Geospatial Data, Maps & Spatial Analysis

Deibi Sibrian

Data Science for Social Justice Fellow 2024
Deibi is a Ph.D. student in the Department of Environmental Science, Policy, and Management, centering critical interdisciplinary ecology and multispecies justice. Deibi coined the term "Cryptonocene," an interdisciplinary framework, to study the socio-environmental health impacts of cryptocurrencies and related technologies, such as AI. With over two years of experience as a graduate instructor, Deibi now is a Graduate Student Researcher, NSF Digital Transformation Fellow, and Mentored Research Fellow. Before joining Berkeley, Deibi was the project manager for an interdisciplinary team...

Scarlet Sands-Bliss

Data Science & AI Fellow 2025-2026, Domain Consultant, Research IT
School of Public Health

Scarlet Bliss is an MS/PhD student in Epidemiology in the School of Public Health. Her work focuses on mixed methods approaches to characterizing and preventing spread of antimicrobial resistance and other enteric pathogens via the environment. She has experience in statistical analysis and public health bioinformatics. She is interested in ethical use of big data as it relates to epidemiologic research.

Armaan Hiranandani

Data Science & AI Fellow 2025-2026
School of Information

Armaan Hiranandani is a Master’s student in Data Science at UC Berkeley, where he also earned his B.S. in Industrial Engineering & Operations Research. Born and raised in Dubai, Armaan recently completed a software engineering internship at Netflix, working on the machine learning platform team. His interests include building scalable AI systems and applying data science to solve real-world problems.

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.

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...

A Participant-Centered, GIS-Based Approach to Improving Contextual Measurement

November 19, 2025
Sarah Daniel
by Sarah Daniel. Researchers increasingly recognize that neighborhoods profoundly shape life outcomes, yet measuring them remains challenging. A common approach uses administrative boundaries, such as census tracts, as proxies for neighborhoods, but this method presents three key challenges. First, administrative boundaries may fail to capture residents’ lived experiences, a limitation that is particularly concerning in marginalized communities; second, they can misrepresent contextual effects; and third, they may produce inconsistent findings. To address these issues, I advocate for the use of self-defined neighborhood boundaries as an alternative measure. I compare GIS- and non-GIS-based methods and propose that GIS-based methods offer the strongest potential for more valid measurement.

John Cherry

Consulting Drop-In Hours: By appointment only

Consulting Areas: ArcGIS Desktop - Online or Pro, Cluster Analysis, Data Sources, Data Visualization, Excel, Geospatial Data: Maps and Spatial Analysis, GIS (ArcGIS Pro, QGIS); spatial data analysis and visualization, Google Earth Engine, Mixed Methods, Public health data analysis; infectious disease mapping; rural and global health applications of GIS, Experimental Design, Spatial Statistics, Survey Sampling

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

Evan Kartheiser

Consulting Drop-In Hours: By appointment only

Consulting Areas: ArcGIS Desktop - Online or Pro, Data Visualization, Geospatial Data: Maps and Spatial Analysis, Git or GitHub, Google Earth Engine, HTML / CSS, Javascript, Python, QGIS, R, Regression Analysis, SQL, Spatial Statistics, Tableau, Time Series

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,...