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Predicting the Future: Harnessing the Power of Probabilistic Judgements Through Forecasting Tournaments

April 29, 2025
by Christian Caballero. From the threat of nuclear war to rogue superintelligent AI to future pandemics and climate catastrophes, the world faces risks that are both urgent and deeply uncertain. These risks are where traditional data-driven models fall short—there’s often no historical precedent, no baseline data, and no clear way to simulate a future world. In cases like this, how can we anticipate the future? Forecasting tournaments offer one answer, harnessing the wisdom of crowds to generate probabilistic estimates of uncertain future events. By incentivizing accuracy through structured competition and deliberation, these tournaments have produced aggregate predictions of future events that outperform well-calibrated statistical models and teams of experts. As they continue to develop and expand into more domains, they also raise urgent questions about bias, access, and whose knowledge gets to shape our collective sensemaking of the future.

María Martín López

Data Science Fellow 2023-2024
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...

Nimita Gaggar

Consultant
Public Health

Passionate and driven Public Health graduate student at UC Berkeley with a strong background in program management and a relentless pursuit of excellence. I have 5+ years of experience in program management and operations in the healthcare industry. My academic journey at UC Berkeley has equipped me with a multifaceted skill set, blending strategic thinking, data-driven decision-making, and effective communication. I thrive in fast-paced, dynamic environments and have a proven ability to lead cross-functional teams toward project success.

Gaby May Lagunes

Consultant
ESPM

Hello! I’m Gaby (she/her). I am PhD student at the ESPM department, I hold a masters in Data Science and Information from the Berkeley ISchool and I have 5+ years of industrial experience in different data roles. Before that I got a masters in Engineering for International Development and an undergraduate degree in Physics from University College London. And somewhere between all that I got married, survived the pandemic, and had two awesome boys. I’m very excited to help you use data to enhance your work and your experience here at Berkeley!

Farnam Mohebi

Data Science Fellow 2023-2024, Data Science for Social Justice Senior Fellow 2024
Haas School of Business

I am a PhD student at the Haas School of Business, University of California, Berkeley, and a researcher in the Department of Radiation Oncology at the University of California, San Francisco, having previously earned my MD and MPH degrees. My research focuses on the intersection of professionals and emerging technologies, drawing from the fields of medical sociology, organizational theory, and science and technology studies. I am particularly fascinated by the evolving relationship between physicians and artificial intelligence, the phenomenon of physician influencers, and the social...

Iñigo Parra

Availability: By appointment only

Consulting Areas: Python, R, LaTeX, Data Manipulation and Cleaning, Data Science, Data Visualization, Deep Learning, Digital Humanities, Machine Learning, Natural Language Processing, Social Network Analysis, Regression Analysis, Means Tests, Bash or Command Line, Excel, Gephi, Git or Github, Qualtrics, RStudio, Overleaf

Renee Starowicz, Ph.D.

Data Services Manager, Senior Instructor, Senior Consultant, Co-Executive Director of Berkeley FSRDC
D-Lab
Berkeley Graduate School of Education

Renee Starowicz, Ph.D., has been affiliated with the D-Lab since January 2020 when she joined the NSF IUSE, Undergraduate Data Science at Scale project. Renee’s research interests include Critical Disability Studies, Trauma-skilled inclusive practices and Multimodal Communication Access. At the DLab, Renee is an instructor for STATA FUNdamentals and Introduction to Qualtrics.

How can we use big data from iNaturalist to address important questions in Entomology?

February 26, 2024
by Leah Lee. Large-scale geographic data over time on insect diversity can be used to answer important questions in Entomology. Open-source, open-access citizen science platforms like iNaturalist generate huge amounts of data on species diversity and distribution at accelerating rates. However, unstructured citizen science data contain inherent biases and need to be used with care. One of the efforts to validate big data from iNaturalist is to cross-check with systematically collected data, such as museum specimens.

Social Sciences D-Lab Celebrates a Decade of Innovation and Welcomes New Leadership

December 4, 2023
by Claudia von Vacano, Ph.D. On November 8, 2023, the Social Sciences D-Lab celebrated its 10th anniversary with the introduction of the new faculty director, Demography Professor Dennis Feehan. The event celebrated D-Lab’s accomplishment with the outgoing faculty director Sociology Professor Dave Harding. Social Sciences Dean, Raka Ray, offered warm congratulations to the leadership and staff, underscoring the importance of promoting equity in computational social sciences and the support of qualitative methods research.

Scarlet Bliss, MS

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.