Squirrel AI Learning has established major research collaborations with leading research institutions such as SRI International, Chinese Academy of Sciences, Carnegie Mellon University and UC-Berkeley.

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Squirrel AI Learning (Yixue)-SRI Joint Lab of AI-based Adaptive Learning

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Squirrel AI Learning - Chinese Academy of Sciences Joint Lab of AI Adaptive Learning


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Tom Mitchell Ph.D., Interim Dean & Professor of the School of Computer Science at Carnegie Mellon University, Chief AI Officer of Squirrel AI Learning

Professor Mitchell is a former Chair of the Machine Learning Department at CMU. Mitchell is known for his contributions to the advancement of machine learning, artificial intelligence, and cognitive neuroscience and is the author of the textbook Machine Learning. He is a member of the United States National Academy of Engineering since 2010. He is also a Fellow of the American Association for the Advancement of Science and a Fellow of the Association for the Advancement of Artificial Intelligence.

He is a prolific author of scientific works on various topics in computer science, including machine learning, artificial intelligence, robotics, and cognitive neuroscience. He has authored about 130 scientific articles. Mitchell published one of the first textbooks in machine learning, entitled Machine Learning in 1997.


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Edgar Kalns, Ph.D., Technical Director, Information and Computing Sciences of SRI International

Edgar leads multi-disciplinary teams of researchers and software engineers to design and deliver prototypes for commercial clients who are seeking novel, AI-based capabilities to enhance their product portfolios.  These innovations comprise machine learning components from multiple SRI research labs with expertise in voice interactions, natural language, text analytics, and computer vision. Kalns also leads SRI’s Microservices Platform which facilitates lab-to-product transition of AI software assets. Previously, Kalns directed SRI’s Studio on Aging, a set of R&D projects focused on monitoring the health of seniors in their homes.

Prior to joining SRI, Kalns was Head of Products & Engineering at [24]7.ai, a company that enables chat- and voice-based customer care interactions for Global 100 enterprises. In his role, he was responsible for all product management and engineering activities for the company’s digital virtual assistant and automated speech recognition products. He holds six U.S. patents.


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Marie Bienkowski, Ph.D., Center Director, SRI Education

Marie Bienkowski directs the Center for Education Research & Innovation. She has more than three decades of experience at SRI in educational technology research, education project and program evaluation, and artificial intelligence software design and development.

Bienkowski has developed a broad policy-level perspective on education research through her participation on National Science Foundation (NSF) program evaluations. She was a coauthor on the research brief on Using Technology to Personalize Learning in K–12 Schools. Bienkowski is a regular reviewer for the AERA Division C section on Engineering and Computer Science, for the Learning Analytics & Knowledge annual conference, and for the annual conference on Innovation and Technology in Computer Science Education (ITiCSE). She is an associate program chair for the annual meeting of the Association for Computing Machinery’s Special Interest Group on Computer Science Education (SIGCSE). She regularly reviews for computer science education-related journals (e.g., ACM’s Transactions on Computing Education) and ACM InRoads, and she was on the editorial board for Teachers College Record.


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Girish Acharya, Engineering Director, Artificial Intelligence Center of SRI International

Girish Acharya is responsible for integration of CALO/PAL, which aims to create a next-generation personal cognitive assistant that learns and self-improves in the wild. The ambitious effort brings together 22 leading research institutions, universities and commercial companies.

Prior to SRI, Acharya was a senior consultant at HP, where he helped design and implement an HP content management bridge between hundreds of authoring and publishing communities. He also previously was director of engineering at Verticalnet, where he brought together a large team for building supply chain applications.


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Phil Vahey, Ph.D., Director of Strategic Research and Innovation of SRI Education

Phil Vahey, Ph.D. is Director of Strategic Research and Innovation in SRI International's Center for Technology in Learning (CTL). Vahey's research examines the design and use of technology-based systems that enhance the learning of conceptually difficult STEM concepts, as well as how to scale up the use of these systems.

His research has focused on the use of computer-based dynamic representations for making foundational concepts in mathematics accessible to a diverse middle school student population, and the use of media and games for making ideas in Math, Science, and Computational Thinking more accessible for preschool children. Vahey leads CTL's SunBay Digital Mathematics Projects, the Ready to Learn evaluation, and is the SRI lead on the Next Generation Preschool Math project.

He has been a senior contributor to other projects, including the Next Generation Preschool Science Project, the SimCalc project, the Evaluation of Early Elementary Mathematics Curricula project, and CTL's commercial efforts.


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Min Yin, Senior Software Engineer, Artificial Intelligence Center of SRI International

Min Yin builds, designs, develops and releases software systems for a variety of audiences and customers. She is a major contributor to research and commercial projects including fast prototypes that support innovative research ideas (Autism Robot and Virtual Personal Assistant); viable bridge systems that attract venture capital (Siri and Tempo); and large customized and commercial systems (TA and BBVA).


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Sam Wang, Ph.D., Education Researcher of SRI Education

Sam Wang, Ph.D., an education researcher in the Center for Technology in Learning at SRI International, has extensive quantitative research experience in education. He specializes in planning, designing, and conducting rigorous mixed-methods research to evaluate educational interventions in STEM (science, technology, engineering, and mathematics) education.

The overriding goal of Wang’s research is to document and understand successful STEM learning and ultimately to develop evidence-based principles for STEM education. Wang is currently a quantitative lead for studies of the effectiveness of online instructional systems/resources to (1) promote STEM learning among secondary and postsecondary students, (2) boost college access and student success, and (3) improve basic literacy and numeracy skills among low-skilled adults. His work has appeared in a number of peer-reviewed education research journals, such as Computers & EducationDevelopment and PsychopathologyInternational Journal of Science Education, and Journal of Research in Science Teaching.