Organizing Committee

Vincent is a Professor of Human-Computer Interaction at Carnegie Mellon University, with 30 years of experience in research and development of AI-based learning technologies grounded in cognitive theory, self-regulated learning theory, and user-centered design. His lab created Mathtutor, an AI-based tutoring software for middle school math and the tools for the development and deployment of AI-based software, CTAT and Tutorshop. Vincent has written over 250 publications, with he and his team winning 11 best paper awards at international conferences, and has acted as PI or co-PI on 20 major research grants. Currently, Vincent is co-editor-in-chief of the International Journal of Artificial Intelligence in Education (IJAIED).

Email: aleven@cs.cmu.edu  

https://www.cs.cmu.edu/~./aleven/

Emma is an Associate Professor in the Computer Science Department at Stanford University where she aims to create AI systems that learn from few samples to robustly make good decisions. Her work is inspired and motivated by the positive impact AI might have in education and healthcare, with interests in foundation and large language models to advance AI-assisted human tutoring systems. Emma is part of the Stanford AI Lab, the Stanford Statistical ML group, and AI Safety @Stanford. She has received a NSF CAREER award, Office of Naval Research Young Investigator Award, a Microsoft Faculty Fellow award and an alumni impact award from the University of Washington. Emma and her lab have received multiple best paper nominations and awards for their AI and machine learning work (UAI best paper, Reinforcement Learning and Decision Making Symposium best paper twice) and Ai of education (Intelligent Tutoring Systems Conference, Educational Data Mining conference x3, CHI). 

Email: ebrun@cs.stanford.edu

http://cs.stanford.edu/people/ebrun/

Scott is a Professor of Special Education at Vanderbilt University. His primary research focus is on natural language processing and the application of computational tools and machine learning algorithms in language learning, writing, and text comprehensibility. His main interest area is the development and use of natural language processing tools in assessing writing quality and text difficulty. He is also interested in the development of second language learner lexicons and the potential to examine lexical growth and lexical proficiency using computational algorithms. 

Email: scott.crossley@vanderbilt.edu

https://learlab.org/

Dora is an Assistant Professor in Education Data Science at Stanford University. Her research focuses on measuring equity, representation and student-centeredness in educational texts, with the goal of providing insights to educators to improve instruction. She develops measures based on natural language processing that work well for high-dimensional, unstructured data, and she applies these measures to provide feedback to educators. Dr Demszky has received her PhD in Linguistics at Stanford.

Email: ddemszky@stanford.edu 

www.dorademszky.com 

Shiv is the Head of Product at PLUS - Personalized Learning Squared at Carnegie Mellon University. A graduate of the METALS program at CMU, Shiv was the lead curriculum developer at First Code Academy in Hong Kong and previously worked on corporate training in the metaverse. In his free time he follows Manchester United and the Golden State Warriors. 

Email: shivang@cmu.edu

PLUS: http://tutors.plus

Ken is the Hillman professor of Computer Science and Psychology at Carnegie Mellon University and founder of PLUS tutoring. He is a co-founder of CarnegieLearning, Inc. that has brought Cognitive Tutor based courses to millions of students since it was formed in 1998, and leads LearnLab, the scientific arm of CMU's Simon Initiative. Through extensive research and development in human-computer tutoring, Ken has demonstrated a doubling of math learning among middle school students, with future aims at bringing similar high-quality tutoring at scale. He has authored over 300 research papers and over 60 grant proposals. 

Email: koedinger@cmu.edu

PLUS: http://tutors.plus

http://pact.cs.cmu.edu/koedinger.html.org

Chris is an Assistant Professor in Computer Science at Stanford University. His research is in AI (and other computational methods) for education. He teaches introduction to Computer Science, CS106A and the online offering, Code in Place. The secret ingredient to both courses is high-quality human tutoring at scale.

Email: cpiech@stanford.edu 

https://stanford.edu/~cpiech/bio/index.html

Steve Ritter is Founder and Chief Scientist at Carnegie Learning. Dr. Ritter earned a doctorate in cognitive psychology at Carnegie Mellon University and was instrumental in the development and evaluation of the Cognitive Tutors for mathematics. He led the transfer of the Cognitive Tutor technology to Carnegie Learning, where it forms the basis of the company’s MATHia intelligent tutoring system. Dr. Ritter is the author of numerous papers on the design, architecture and evaluation of adaptive instructional systems and is recognized as an expert on the design and evaluation of educational technology and on educational analytics. At Carnegie Learning, Dr. Ritter leads a research team devoted to using learning engineering to improve the efficacy of the company’s products. Current projects focus on such issues as algorithmic bias in educational AI, supports for teaching math to struggling readers and the UpGrade tool for supporting rigorous field tests of educational software.

Email: sritter@carnegielearning.com

Carnegie Learning: www.carnegielearning.com

LinkedIn

Danielle is a systems scientist at Carnegie Mellon University and research lead on the PLUS - Personalized Learning Squared tutoring project. She is a former middle school math teacher, instructional coach, and school administrator, founding several mentoring programs supporting young women and youth in STEM. Danielle leverages her past experiences to advance AI-assisted human tutoring through research and development of tutor training and the creation of AI-assisted tutor feedback. She has first-authored over a dozen peer-reviewed papers since 2021.  

Email: drthomas@cmu.edu

PLUS: http://tutors.plus

LinkedIn 

Simon is a co-founder of Eedi and also host of the Data Science in Education meetup. He coordinates Eedi's machine learning research, which has been conducted in collaboration with Microsoft Research, and turns this into new product features. With experience leading both product development and research, he has created award-winning edtech solutions with strong data science foundations.  

Email: simon.woodhead@eedi.co.uk

Eedi: http://www.eedi.com/

LinkedIn

Wanli is an assistant professor of educational technology at the College of Education. His research themes are: (1) explore and leverage educational big data in various forms and modalities to advance the understanding of learning processes; (2) design and develop fair, accountable and transparent learning analytics and AI powered learning environments; (3) create innovative strategies, frameworks, and technologies for AI, Data Science, and STEM education.

Email: wanli.xing@coe.ufl.edu 

https://uf-aice-lab.github.io/AICE/index.html