Omalabake Adenle, Director, AJA.LA Studios
Omolabake Adenle founded AJA.LA Studios to develop speech technologies for low-resource languages, primarily focusing on African languages. She is also founder of AJA.LA Social, a non-profit that advocates for access to and education on the impact of language technologies for members of marginalized communities. Prior to AJA.LA Studios, she served as a vice president of quantitative strategies at Morgan Stanley. Her awards include two Innovate UK grants, selection as a finalist for the 2017 Innovation Prize for Africa, and finalist for Best Innovation for Development at the 2018 Spindle Awards. She holds a Ph.D. in information engineering from Cambridge University.
Benjamin Grewe, Professor of Systems Circuits and Neuroinformatics, ETH Zurich
Benjamin Grewe focuses on developing new technologies related to computer science, machine learning, and brain science. His lab combines research projects in deep artificial neuronal networks and systems neuroscience. He conducted post-doctoral research at Stanford University investigating neuronal network learning algorithms in the mouse brain, which led to several ground-breaking publications. His research group at ETH Zurich engages in numerous public outreach activities, including participating in the ETH Zurich Pavilion at the annual World Economic Forum’s Annual Meeting in Davos, Switzerland. Grewe earned a Ph.D. at ETH Zurich in neuroinformatics and was awarded the Pfizer Research Prize in 2011.
Michael Littman, Professor of Computer Science and Co-Director of Humanity-Centered Robotics Initiative, Brown University
Michael Littman studies machine learning and decision-making under uncertainty. He has earned multiple university-level awards for teaching, and his research on reinforcement learning, probabilistic planning, and automated crossword-puzzle solving has been recognized with three best-paper awards and two influential paper awards. His public engagement includes a collection of parody song videos on YouTube covering important topics in computer science (he also enjoys performing music with his family). Littman is a founding member of "AI Hub", an organization with the goal of providing free high-quality information about AI to the public. He received a Ph.D. in computer science from Brown University.
- Collusion Rings Threaten the Integrity of Computer Science Research, Communications of the ACM, June 2021
- Michael Littman Views AAAS Public Engagement Fellowship as a Lighthouse Illuminating His Goals, AAAS News, April 12, 2021
Heather Lynch, IACS Endowed Chair for Ecology & Evolution, Stony Brook University
Heather Lynch is a quantitative ecologist whose research focuses on the population dynamics of Antarctic wildlife. Lynch has pioneered the use of satellite imagery for studying the distribution and abundance of Antarctic seabirds and published the first Antarctic-wide satellite-based surveys of both Adélie penguins and Antarctic petrels. More recently, her research group has been developing computer vision-based tools for annotating satellite imagery, for penguins, pack-ice seals, and whales. She co-leads an NSF-funded program to train graduate students to work at the science-policy interface. Her work has been covered extensively in the media, and she engages K-12 students and citizen scientists to help search for undiscovered penguin colonies using publicly available satellite imagery, including working directly with tour groups in the Antarctic. Lynch has a Ph.D. in organismic and evolutionary biology from Harvard University.
Nicholas Mattei, Assistant Professor of Computer Science, Tulane University
Nicholas Mattei's research focuses on the theory and practice of artificial intelligence, machine learning, data science, and the impact of these technologies on society. He is motivated by both creating new systems and technologies, and by educating others about the possibilities and opportunities of computer science. His research leverages theory, data, and experiments to create novel algorithms, mechanisms, and systems that enable autonomous agents and humans to make better decisions individually and in groups. Before joining Tulane, he had a series of other research and development positions in government, private industry, and academia. He received his Ph.D. in computer science from the University of Kentucky.
- Nicholas Mattei Brings Service-Learning and Community Engagement into Tulane's Computer Science Department, AAAS News, April 7, 2021
Anita Nikolich, Director of Research and Technology Innovation and Research Scientist, University of Illinois
Anita Nikolich works at the intersection of cybersecurity, privacy and networked technologies. She is the recent co-recipient of an NSF MidScale Award addressing design of a secure future Internet. She helps organize hands-on cybersecurity events for K-8 students, the AI Village at DEFCON, a security conference that attracts over 25,000 attendees, and the Taste of Science program in Chicago. She works to engage people in understanding the privacy implications of mass data collection, algorithmic models for decision-making, and the need for better information authenticity indicators in an era of “deep fakes.” Nikolich has an M.S. in engineering from the University of Pennsylvania.
