Software Tools

Decision-Making Under Pressure during My PhD: Lessons from whale songs and ocean noise

May 6, 2025
Jaewon Saw
by Jaewon Saw. This blog post shares a story from a field experiment using Distributed Acoustic Sensing (DAS) to detect whale vocalizations in Monterey Bay. Most of the data got overwhelmed by noise from boat engines, wave motion, and cable instability. On the final day, a spur-of-the-moment decision to add loops to the fiber optic cable dramatically improved signal quality.

Sahiba Chopra

Data Science Fellow 2024-2025
Haas School of Business

I'm a PhD student in the Management and Organizations (Macro) group at Berkeley Haas. I have a diverse professional background, primarily as a data scientist across numerous industries, including fintech, cleantech, and media. I hold a BA in Economics from the University of Maryland, an MS in Applied Economics from the University of San Francisco, and an MS in Business Administration from UC Berkeley.

My research focuses on the intersection of inequality, technology, and the labor market. I am particularly interested in understanding how to reduce inequality in...

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.

Demystifying AI

May 5, 2025, 2:30pm
In this workshop, we provide a basic and relatively non-technical introduction to the foundational concepts underlying contemporary AI tools. First, we’ll cover the the fundamentals of AI, Machine Learning, and Neural Networks/Deep Learning. Then, we’ll examine the capabilities and limitations of contemporary AI tools such as ChatGPT, Claude, and Perplexity, and outline best practices for the use of such tools.

Git Fundamentals

May 8, 2025, 10:00am
This introductory workshop covers basics of Git using command line(Bash). We will cover key concepts and workflows, including version control, repository creation, branching, merging, and collaboration. You'll gain hands-on experience navigating Git, managing repositories, and contributing to projects, making it easier to streamline your work and collaborate with others.

MAXQDA Fundamentals Departmental (90m)

April 14, 2025, 12:30pm
This 90-minute introductory workshop will teach you MaxQDA from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the MaxQDA software, upload multiple forms of data then how to use manual and autocode features. We will review some of the additional analytic features including visual, memo and the Questions, Themes and Theories (QTT) tools. We will briefly touch on the MaxQDA Team cloud-based version. Instructors will share recommended resources.

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 Deep Learning

March 4, 2025, 2:00pm
In this workshop, we will convey the basics of deep learning in Python using keras on image datasets. You will gain a conceptual grasp of deep learning, work with example code that they can modify, and learn about resources for further study.

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...

Thomas Lai

Consultant
School of Information

I am a Product Engineer passionate about applying engineering, data science, machine learning, and problem-solving principles to improve device performance and solve complex challenges. With experience in statistical analysis, lab bench automation, and Python scripting, I have developed a strong technical skill set that allows me to make meaningful contributions to any project. Beyond my work, I am also passionate about exploring new topics and ideas, from the latest technology trends to how to improve the overall well-being of humans. I enjoy applying the first principle to any...