I am a first year masters student at UC Berkeley school of Information majoring in Information Management and Systems with a focus on Data Science and ML. I like to build optimized yet simple and scalable solutions powered by data using emerging AI technologies.
Daniel Lobo is a PhD student in the Department of Sociology with an emphasis in Political Economy at UC Berkeley. He is broadly interested in how culture, or the unspoken “rules of the game,” reproduces inequality within a system of racial capitalism. At the individual level, he is interested in documenting and measuring the extent to which cultural capital and social capital enable or constrain opportunities for intergenerational mobility. At the organizational level, he is interested in documenting and measuring the extent to which culturally-based selection and promotion processes...
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...
I am an undergraduate student studying Data Science with an emphasis in Applied Mathematics & Modeling. I enjoy storytelling through data visuals and learning new visualization tools.
Swetha (she/her) is a 5th Year Master of Information and Data Science student at the School of Information, with experience in Cognitive Science, Psychology research, and product management. Her research interests include building ethical, transparent AI and the impacts of technologies (specifically, mass media, surveillance, and algorithms of bias) on longitudinal behavioral health. She is happy to help with questions on Python, R, SQL, machine learning, neural networks, statistical analysis, and research design!
You have gathered the needed data to support your research, check. You have made some hypotheses about what you hope to conclude, check. You have spent time cleaning the data and organizing it in a manner that permits further exploration, check. You have sliced and diced the data with your favorite data exploration software packages or techniques and created some data visualizations that you feel confident about, quadruple check! You are now armed with insights that you hope to showcase to the world, what’s next? In this article, I would like to share some tips for creating a...
Tiffany Taylor is a doctoral student at the University of California, Berkeley. Previously, she received a Master of Public Health in Epidemiology from Columbia University's Mailman School of Public Health. She graduated from the University of Chicago with majors in Political Science, Sociology, and Comparative Race and Ethnic Studies (Asian American Studies). Some of her research interests include social medicine, educational sociology, and social demography. Additional interests include pilates, yoga, and fashion.
Priscila Amorim is a recent graduate of UC Berkeley's Bachelor's of Arts in Data Science program, and is currently attending Northwestern Univerisity for a Master's of Science in Data Science. Priscila is passionate about the intersection of technology and social justice, and in particular, health justice. Their goal is to work on climate justice through database management or data engineering to support data scientists and analysts in their work through the availability of ubiquitous data. Priscila is currently working on the Changemaker's Digital Health Project to help create...
Daphne is a current 5th-year graduate student at the School of Information with a keen interest in the intersection between healthcare and data science. She has prior work experience in the realm of public health, consulting, and research. Currently, she is a data science research intern at a DC consumer experience startup. She is particularly interested in how data can be used to power insights and help move society towards a more equitable future.
Grazia is a postdoctoral scholar at the Chemical Science Division at Berkeley Lab and a Data Science Fellow at D-Lab. Her research has focused on several different aspects of atmospheric chemistry and she is now interested in data science and machine learning tools applied to atmospheric pollution problems.
