KeynotesSIGCSE TS 2025
Dr. Cecilia Aragon
What is Human-Centered AI and Why Does It Matter?
There have been extraordinary advances in our ability to collect, analyze, and interpret vast amounts of data which have transformed the fundamental nature of artificial intelligence (AI). The human aspects of AI, including how to support creativity and human insight without violating individual rights, how to address ethical concerns, and the consideration of societal impacts, have received less attention. Yet these human issues are becoming increasingly vital to the future of AI. Dr. Aragon will reflect on a 30-year career in data science and AI in industry, government, and academia, discuss what it means for AI to be both rigorous and human-centered, and speculate upon future directions for data science and AI.
Bio:
DR. CECILIA ARAGON is Professor and Director of the Human-Centered Data Science Lab at the University of Washington. Her research focuses on analysis of vast data sets. Her awards for research, and a stint designing software for NASA, led President Obama to call her "one of the top scientists and engineers in the country” when she received the prestigious Presidential Early Career Award for Scientists and Engineers. She has worked with Nobel Prize winners, taught astronauts to fly, and created musical simulations of the universe with rock stars. She is one of the co-founders of Latinas in Computing. Dr. Aragon’s research has been recognized with over $28M in grants from federal agencies, private foundations, and industry, and she has published over 200 articles and 3 books. Her two latest books are Flying Free (Blackstone Publishing 2020) and Human-Centered Data Science (MIT Press 2022). She is a Distinguished Member of the ACM and a 2017-18 Fulbright Scholar. She won the Distinguished Alumni Award in Computer Science from UC Berkeley in 2013, the Faculty Innovator in Teaching Award from her department at UW that same year, and was named one of the Top 25 Women of 2009 by Hispanic Business Magazine. Most recently, she was featured in GeekWire on her latest venture, a tech startup.
Jamika D. Burge, PhD
Intersectionality is Computer Science Education
When the Double Bind Report (Malcom, Hall & Brown, 1975) was released fifty years ago, it was groundbreaking in that it illuminated, for the first time, the unique experiences of women of color in STEM careers, as students and professionals. It helped to expose the factors that describe why their experiences were different — factors that, until then, had largely gone unacknowledged. When it comes to computer science education, intersectionality, much like accessibility, presents the same opportunity — it informs our ability to develop CS curricula that meets all students’ needs by bringing awareness to the obstacles that affect some of our students. The result is transformative. In this talk, I will walk us through the brief, yet rich history of intersectionality in computing and show how its alignment to CS education drives outsized impact for the computing discipline.
Bio:
Dr. Jamika D. Burge is CEO and Co-Founder of blackcomputeHER.org, INC (pronounced ‘black computer’), a non-profit (501(c)3) dedicated to supporting computational thinking, design thinking, and workforce development for Black women and girls in computing+tech, which effectively supports the advancement of everyone in computing+tech. She is an authority on research and programming that investigates the intersectionality of Black women and girls in computing, and under her leadership, blackcomputeHER.org, INC has raised almost $2MM in capital for delivering impact through blackcomputeHER programming.
Jamika is also Founder and Principal of Design & Technology Concepts, LLC, a tech consultancy that focuses on computer science education & research and inclusive design. She has consulted for Google, the National Center for Women in Technology (NCWIT), the American Association of Colleges & Universities (AAC&U), the University of North Carolina at Charlotte, among others, and she was formerly a research scientist consultant with the Thurgood Marshall College Fund (TMCF). Jamika holds a PhD in computer science and applications from Virginia Tech. She and her work have been featured in the New York Times and ComputerWorld, and, in 2022, she was recognized, by Airtable, as one of the top 30 Black Women in Tech. In 2024, she was recognized as one of 100 top Black Women Leaders who are transforming corporate America, by Diversity Woman Magazine.
Dr. Burge has served on the advisory board for the Center for Minorities and People with DIsabilities in IT (CMD-IT) (since 2015), the Virginia Tech Alumni Advisory Board for the Computer Science Department (2017-2024); the Friends of Technology Advisory Board (Advisors to the President), at Grambling State University (since 2019); and the Center for Inclusive Computing, at Northeastern University (2020-2023)). She is a graduate of Fisk University, holds a PhD in Computer Science from Virginia Tech, and completed a postdoc at The Pennsylvania State University. In addition to serving as a research and industry practitioner, she has also been a computer science professor at several HBCU’s, including Spelman College, North Carolina A&T State University, and Howard University. Since 2020, she has served on the National Academy of Science Committee on Addressing the Underrepresentation of Women of Color in Tech, which delivered the report, Transforming Trajectories for Women of Color in Tech (2022).
From 2010-2014, Dr. Burge served as a tech consultant to DARPA, the Defense Advanced Research Projects Agency, in the Information Innovation Office. While there, she provided technical and management consultation for innovative DARPA programs which were funded at over $70M. Dr. Burge is currently Head of Enterprise Research & Insights for Data, AIML, and Software Design at Capital One.
Keynotes
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Closing Remarks Keynotes | |
Intersectionality IS Computer Science EducationHybrid Keynotes | |
Welcome and Opening Remarks Keynotes | |
What is Human-Centered AI and Why Does It Matter?Hybrid Keynotes |