Python

Emma Turtelboom

Data Science Fellow 2023-2024
Astronomy

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.

Melike Sümertaş

Data Science Fellow
History

I hold a PhD in History from Boğaziçi University, Istanbul and B.A and M.A degrees from Middle East Technical University in Ankara, Department of Architecture, and Program in Architectural History. My research focuses on the urban/architectural/visual culture of the late Ottoman Empire and its capital city Istanbul, with a particular interest in the Greek-Orthodox community. My current project in the History Department of UC Berkeley under the umbrella of the Istanpolis collaboration led by Prof. Christine Philliou, focuses on utilizing digital humanities tools for urban/...

Leïla Njee Bugha

Data Science Fellow
Agricultural and Resource Economics

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...

Suraj Nair

Data Science Fellow
School of Information

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.

María Martín López

Data Science Fellow
Psychology

María Martín López is a PhD student in the Cognition area within the Department of Psychology. Her research relates to cognitive computational and quantitative models of individual differences in behaviors, thoughts, and emotions. She is particularly interested in how we can create and leverage novel algorithms to understand, measure, and predict processes relating to externalizing psychopathology (e.g. impulsivity, aggression, substance use). She answers these questions using a range of computational and quantitive models including AI, NLP, SEM, time series analysis, multi-level...

Measuring Vowels Without Relying on Sex-Based Assumptions

April 8, 2025
Amber Galvano
by Amber Galvano. This tutorial builds on my previous post on Python for acoustic analysis, this time focusing on measuring vocal tract resonances without relying on sex-based assumptions. I demonstrate how to process audio files and vowel annotations using an adaptive method that optimizes the acoustic analysis across a recording. Instead of fixing parameters based on generalized vocal tract length correlations, this approach varies them within a defined range for greater accuracy. This not only enhances measurement precision but also avoids requiring (or assuming) speakers’ sex in data collection. Finally, I show how to filter for outliers and create high-quality vowel space visualizations.

Python Data Visualization: Parts 1-2

April 7, 2025, 8:00am
For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook.

Python GPT Fundamentals

March 4, 2025, 10:00am
This workshop offers a general introduction to the GPT (Generative Pretrained Transformers) model. No technical background is required. We will explore the transformer architecture upon which GPT models are built, how transformer models encode natural language into embeddings, and how GPT predicts text.

Python Fundamentals: Parts 1-4

May 5, 2025, 12:00pm
This four-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Lauren Chambers

Consultant
School of Information

Lauren Chambers is a Ph.D. student at the Berkeley School of Information, where she studies the intersection of data, technology, and sociopolitical advocacy with Prof. Deirdre Mulligan. Previously Lauren was the staff technologist at the ACLU of Massachusetts, where she explored government data in order to inform citizens and lawmakers about the effects of legislation and political leadership on our civil liberties. Lauren received her Bachelor's from Yale in 2017, where she double-majored in astrophysics and African American studies, and she spent two years after graduation in...