Carolyn Rose, Professor of Computer Science, Carnegie Mellon University
Carolyn Rose focuses on AI technologies such as machine learning, text mining, conversational agents, and robotics. Her award-winning research program is situated at the frontiers between artificial intelligence, education, and society. She spearheaded the inception of the International Alliance to Advance Learning in the Digital Era (IAALDE), an umbrella organization that brings together 11 different national and international research societies to integrate and disseminate scientific findings from across the societies. She is a past president of the International Society of the Learning Sciences, and Senior Member of IEEE. Rose has a Ph.D. in language and information technologies from Carnegie Mellon University.
Brian Scassellati, A. Bartlett Giamatti Professor of Computer Science, Cognitive Science, and Mechanical Engineering, Yale University
Brian Scassellati’s research focuses on understanding how humans and robots interact with each other, using methods from artificial intelligence to build smarter and more interactive machines and methods from psychology to understand how robots reveal our uniquely human social capabilities. He and his students build socially assistive robots to help children with autism spectrum disorder learn social skills, collaborative manufacturing robots that work with people on everyday tasks, and humanoid robots that help us understand why we treat some robots as objects and other robots like people. He currently serves on the Executive Council of the Association for the Advancement of Artificial Intelligence (AAAI). His work has been covered extensively in the media. Scassellati received his Ph.D. in computer science from the Massachusetts Institute of Technology.
William Smart, Professor in the Robotics Program, Oregon State University
Bill Smart’s research focuses on questions in human-robot interaction, long-term autonomy, and the intersection of robotics, law, and policy, such as: how can we design robots that collaborate with humans to make them more productive and effective? How do these systems interact with our current legal, policy and regulatory frameworks? How do we talk about these new technologies in a nuanced and meaningful way with the people who will be most impacted by them? Smart is also an Oregon Museum of Science and Industry (OMSI) Science Communication Fellow. He holds a Ph.D. in computer science from Brown University.
Biplav Srivastava, Professor of Computer Science, University of South Carolina
Biplav Srivastava’s research interest is in enabling people to make rational decisions despite real world complexities of poor data, changing goals and limited resources. He is exploring new approaches for goal-oriented, ethical, human-machine collaboration via natural interfaces using domain and user models, learning, and planning. He is also interested in understanding issues affecting the adoption of AI technologies and impacts on the workforce, and removing those barriers. Srivastava has applied AI using sensor and open data in domains like water, traffic, space and health. He has interacted with commercial customers, universities, and governments to communicate the relevance of state-of-the-art AI methods to stakeholder priorities. Srivastava earned a Ph.D. in computer science from Arizona State University.
- Biplav Srivastava Applies Artificial Intelligence to Real-World Challenges, AAAS News, May 5, 2021
- Bihar poll further reinforces robustness of Indian election model, Indian Express, November 13, 2020
- A new data-driven model shows that wearing masks saves lives – and the earlier you start, the better, The Conversation, November 13, 2020
Lyle Ungar, Professor of Computer and Information Science, University of Pennsylvania
Lyle Ungar’s research group uses machine learning and text mining to study personality, culture and other drivers of well-being (e.g., friendship, empathy, stress, and depression), often as revealed in social media language. He also studies the use of computers to enhance both individual and group decision-making and to support positive habit formation. Ungar co-leads the World Well Being Project (wwbp.org), a group of psychologists, computer scientists and physicians seeking to understand and improve well-being around the world. He has a Ph.D. in chemical engineering from the Massachusetts Institute of Technology.
John Zimmerman, Tang Family Professor of Artificial Intelligence and Human-Computer Interaction, Carnegie Mellon University
John Zimmerman researches interaction with intelligent systems, service innovation via social computing, human-robot interaction, and how technical systems can help people become the person they desire to be. While at Philips Research, he co-invented a method for scrolling touchscreens that is used on most smartphones and tablets. He has also designed TV show recommenders, a decision support tool that helps cardiologists decide when to implant mechanical hearts, and a crowdsourced real-time arrival system for transit riders. For the last several years he researched why AI is so difficult for designers to engage as a design material. Zimmerman holds a Masters in interaction design from Carnegie Mellon University.
- John Zimmerman Seeks to Make AI More Useful and Build Public Engagement into His Proposals, AAAS News, June 9, 2021