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.

Aniket Kesari, Ph.D.

Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law

Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.

Featured D-Lab Blog Post: Introducing “A Three-Step Guide to Training Computational Social Science Ph.D. Students for...

Alex Bruefach

Discovery Graduate Fellow
Materials Science and Engineering

Alex is a PhD Candidate in materials science and engineering developing image processing and machine learning techniques for extracting information from electron microscopy datasets. Her primary focus is understanding what information is transferred from various feature representations of images. She has extensive experience collaborating across boundaries and is passionate about brainstorming innovative approaches to challenging data science problems!

Christopher Paciorek, Ph.D.

Research Computing Consultant, Adjunct Professor
Department of Statistics
Research IT

Chris Paciorek is an adjunct professor in the Department of Statistics, as well as the Statistical Computing Consultant in the Department's Statistical Computing Facility (SCF) and in the Econometrics Laboratory (EML) of the Economics Department. He is also a user support consultant for Berkeley Research Computing. He teaches and presents workshops on statistical computing topics, with a focus on R.

Erin Manalo-Pedro

Research Fellow
Community Health Sciences (UCLA)

Erin Manalo-Pedro is a Ph.D. student in the Department of Community Health Sciences at the UCLA Fielding School of Public Health with a minor in education. She focuses her racial health equity research on curriculum, the health workforce, and political interventions for communities of color. Drawing from Public Health Critical Race Praxis and Pinayism, she aims to use methods, like natural language processing and counter storytelling, to document the subtleties of structural racism and resistance from marginalized groups.

To guide her interdisciplinary approach, Erin leverages...

Swetha Pola

Research Fellow
School of Information

Swetha (she/her) is a 5th Year Master of Information and Data Science student at the School of Information, with experience in Cognitive Science, Psychology research, and product management. Her research interests include building ethical, transparent AI and the impacts of technologies (specifically, mass media, surveillance, and algorithms of bias) on longitudinal behavioral health. She is happy to help with questions on Python, R, SQL, machine learning, neural networks, statistical analysis, and research design!

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What is MLOps? An Introduction to the World of Machine Learning Operations

May 10, 2022
Sam Temlock
More than ever, AI and machine learning (ML) are integral parts of our lives and are tightly coupled with the majority of the products we use on a daily basis. We use AI/ML in almost everything we can think of, from advertising to social media and just going about our daily lives! With the prevalent use of these tools and models, it is essential that, as IT systems and software became a disciplined practice in terms of development, maintainability, and reliability in the early 2000s, ML systems follow a similar trend. The field focused on developing such practices is currently loosely defined under many different titles (e.g., machine learning engineering, applied data science), but is most commonly known as MLOps, or Machine Learning Operations.

Spencer Le

Data Peer Consultant, UTech
Computer Science
Data Science

I am a senior majoring in Computer Science and minoring in Data Science. I love crunching down big data and analyzing it in order to help solve real-life issues. In my free time, I like jamming out to music, drawing, studying history, and posting on my foodstagram. If you have any questions regarding Computer Science or Data Science, please stop by!

Lia Chin-Purcell

Consultant
School of Information

Hello! I am a first-year Masters's student at the School of Information in the MIMS program with a focus is in data science and ethics. Before joining Berkeley, I studied computer science at the University of Puget Sound.

Ash Tan

Consultant
School of Information

Ash is a Masters of Information and Data Science student at the Berkeley School of Information. He currently studies data collection, analysis, and visualization, as well as research design and machine learning techniques. His interests include cognitive science, Wikipedia data, and privacy research.

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Jordan Weiss, Ph.D.

Data Science Fellow
Demography

Jordan Weiss is a demographer who studies population health and inequality. A central theme of his work concerns the integration of theories across multiple disciplines with advances in statistical and computational science to inform research design and translate findings into actionable, policy-relevant information.

Jordan earned his Ph.D. in Demography and Sociology from the University of Pennsylvania where he also earned an MA in Statistics. He is currently a Postdoctoral Scholar in the Department of Demography and Data Science Fellow at the University of California,...