Her research investigates new ways for K-12 students to learn about AI concepts, practices and ethics by designing, programming, training and interacting with robots, AI toolkits and other technologies. Her research also develops personalized learning companions for language, literacy and social-emotional development.

and the Abdul Latif Jameel World Education Lab. His research developed new standards for RFID and he has been very influental in the field of Internet of Things -- that are becoming increasingy intelligent and connected. His core interest areas for this project are K-12 AI education, vocational-technical AI training, and the future workforce.

He has developed tools and programming languages to help students learn about AI and computer science. App Inventor empowers people with little programming experience to write mobile phone applications. His team is expanding App Inventor to help students learn about AI and develop AI-enabled mobile apps.

His work uses a design based research methodology to span the K-12 educational technology ecosystem, from design and development of new technologies to professional development and implementation to prepare the next generation of STEM educators. He is Director of the Schellar Teacher Education Program.

learning and how we are measuring it. She has developed many game- and simulation-based assessments. Her evaluation projects use evidence-centered design in combination with educational data mining techniques. The Playful Journey Lab focuses on developing playful, authentic, yet rigorous learning assessments.

programming language and online community, used by over 200 million children and educators around the world. He is author of the book "Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers and Play." His focus in this project is how AI and Scratch can promote children's creative thinking.

the Global Entrepreneurship (G-Lab), Enterprise Management (EM-Lab), and the China and India Lab. He helps students put classroom theory into practice, as students work side-by-side with organizations to apply classroom lessons to high-impact business and society challenges. For this project, his key area of focus is in creating a new AI career pathway for vocational-technical education.

accessible and intuitive to non-AI students and researchers. For this project, she is playing a key role in the Bridge's efforts to develop engaging educational applications with Jupyter notebooks that allow students to explore machine learning concepts and techniques across interesting problem domains and datasets.

His research focus is on the neural mechanisms of memory, cognition, and emotion in the human brain and how those mechanisms are disrupted in neurological and psychiatric disorders. For this project, his interest is in early assessment and intervention to support young learners with special needs such as ASD and dyslexia.

technology strategy. He has written three award-winning books and published in top journals. He is now focused on helping employers, educators, and other groups to rethink the process of workforce learning around the world. George is co-chair of the MIT Sloan CIO Leadership Awards, faculty advisor to the Board of Directors for the Technology Business Management Council.

Laboratory. He is also the Director of Beaver Works, a joint center establihsed by MIT Lincoln Lab and the MIT School of Engineering. Beaver Works offers a project-based STEM summer program to talented high school students to learn about various technologies. AI related topics include autonomous driving, data science for health, digital assistants, and more.

Her expertise is in computational thinking and integrating computer science into STEM education. Her research investigates K-12 student learning through integrated STEM and computing curricula, teachers' development as computational thinkers, and new ways for K-12 students to learn foundational AI concepts.

strategies, calibration of self-efficacy, and on pedagogy related to active learning. She is interested in how teacher beliefs influence pedagogical choices. She has expertise in developing instruments to measure psychological constructs, and statistical analysis of the resultant data. She also runs project evaluations to assess impact from multiple perspectives.

She is an Advisory Member on the IEEE's Children & Youth Experiences Committee and her research focuses on translating policy to practice by collaborating across policy, industry, and advocacy to reimagine meaningful choice and control in sharing personal data. She previously led design for government agencies at U.S. Digital Service at the Obama White House.

where he earned he earned Ph.D., and is a Research Fellow in Digital Ethics and Governance at the Jain Family Institute. He studies the ethics of technology, develops best practices for responsible engineering and research, and teaching ethics to engineers.

focuses on developing social robot learning companions for early-language and literacy skills. He synthesizes insights from machine learning, affective and educational sciences, and children’s media design. He develops affective personalization algorithms and is interested in how transfer learning can accelerate and improve personalization across students.

a number of AI education projects, including PopBots, social robot learning companions that teach AI through social interaction. Additionally, she runs studies that investigate children’s relationships with intelligent agents. To address misunderstanding and mistrust of AI, Randi is preparing the next generation to use AI to solve important problems in their communities.

For her MEng thesis, she created the CloudDB block set for data sharing in App Inventor. Natalie aims to create tools that will lower the barrier of entry and raise the ceiling of possibilities for technical innovation. She joined the App Inventor team in 2016 on the Hong Kong CoolThink project. She taught high school STEM courses in Barcelona, interned at Apple as an Engineering Program Manager, and interned at Google as an Associate Product Manager.

encompass affective computing, human-robot interaction, machine learning, and psychology. She designs algorithms for social robots that can adaptively support and engage children as empathetic, peer-like companions to facilitate learning outcomes. She also computationally models parent-child interaction dynamics during storytelling.

Safinah Ali's work focuses on leveraging child-robot interaction to enhance early childhood literacy as well as developing children's learning mindsets such as creativity, growth mindset and curiosity. Her recent work involves designing game interactions that afford children and embodied robots co-create art. Her previous work has revolved around educational game design, assistive technology and human-computer interaction.

