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.

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.

Alongside the MIT App Inventor team, she has developed an interface to enable nearly anyone to develop conversational agents, a web-based teachable conversational agent for 3-5th graders, and a voice-first, natural language tool for programming. She believes that given the right tools, knowledge and skills, anyone can create significant positive change in their 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.

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.

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.

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.

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.

Previously, he’s worked in R&D, product management, marketing and business development roles in industry. 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.

Her work with RAISE provides a unique nexus for her background as an educator and in the arts, as well as her current work with the Diversity & Leadership program at the Media Lab.

He has earned a Masters degree in Technology (Control Systems) with diverse experience in engineering, education, instructional design and curriculum development. He will be collaborating with MIT on research objectives, towards the further development of student curricula and teacher training materials.

Before joining MIT, she taught computer science to middle school students in Cambridge, Massachusetts. She is particularly interested in making computer science education accessible and engaging to students who don't yet see themselves in STEM. 

exploring intersections of technology and playful constructionist pedagogies in the classroom. 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.

He previously designed and wrote ​​educational materials for NASA and for out-of-school engineering programs at PBS. In his role as a technology journalist, Robert ​​has served as a senior editor at Wired magazine, and as a contributing writer for Wired, Popular Science, and Make magazines. His 2005 publication, Makers, was the first book about the maker movement.