Git or Github

Grace Hu

Data Science for Social Justice Fellow 2024
Bioengineering

Grace is a 3rd year Bioengineering PhD candidate in the joint UC Berkeley-UCSF Graduate Program. Her research lies at the nexus of computational design and 3D-bioprinting to advance tissue engineering for regenerative medicine. She previously studied Materials Science and Engineering (B.S.) and Computer Science (M.S.) at Stanford University, where she investigated printable batteries to power an ultra-affordable scanning electron microscope and explored computer science education research by developing AI models to augment teaching ability.

In her free time she...

Tracy Burnett

Data Science for Social Justice Fellow 2024
Department of Environmental Science, Policy, and Management

Tracy uses qualitative methods founded in complexity theory and hierarchy theory to model the interlinked scales of coupled social-ecological systems. She conducted the majority of her research among nomads in Amdo, Tibet. She works to develop both theoretical and technological tools that support linguistic diversity and cultural resilience.

Hugh Kadhem

Mathematics

Hugh Kadhem is a Ph.D. student in Applied Mathematics, with broad research interests in computational quantum physics and high-performance scientific computing.

Git for Research Transparency and Reproducibility Training (RT2)

June 6, 2024, 3:15pm
This is a custom Git workshop for the 2024 Research Transparency and Reproducibility Training (RT2).

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

Can Machine Learning Models Predict Reality TV Winners? The Case of Survivor

March 14, 2023
by Kelly Quinn. Reality television shows are notorious for tipping the scales to favor certain players they want to see win, but could producers also be spoiling the results in the process? Drawing on data about Survivor, I attempt to predict the likelihood of a contestant making it far into the game based on editing and production decisions, as well as demographic information. This post describes the model used to classify player outcomes and other potential ways to leverage data about reality TV shows for prediction.

James Hall

Consultant
Department of Statistics

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,...

Aniket Gupta

Discovery Fellow
School of Information

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.

Shivani Patel

IUSE Undergraduate Advisory Board
Cognitive Science
Data Science

Hi! I’m a third-year at UC Berkeley studying Cognitive Science and minoring in Data Science. I will be pursuing a Doctorate of Physical Therapy with an emphasis in Sports Medicine but will be using my Data Science education as a way to enhance the field. I like learning about business models, impacted industries, and approaches to solving major problems in our world/communities.

Reubén Pérez

Consultant
Sociology

Reubén Pérez is a Ph.D. student in the Department of Sociology at UC Berkeley, where his research focuses on the politics of ethnoracial data production in the context of Latin America and the Caribbean.