Software Output Interpretation

Filtering, Visualizing, and Interpreting Spatial Time Series Data

December 17, 2025
Maksymilian Jasiak
by Maksymilian Jasiak. Spatial time series (consecutive measurements across space and time) are often difficult to interpret, especially when there are many overlapping signals. However, have no fear! Filtering and visualizing can help better interpret and understand the spatial time series data.

Seeing Behavior in Everyday Data

December 10, 2025
Skyler Yumeng Chen
by Skyler Chen. This post discusses how my training in data science changed the way I think about behavioral research. I share how simply exploring everyday datasets and noticing small, unexpected patterns can spark new research questions, and how archival data and experiments each offer distinct yet complementary insights into how people make judgments and decisions. I also highlight the growing set of tools that help us understand behavior in richer ways.

Digitization of Historical Maps in the Age of AI

December 3, 2025
Elena Stacy
by Elena Stacy. Researchers today increasingly have access to a wealth of tools to streamline or automate labor-intensive data processing and generation tasks. When it comes to mapping, progress has been slower. This blog details the author's experience tackling the digitization of a historical map in the age of AI.

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...

Beyond the Hype: How We Built AI Tools That Actually Support Learning

November 12, 2025
Weiying Li
by Weiying Li. What does genuine partnership look like when building AI for education? Working with middle school teachers and computer scientists, we co-designed AI dialogs where teachers are valuable contributors to refine what the AI understands as valuable thinking. Through iterative refinement, teachers identified precursor ideas and observations that predicted future learning, and refined guidance design in the dialog. Our AI dialog sees learning the way teachers do, built through genuine collaboration where both model development, learning sciences theories, and teachers' classroom expertise work together from the start, not just at the end.

Sharazad Ali

Consulting Drop-In Hours: By appointment only

Consulting Areas: Cluster Analysis, Databases and SQL, Data Visualization, Diversity in Data, Excel, Experimental Design, Focus Groups and Interviews, Machine Learning, Means Tests, Python, Qualitative Methods, Qualtrics, R, Regression Analysis, RStudio Cloud, Software Output Interpretation, SQL, Time Series

Quick-tip: the fastest way to speak to a consultant is to first ...

Lance Santana

Consulting Drop-In Hours: By appointment only

Consulting Areas: APIs, ArcGIS Desktop - Online or Pro, Bayesian Methods, Cluster Analysis, Data Visualization, Databases and SQL, Excel, Git or GitHub, Java, Machine Learning, Means Tests, Natural Language Processing (NLP), Python, Qualtrics, R, Regression Analysis, Research Planning, RStudio, Software Output Interpretation, SQL, Survey Design, Survey Sampling, Tableau, Text Analysis

Quick-tip: the fastest way to speak to a consultant is to first ...

Aidan Lee

Consulting Drop-In Hours: By appointment only

Consulting Areas: ArcGIS Desktop - Online or Pro, Bayesian Methods, Causal Inference, Cluster Analysis, Data Sources, Data Visualization, Databases and SQL, Digital Health, Excel, Experimental Design, Geospatial Data: Maps and Spatial Analysis, Git or GitHub, LaTeX, Machine Learning, Means Tests, Mixed Methods, Natural Language Processing (NLP), OCR, Python, Qualtrics, R, Regression Analysis, Research Design, Research Planning, RStudio, RStudio Cloud, SAS, Software Output Interpretation, SPSS, SQL,...

Jonathan Pedroza (JP)

Postdoctoral Scholar
Berkeley School of Education

JP is a postdoctoral scholar in Data Science Education. He received his PhD in Prevention Science from the University of Oregon. His research interests include: examining risk and protective factors of health disparities in Latina/o/x/e populations and investigating educational outcomes in underrepresented student populations. JP uses a social-ecological framework to address his research interests.

Previously, he has served as an adjunct lecturer at Cal Poly Pomona teaching research methods and statistics, as well as a data scientist at the University of Kansas' Accessible Teaching...

Maksymilian Jasiak

Data Science & AI Fellow 2025-2026
Civil and Environmental Engineering

Maksymilian Jasiak is a PhD Student in GeoSystems Engineering at the University of California, Berkeley. His research focuses on Distributed Fiber Optic Sensing (DFOS) for lifeline infrastructure monitoring. His work aims to advance critical infrastructure security and resilience. He holds a MS in GeoSystems Engineering from the University of California, Berkeley and a BS in Civil Engineering from the University of Illinois Urbana-Champaign.