Emily Q. Wang
Emily is a PhD student in the Technology and Social Behavior program. Her research in human-computer
interaction focuses on creating accessible groupware systems for Deaf and hearing professionals. Before
coming to Northwestern, Emily completed a self-designed engineering major with coursework in computer
science, human-centered design, and psychology at Olin College of Engineering.
JaCoya is a PhD student in the Department of Computer Science at Northwestern University. She graduated
from Fayetteville State University (FSU) with a Bachelors of Science degree in Computer Science with a
minor in Mathematics and a Masters of Science degree in Mathematics. She’s currently building and using
current technologies that allow 6-12th grade students to create, learn, and engage with data science. Her
area of interest includes using technologies to improve and enhance methods of instruction and
investigating instructional strategies that promote equal access to individuals from culturally diverse
Michael Smith is a Computer Science and Learning Sciences PhD student at Northwestern University,
and a National GEM Consortium PhD Fellow. Some of his research and project interests include exploring
the intersections of technology & education, formal and informal learning, computing culture, new media
and community, and games.
Coming from Malden, MA, Natalie is a Ph.D. student in Computer Science and
Learning Sciences. She graduated with a Computer Science degree from the University of
Pennsylvania as both a Questbridge Match Scholar and Janey Scholar. Natalie has a passion
for empowering students. Her interests lie in identity, collaboration, and belonging.
Kit grew up in Sudan, a country in a civil war. From there he moved around a lot. These travels motivated
him to notice the gross disparities. This motivation got him started working with disadvantaged youth in
Nashville back in the ’90s and running a mentoring program in Upstate New York in the 2000s. This
motivation has taken him into simulation through agent based models, especially models dealing with social
systems that demonstrate the intersubjective development of inequality. Kit has an M.A. in international
development and experience working overseas implementing field projects in loan provision, agricultural
systems transformation and recycling efforts. Kit also has experience teaching biology, population dynamics
and computer programming through ant based models in schools in Nashville, Tennessee with Vanderbilt. Kit
is currently interested in multi-modal sensors. He sees them as a bridge between agent based methods and
his other evaluations frameworks.
Sarah is from West Rogers Park, Chicago. She is a PhD student in Learning Sciences. She is currently interested
in the microacts of teaching, learning, and identity development through hands-on making and in intergenerational
Stephanie is a Ph.D. Student in Computer Science and Learning Science from the Philadelphia area. She's a
graduate of Villanova University where she studied Computer and Electrical Engineering. She is interested
in increasing access to STEM for underrepresented youth through informal learning opportunities. She is
additionally interested in the intersections of socio-cultural theories, constructionism, and multi modal
analytics. When not doing research she can be found laughing at her own jokes, watching YouTube, or using
Originally from Tel-Aviv, Israel and currently working on his PhD in Learning Sciences at Northwestern's
School of Education and Social Policy. David is interested in out-of-school learning and particularly how
children learn around popular culture and media.
Connor is a Ph.D. student in Computer Science and Learning Sciences originally from Columbia, SC. He's a
proud University of South Carolina alumnus who studies how to help teachers integrate computation into
their classrooms and how to get students to think with computation.
Born in Bronxville, New York and raised in Ellicott City, Maryland, Khalil, a UMBC Alum, is a Computer
Science PhD student with interests in Machine Learning. More specifically with interests in Reinforcement
Learning, NLP, and how Machine Learning can help augment, not necesarily replace, humans in task and jobs
such as driving, learning, manufacturing, and any other area.