Machine Learning

Need help with Machine Learning?

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Below are the consultant we have available with Machine Learning and other expertise listed.

Enrique Valencia López

Data Science Fellow 2022-2023
Graduate School of Education

Enrique Valencia López is a PhD student in the Policy, Politics and Leadership cluster at the Graduate School of Education.His research interests relate to three broad areas: the stratification of education by gender, immigration status and ethnicity; the measurement of teacher working conditions and well-being; and education in Latin America.

Before coming to Berkeley, Enrique worked for Mexico’s National Institute for Educational Evaluation and Assessment (INEE) in both the Policy and Indicators area. During that time, he co-authored Mexico’s first report on the educational...

Ruiji Sun

Data Science Fellow 2024-2025
Center for the Built Environment

Ruiji Sun is currently a Ph.D. candidate in Building Science at UC Berkeley. He is also a GSR at the Center for the Built Environment (CBE). His dissertation focuses on causal inference in the built environment. Other areas of his research include indoor environmental quality, personalized environmental control systems, and building energy modeling.

He obtained his M.S. degree from Carnegie Mellon University and double-majored in Mechanical Engineering (HVAC) and Architecture at Xi’an University of Architecture and Technology, China. Ruiji also served as a board...

Nanqin Ying

Data Science Fellow 2024-2025
Goldman School of Public Policy

Nanqin Ying, a second-year graduate student at the Goldman School of Public Policy specializing in Development Practices, combines a robust nonprofit background with advanced data science techniques. She focuses on leveraging machine learning and big data to drive significant social change, aiming to transform insights into actionable, positive impacts on communities.

Jaewon Saw

Data Science Fellow 2024-2025
Civil and Enviromental Engineering

I am a PhD candidate in Systems Engineering. My current research focuses on distributed acoustic sensing (DAS), a cutting-edge technology with diverse applications. I have used DAS to detect whale vocalizations in Monterey Bay, California, and to monitor roadways, water pipelines, and energy infrastructure.

I enjoy identifying and mitigating challenges that arise when applying new technologies by developing data tools, pipelines, and frameworks for real-world deployments. My work is driven by a keen interest in exploring and refining innovative...

Sharing Just Enough: The Magic Behind Gaining Privacy while Preserving Utility

April 15, 2025
Sohail Khan
by Sohail Khan. Netflix knows what you like, but does it need to know your politics too? We often face a frustrating choice: share our data and be tracked, or protect our privacy and lose personalization. But what if there was a third option? This article begins by introducing the concept of the privacy-utility trade-off, then explores the methods behind strategic data distortion, a technique that lets you subtly tweak your data to block sensitive inferences (like political views) while still maintaining useful recommendations. Finally, it looks ahead and advocates for a future where users, not platforms, shape the rules, reclaiming control of their own privacy.

Suraj Nair

Data Science Fellow 2023-2024
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 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...

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.

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.

Sanjana Gajendran

Consultant
MIMS

I'm a second year MIMS Student with a focus on Data Science and Natural Language Processing. During the Summer 2023, I interned at Genentech as a Data Science Intern.