Machine Learning

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

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.

Nikita Samarin

Data Science Fellow 2021-2022
Electrical Engineering and Computer Science (EECS)

Nikita Samarin is a doctoral student in Computer Science in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley advised by Serge Egelman and David Wagner. His research focuses on computer security and privacy from an interdisciplinary perspective, combining approaches from human-computer interaction, behavioral sciences, and legal studies. Samarin is a member of the Berkeley Lab for Usable and Experimental Security (BLUES) and an affiliated graduate researcher at the Center for Long-Term Cybersecurity (CLTC) and the...

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...

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...

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...

Bruno Smaniotto

Data Science Fellow 2024-2025
Economics

I'm originally from Brazil, but I have been living in Berkeley for the last 5 years working towards my PhD in Economics. My main areas of interest are Behavioral and Macroeconomics, mostly their intersection, but I'm excited about learning and working on empirical applications on different fields.

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.