Data Scientist, Senior Consultant, and Senior Instructor
Physics
I am staff at the Social Sciences D-Lab. I received my Ph.D. in the Physics department at Berkeley. My research lies in the realm of theoretical/computational neuroscience, which aims to use mathematical and computational tools to better understand how neural systems operate and process information. My projects include using information-theoretic techniques to study how neural variability impacts information processing in neural circuits and investigating the statistical issues that impede the interpretation of parametric models of neural activity.
Wadzanai is a graduate student at the School of Information and she is a part of the MIMS program. She has a vested interest in the integration between data science, technology and developmental surveillance techniques. She has prior experience working as a quantitative analyst in project management consulting within a professional services firm, public health, and most recently in sustainable construction materials. Wadzanai is particularly interested in increasing access of STEM subjects and fields to under-privileged women of color in the African continent, particularly her home...
Monica is a third-year Ph.D. candidate in the Environmental Science, Policy, and Management program. She uses computational tools to study the evolution and ecology of agricultural plant pathogens. Previously, she worked on a data science team at a biotech company in Boston.
James Hall is a graduate student in the Statistics MA program at University of California, Berkeley. He is a husband and father to three awesome kids. Originally from Baltimore, MD, James earned his bachelors in Mathematics at the United States Military Academy at West Point, NY in 2011, and served as a U.S. Army officer. He’s served as a leader at multiple levels within large organizations with a professional focus on visualizing and communicating complex analysis to decision makers. James’ experience and coursework give him expertise in navigating different statistical methods,...
Frances Leung is a master’s student at UC Berkeley School of Information where she focuses her studies in information and data science. She has a keen interest in leveraging data-driven insights to better understand consumer behaviors and the world around us. In her professional work as a management consultant, she advises retailers and consumer businesses on digital transformation and creating web/mobile experiences that delight consumers through a human-centered approach. Frances holds a Master in Business Administration from York University, Schulich School...
Irene is a PhD student in City and Regional Planning. Her research interests lie at the intersection of urban geography, political science, and public health. In particular, she studies street vendors in Mexico City and how the spatiality and politics of their working conditions impact their access to healthy food. She strongly believes in connecting with other social scientists to share perspectives on how to use technology to acquire greater knowledge of social phenomena.
Electrical Engineering and Computer Science (EECS)
Nikita Samarin is a doctoral student in Computer Science in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley advised by Serge Egelman and David Wagner. His research focuses on computer security and privacy from an interdisciplinary perspective, combining approaches from human-computer interaction, behavioral sciences, and legal studies. Samarin is a member of the Berkeley Lab for Usable and Experimental Security (BLUES) and an affiliated graduate researcher at the Center for Long-Term Cybersecurity (CLTC) and the...
Sam (he/him) is a Master of Information and Data Science graduate student at the School of Information, with experience in Cybersecurity and Network Programming. He holds a BS in Computer Systems Engineering from Rensselaer Polytechnic Institute and has previous experience in consulting at Deloitte. He has experience with Python, R, SQL, machine learning, data analytics, statistical analysis, and research design.
Seyi is a PhD Student in the School of Information and is a member of the Algorithmic Fairness and Opacity Group. Her research broadly explores the problem space of digital memory, specifically the social discourse surrounding algorithms, ethics, and engagement. Additionally, her work often explores histories of quantification and the politics of categories within emerging technologies. She uses a mixed methods approach to research; this includes ethnography, interviews, grounded theory, surveys, data analysis and values-based design. Here at the D-lab, she leads the qualitative...