Eric Van Dusen named 2026 Chancellor’s Outstanding Staff Award recipient
Eric Van Dusen, Outreach and Tech Lead for Data Science Undergraduate Studies at University of California, Berkeley, has been named a 2026 recipient of the Chancellor’s Outstanding Staff Award (COSA).
The COSA honors staff members whose “exceptional initiative has made a significant positive impact on the UC Berkeley campus community.” Van Dusen was recognized for his contributions to developing Berkeley’s world-class data science education and expanding access across California’s community colleges, CSU campuses, and other UC campuses.
Conversation at UC Berkeley workshop shares perspectives on AI and humanity
A recent discussion at the National Workshop on Data Science Education illustrated the value of open conversation about the impact of AI on humanity.
Safiya Noble, an internet studies scholar, social scientist and UCLA professor, joined Jennifer Chayes, dean of the UC Berkeley College of Computing, Data Science, and Society (CDSS), during a June 24 afternoon session on the Berkeley campus. Their wide-ranging conversation considered the importance of critical thinking and interdisciplinary education, and the need for open systems to expand access to, and participation in, the development and use of AI technologies.
UC Berkeley alumni share insights on data science career paths at National Workshop
In a week filled with panels on pedagogy, curriculum design and emerging technologies in the classroom, the 2025 National Workshop on Data Science Education paused to ask a critical question: What comes next for the students we teach?
A panel of UC Berkeley alumni offered their perspectives, reflecting on how their undergraduate experience shaped their careers, what they wish they'd known earlier and how educators can better prepare students for a changing workforce.
Data Science Undergraduate Studies and Puente partner to inspire underrepresented students in STEM
This summer, we partnered with the Puente MaS program to introduce CA community college students underrepresented in STEM to the field of data science. Through student narratives, a career professional's advice, and information from our Data Science Undergraduate Studies team, the students discovered pathways into a major many had never heard of.
UC Berkeley convenes, connects California data science education pioneers
Dozens of California public educators walked into a sunlight streaked, first floor-room at the edge of UC Berkeley in late June. Hugging each other and snagging coffee or water, they navigated blue and gold star-shaped balloons to settle at tables facing a projector screen.
These scholars are part of a state effort to make California the nation’s leader in excellent, equitable and accessible undergraduate data science education. For the next two days, the assembled attendees would share how they’re building programming, community or pathways to do just that...
About our educational partnerships
UC Berkeley's Data Science Undergraduate Studies is dedicated to making high-quality data science education accessible beyond Berkeley. Through partnerships with other institutions, we strive to broaden access and impact.
Our approach to data science education:
- Empowers student discovery. Through our approachable foundations course and by developing curricula add-ons for other disciplines, we seed opportunities for students to discover this burgeoning field.
- Bridges disciplines. We view data science as an interdisciplinary field with applications spanning from the sciences to the humanities and we promote connections across these diverse areas.
- Integrates human contexts and ethics. Our curricula incorporates human contexts and ethical considerations, equipping students to make responsible and impactful decisions in their careers.
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Media
Data About Data Science: Rethinking How We Teach
In this episode, we speak with Alana Unfried, Professor of Statistics at Cal State Monterey Bay, about the future of statistics and data science education. Alana shares her path from classical statistics training to undergraduate teaching, educational research, and her work on MASDER, a national project focused on measuring student motivation, attitudes, and learning environments in statistics and data science classrooms.
Alana discusses why data science education needs stronger research tools, better shared data, and a clearer understanding of what students are actually experiencing in the classroom. She explains how MASDER helps faculty collect survey data, compare their classes to national trends, and contribute to a larger picture of what is working across institutions. The conversation also explores major gaps in access to data science education, especially between highly selective and more inclusive schools, and how different departments shape what students learn. Alana also reflects on the growing role of generative AI in data science education and why faculty development will be essential as the field continues to evolve.
Listen on Spotify or Apple Podcasts
Breaking Down the Walls: Community-Centered Data Science Education
In this episode, we speak with Kagba Suaray, Professor of Mathematics and Statistics at Cal State Long Beach, about building a more community-centered vision for data science education. Kagba shares how his work connects data science to local issues in Long Beach and Compton, from public health and housing justice to educational equity, while creating opportunities for students to learn through real, meaningful data. He discusses the power of interdisciplinary collaboration, breaking down barriers that keep students from seeing themselves as “data people,” and designing programs that make data science more inclusive, applied, and community-driven. Kagba also reflects on what it takes to build partnerships, support underrepresented students, and help communities tell their own stories through data.
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A New Frontier: Computational Health and AI Innovation
In this episode, we sit down with Adam Yala, Assistant Professor at UC Berkeley and UCSF and co-founder of Voio, to explore how AI is reshaping the future of healthcare. Adam walks through his path from research to building real-world systems, and why computational health is emerging as its own distinct field rather than just an application of AI. We dive into what it actually takes to build in this space, from understanding clinical complexity to navigating challenges like data access and compute. Adam also shares how his experience across academia and startups has shifted his perspective on speed, innovation, and creating meaningful impact.
Listen on Spotify or Apple Podcasts