Events

Upcoming Events

Berkeley Conversations on COVID-19: Creating Informed Responses: Berkeley’s Computing and Data Science In Action

Apr 7, 2020, 10:00 am to 11:30 am

Campuswide online video series

Information Access Seminar: Deirdre Mulligan

Apr 10, 2020, 3:10 pm to 5:00 pm

Deirdre Mulligan is an associate professor at the School of Information and the associate dean and Head of School

UC Berkeley’s Digital Lifecycle Program: Mass Digitization of Special Collections for Use and Preservation

Apr 17, 2020, 3:10 pm to 5:00 pm

How the UC Berkeley Library is digitizing its rare and special historical collections.

Seminar Project Reports

Apr 24, 2020, 3:10 pm to 5:00 pm

Student reports on e-commerce marketing, AI, and cloud information systems.

150 Years of Women at Berkeley

May 1, 2020, 3:10 pm to 5:00 pm

An overview of the 150 Years of Women at Berkeley project.

MIMS Final Project Showcase

May 14, 2020, 4:00 pm to 8:00 pm

Graduating master’s students present their intriguing research projects and innovative new information systems. A panel of judges will select outstanding projects for the James R. Chen Award.

Previous Events

101 Years of Women

Apr 3, 2020, 3:10 pm to 5:00 pm

An informal discussion of women in the history and heritage of the School.

Berkeley Conversations on COVID-19: Making Sense of Data, Social Distancing, and What Lies Ahead

Apr 3, 2020, 12:30 pm to 1:00 pm

Campuswide online video series

Rob Sanderson (photo: Sarah Waldorf/Getty Center)

Tiers of Abstraction and Audience in Cultural Heritage Data Modeling

Mar 13, 2020, 3:10 pm to 5:00 pm

Rob Sanderson is a semantic architect at the J. Paul Getty Trust and a passionate advocate for open culture, linked open data, and the digitization of cultural heritage.

Feminist Open Access and Internet Publishing

Mar 12, 2020, 5:00 pm to 8:00 pm

Discover how the Organization for Transformative Works built a model for non-corporate, user-driven, online participatory cultures.

Big Give

Mar 11, 2020, 9:00 pm to Mar 12, 2020, 9:00 pm

Seize the moment during Big Give, Berkeley’s annual fundraising event.

Howard Besser (photo by Dan Streible: http://flic.kr/p/7Wbqr8)

Archiving the Non-Organizational Born-Digital: The Challenges Posed by Material from Individuals, Communities, Social Movements, and Events

Mar 6, 2020, 3:10 pm to 5:00 pm

How archives and special collections can address the transition from analog to digital creation and the digital deluge.

Green NLP

Mar 6, 2020, 11:10 am to 12:00 pm

Roy Schwartz is a research scientist at the Allen institute for AI and at the computer science and engineering department at the University of Washington.

Ph.D. Research Reception

Mar 4, 2020, 4:10 pm to 8:00 pm

School of Information Ph.D. students share their innovative research with the community.

WiDS Berkeley

Mar 2, 2020, 8:45 am to 4:30 pm

Women in Data Science is a one-day technical conference bringing together data scientists and professionals from around the globe to discuss the latest research and applications of data science.

Seminar Project Progress Reports

Feb 28, 2020, 3:10 pm to 5:00 pm

What is Wrong with my Model? Detection and Analysis of Bugs in NLP Models

Feb 28, 2020, 11:10 am to 12:00 pm

Marco Ribeiro is a researcher at Microsoft Research, focused on helping humans interact with machine learning models meaningfully.

Repairing Innovation: The Labor of Integrating New Technologies

Feb 24, 2020, 4:10 pm to 5:30 pm

Madeleine Clare Elish uncovers the hidden labor behind automated aviation, driverless cars, small scale agriculture, grocery retail, and emergency healthcare.

Assessing the Reliability of Clothing-Based Forensic Identification

Feb 21, 2020, 3:10 pm to 5:00 pm

A 2009 report was highly critical of many forensic practices. This is the first thorough analysis of the purportedly distinct patterns on the seams of denim pants.

Veridical Data Science

Feb 19, 2020, 12:00 pm to 1:00 pm

Bin Yu is Chancellor’s Distinguished Professor of statistics and EECS. Her research focuses on practice, algorithm, and theory of statistical machine learning and causal inference.