thesis on "Local Greyvalue Invariants for Image Matching and Retrieval".
Schmid was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2012 for contributions to large-scale image retrieval, classification and object detection. She was a co-winner of the Longuet-Higgins Prize in 2006 and again in 2014.
9. Suchi Saria
Assistant Professor at Johns Hopkins University
Saria’s interests span machine learning, computational statistics, and its applications to domains where one has to draw inferences from observing a complex, real-world system evolve over time. The emphasis of her research is on Bayesian and probabilistic graphical modeling approaches for addressing challenges associated with modeling and prediction in real-world temporal systems. In the last seven years, she has been particularly drawn to computational solutions for problems in health informatics (see her recent article on this topic) as she sees a tremendous opportunity there for high impact work.
Prior to joining Johns Hopkins, she earned her PhD and Masters at Stanford in Computer Science working with Dr. Daphne Koller. She also spent a year at Harvard University collaborating with Dr. Ken Mandl and Dr. Zak Kohane as an NSF Computing Innovation Fellow. While in the valley, she also spent time as an early employee at Aster Data Systems, a big data startup acquired by Teradata. She enjoys consulting and advising data-related startups. She is an investor and an informal advisor to Patient Ping.
She is originally from Darjeeling, India and (jokingly) adds that she can be bribed with good tea.
10. Anima Anandkumar
Principal scientist at Amazon Web Services, Professor at the California Institute of Technology
Anima's research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. Tensor decomposition methods are embarrassingly parallel and scalable to enormous datasets. They are guaranteed to converge to the global optimum and yield consistent estimates for many probabilistic models such as topic models, community models, and hidden Markov models. More generally, Anima has been investigating efficient techniques to speed up non-convex optimization such as escaping saddle points efficiently.
11. Devi Parikh
AI researcher at Georgia Tech and Facebook AI Research
She was featured in Forbes' list of 20 "Incredible Women Advancing A.I. Research".
I am an Assistant Professor in the School of Interactive Computing at Georgia Tech and a Visiting Researcher at Facebook AI Research (FAIR).
From 2013 to 2016 I was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. From 2009 to 2012 I was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed computer science academic institute on the University of Chicago campus. I received my Ph.D. and MS. from Carnegie Mellon University in 2009 and 2007 respectively. My advisor was Prof. Tsuhan Chen (now at Cornell University). I got my BS, also in ECE, at Rowan University in 2005, where I worked with Dr. Robi Polikar on several pattern recognition problems.
She has spent several months at:
Robotics Institute (RI), CMU (Visiting Research Assistant Professor, Summer 2012) collaborating with Martial Hebert
CSAIL, MIT (Visiting Scientist, Spring 2011) collaborating with Antonio Torralba and Aude Oliva
University of Texas at Austin (Research Fellow, Fall 2010) collaborating with Kristen Grauman
Microsoft Research (Redmond) (Visiting Researcher, Summer 2010, 2015; Research Intern, Summer 2008) collaborating with Larry Zitnick
Microsoft Research (Redmond) (Research Intern, Summer 2007) working with Gavin Jancke
Intel Research (Pittsburgh) (Research Intern, Summer 2006) working with Rahul Sukthankar
12. Preethi Narayanan
Preethi Narayanan is a veteran in building and setting up Product and Services functions for large enterprises and has 25+ years of experience.She is a transformational and innovative technology leader with an innate ability in resolving challenges. Preethi has led large and complex cross-functional initiatives across multiple domains.Currently serving as the President of AI services in Hotify AI, Preethi believes, “Artificial intelligence should be seen as a technology that partners with humans, to augment their intelligence, rather than perceived as a risk by some. It is up to us to make the partnership effective by building an ecosystem that leverages it - At Hotify, we believe in making AI work for you.”
Prior to joining Hotify, Preethi has spent over three years as CEO of India Operations at Invigor Group. She comes with vast expertise and innate business acumen across Retail, Supply chain and Healthcare domains. She has demonstrated exceptional drive in her prior roles that include Director-Product Centre of Excellence at iSOFT (CSC), and Technical Project Manager at Staples, USA.
So these are the awesome women in AI, who are being an epitome of motivation and learning. I believe participation is a crucial step for women to represent and grow in a domain that is still nascent. Kudos to you ladies!