I am a PhD Student at the School of Information. My research interests lie at the intersection of development economics and machine learning, with a focus on the use of large scale digital data and new computational tools to study pressing issues in global development.
I am a PhD student in the Astronomy department, and I study planets outside our own solar system. I'm interested in learning how the properties of host stars affect planetary systems. In my free time, I love swimming, hiking, reading, and baking.
Leïla Njee Bugha is a 5th year PhD candidate in the Agriculture and Resources Economics department. She studied at the École Normale Supérieure de Paris-Saclay and at Sciences Po Paris in France, before starting a career in the field of program evaluation of public policies. Most recently, she worked as a Research Analyst at the International Food Policy Research Institute in Washington, DC, evaluating childhood nutrition and social protection programs in West Africa. As a PhD student, she specializes in development and labor economics, with a focus on understanding the barriers to...
I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.
Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law
Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.
Alex is a PhD Candidate in materials science and engineering developing image processing and machine learning techniques for extracting information from electron microscopy datasets. Her primary focus is understanding what information is transferred from various feature representations of images. She has extensive experience collaborating across boundaries and is passionate about brainstorming innovative approaches to challenging data science problems!
I'm Abhishek Roy and I'm double majoring in Economics and Data Science. I've been a part of D-Lab's IUSE project since Spring 2020 and have truly found an organization that is not only passionate about Data Science but also strives to expand its reach equitably to all communities. I am involved in Research and Project Management roles in various departments and labs at Berkeley and I'm an Editor at the Berkeley Economic Review. I love diving into anything at the intersection of Data Science, Economics, Business, and Computational Social Science. Whenever I'm free, I love writing...
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...
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!
Doctoral student in Rachel Morello-Frosch's laboratory in the Department of Environmental Science, Policy, and Management working at the intersection of environmental epidemiology, environmental justice, and causal inference. Particularly interested in developing quantitative methods to investigate the operation of social power in environmental monitoring regimes in the United States.