Please join us on Thursday, November 15 from 10am-noon for the Social Science Matrix Distinguished Lecture, which will be delivered by Alondra Nelson, president of the Social Science Research Council and

This panel discussion will feature scientists in the life sciences who are working on critical research to push their fields in new directions. The panel will focus on scholarly contributions to upend histories of heterosexism, biological determinism, and environmental injustice.

Presented by the Citrin Center for Public Opinion Research, this panel discussion will offer insights and analysis focused on the 2018 mid-term elections.

Please join us for a panel discussion and Q&A presented as part of a Matrix Research Team entitled "Community Conversations on Sexual Violence and Harassment: Narratives of Activism, Inclusion, Confidentiality, Accountability, and Healing". The discussion will focus on the limits of what can be learned about sexual violence and harassment from personal narratives that are shared online, as well as the question of is missed in survey data related to sexual violence and harassment.

Please join us on September 20 for "Navigating Borders and Violence: Indigenous Maya Families and Central American Children in Migration," featuring presentations by two scholars. Leisy J. Abrego, Associate Professor, Department of Chicana/o Studies at UCLA, will present “It is a Crime to be Young Here: Violence Against Minors in Central America, Mexico, and the United States". Patricia Baquedano-López, Associate Professor in the UC Berkeley Graduate School of Education, will present "Pedagogies of Migration/Reframing: What It Means to Teach and Learn Indigenous Maya Families from Yucatán in California".

A panel discussion focused on the new textbook, Artificial Intelligence Safety and Security. Panelists include: Catherine Olsson (Google Brain); Roman Yampolskiy (The Editor of Artificial Intelligence Safety and Security): Author of Preface: “Introduction to AI Safety and Security”; Alexey Kurakin (Google AI): First Author of Chapter 8: “Adversarial Examples in the Physical World” with co-authors Ian J. Goodfellow and Samy Bengio; Phillip Kuznetsov (Machine Learning @ Berkeley): First Author of Chapter 17: “Adversarial Machine Learning” with co-authors Riley Edmunds, Ted Xiao, Humza Iqbal, Raul Puri, Noah Golmant, and Shannon Shih; Mahendra Prasad (UC Berkeley Political Science): Author of Chapter 21: “Social Choice and the Value Alignment Problem”; and Thomas Gilbert (UC Berkeley Machine Ethics and Epistemology).

DUE TO TRAVEL CHALLENGES RELATED TO HURRICANE FLORENCE, THIS EVENT HAS BEEN CANCELLED.

How do our strategies of fighting fire have to change to match the new normal, and when there is a fatality do we have to ask questions differently? Ivan Pupulidy, PhD. applies dynamic perspectives to complex systems and high-risk environments, such as wildland firefighting, aviation, military and medicine. His approach to human factors includes the social aspects of human interaction and sensemaking, which are essential components of a learning organization. As a U.S. Forest Service Director, Ivan replaced the traditional accident investigation model with the Learning Review, which embraces complex events by looking at conditions and networks of influence; this approach helps organizations develop learning and cultural change.

Social scientists are increasingly taking advantage of machine learning methods to gain new insight into their data and expand their methodological toolbox. Presented as part of the ICPSR Summer Program in Quantitative Methods of Social Research, this course covers both supervised and unsupervised machine learning methods but will place special emphasis on the (often) underappreciated suite of unsupervised learning tools.