STEM learning technologies for children. She has worked as a researcher in the consumer robotics industry, focusing on human-robot interaction paradigms in the home, long-term livability, and robots in the lives of children and older adults. Her research interests include understanding the ethical, social, and emotional implications of technology. She is currently working on AI + Ethics curriculum for K-12 students.

team. Her work aims to empower young learners with technology to solve real world problems. At App Inventor, she is developing AI and Internet of Things (IoT) tools to allow anyone to create interconnected, intelligent systems. She believes that given the right tools, knowledge, and skills anyone can create significant positive change in his or her community.

interests lie in Machine Learning and its applications in the field of human-robot interaction and early-literacy education. His recent work focused on building graphical models using word semantics for predicting children's vocabulary from partial information about their existing vocabulary. Prior to this, he worked on algorithms to enable reinforcement learning agents to learn from human feedback. In industry, he has interned at Apple, Palantir and Microsoft where he worked on applications ranging from natural language understanding to anomaly detection.

developing curriculum activities at Code.org, game prototypes and production titles at PopCap, and co-developing the robot-smash-em-up indie game Clone Drone in the Danger Zone.

She has worked on a variety of gaming related projects, both for research applications and in the game industry. Her research interests focus on the use of games for sparking interest and creativity in educational contexts.

She develops educational materials to teach children to be both conscientious consumers and designers of AI systems. Before joining MIT, she completed her undergraduate studies at the University of South Carolina, where she earned a B.S. in Computer Science and Mathematics. Blakeley has completed several AI internships at institutions such as Adobe, Inc. and U.C. Berkeley.

She completed her B.S. at MIT with a double degree in Brain and Cognitive Sciences and Computer Science and Engineering, through which she found a passion for the science of intelligence. She is fascinated by perception and intuition, and explores questions around the uniqueness of human intelligence and its capacity for abstractions such as story understanding, emotion and memory, and Theory of Mind. Particularly, she loves how much we can learn about the mind from the way it develops, and also cares deeply about designing ethical, responsible AI systems for social good. Currently, Jenna is working on a multidisciplinary AI curriculum that focuses on human and machine perception.

Stephen leverages his multidisciplinary background in psychophysiology, cognitive systems engineering, and virtual production to engineer neuromorphic technologies that enhance both human and machine perception. His current research utilizes extended reality (XR) technologies, such as augmented reality (AR) and virtual reality (VR), to enhance human-robot task performance, communication, and teaming.

educational game development, interaction design, and computational HRI. His interest is the intersection of cognitive science and robotics. He is especially interested in studying social cognition and developing human-robot interactions that could provide unique and uplifting experiences for people.

Previously, he’s been in engineering, product management and business development roles in industry in both the U.S. and in Israel. Jeff holds a B.Sc. in mechanical engineering from Cornell University and a M.Sc. in mechanical engineering from the Ben-Gurion University of the Negev. He also holds a M.Sc. in management from Boston University.

He is interested in creating opportunities for learners to tinker, design, and create personally and socially meaningful projects. He has designed and facilitated creative learning experiences at museums, libraries, and other informal learning spaces. He holds an EdM in Technology, Innovation, and Education from the Harvard Graduate School of Education.

At MIT App inventor he leads an NSF funded collaboration with YR Media (former Youth Radio) on the Youth Mobile Power series and the Outsmarting Artificial Intelligence project as well as coordinating international contests such as the App of the Month, Coronavirus App Challenge and the annual virtual Hackathon.

She spent most of her career teaching Computer Science, in several international schools and around New England. She has also served on board of directors for the Computer Science Teachers Association and is passionate about Computer Science education and exposing students to the boundless opportunities CS presents.

She leads the design and development of educational games and playful technologies for learning, contributing to research on how technology can support creative learning experiences for students and teachers. She also brings the playfulness of games into her assessment design work, creating digital and non-digital tools to help both learners and educators assess open-ended work and human skills.

Her research centers around different areas of cognition and how games can be implemented to not just help people learn, but also measure elusive constructs. She received her PhD in Education from University of California, Irvine, an Ed.M. in Mind, Brain, and Education from Harvard Graduate School of Education, and a B.A. in Psychology from New York University. At UC Irvine, she was trained as a Pedagogical Fellow and conducted teaching assistant and course design PD workshops for both first year graduate students and postdocs across various disciplines. Prior to joining MIT, Grace was a postdoctoral fellow at the University of Oregon, working with nonprofit organizations and on an early childhood measures repository.

Currently, she is working on creating a set of Scratch tools and activities for a middle school AI curriculum focused on human and machine audition. Her research interests include signal processing, robotics, and creative human-AI collaboration.

She will design workshops on reinforcement learning to be taught to both K-12 students and adults. Throughout her undergraduate and graduate time at MIT, she has concentrated on AI in coursework, internships, and teaching positions.