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Our Research

AI for Science and Health

ICSI advances artificial intelligence techniques to enhance scientific inquiry and spur groundbreaking innovations in a wide range of areas, from high-energy physics to smart medical devices.

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Accelerating discovery and impact with advanced AI for science and health

AI is an incredibly powerful tool to speed the scientific process. ICSI brings experts in computer science, machine learning, and artificial intelligence together with domain scientists and practitioners to solve problems and spark scientific discovery. Our research helps to enhance the reliability of scientific datasets and workflows, underpins innovations that add value for industry, and makes medical technologies better and safer for patients.

Projects & Initiatives

Projects

AI for High-Energy Physics

We speed the deployment and efficiency of AI models in high-energy physics by embedding physics knowledge into the machine learning process.

Projects

AI Algorithms for Science at the Edge

We accelerate scientific discovery by bringing intelligent ML-based data reduction and processing as close as possible to the data source.

Projects

Paving the Way for Next-Gen Scientific Software

We are creating tools to simplify the transition to next-generation scientific software infrastructure.

Projects

Robust Deep Learning for Threat Detection

We aim to make deep learning models more trustworthy and useful for scientific applications involving complex and dynamic data.

Projects

Advancing Topological Data Analysis

We are developing software for computing generalized persistence diagrams to advance topological data analysis applications by correlating multiple measurements.

Projects

Envisioning Research Impacts

We are developing an organizational structure for envisioning which areas of R&D are poised to generate beneficial innovations in computer and information science and engineering.

Our Experts

Our experts conduct visionary research, mentor and collaborate with our fellows and visitors, and are frequently invited to serve as keynote speakers and panelists. In addition, ICSI experts are available for technical and strategy consulting, allowing you to apply ICSI brainpower to your organization’s most pressing challenges across many areas of machine learning, artificial intelligence, and domain science applications.

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Nadine Alameh

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Nadine Alameh, PhD, is a Senior Fellow at ICSI and an industry-recognized leader in geospatial technologies.

Ben Erichson

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Ben Erichson, PhD, is a Senior Research Scientist and Group Lead for Deep Learning at ICSI and Research Scientist at Lawrence Berkeley National Laboratory.

Maria Franz

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Maria Franz, PhD, is an ICSI-DAAD IFI Postdoctoral Researcher.

Jack Gallant

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Jack Gallant, PhD, is a Research Mentor at ICSI and Professor in the Department of Neuroscience at UC Berkeley.

Amir Gholaminejad

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Amir Gholaminejad (Gholami), PhD, is a Research Affiliate at ICSI and an Associate Research Scientist at the Berkeley Artificial Intelligence Research and Sky Computing Labs at UC Berkeley.

Katherine Kim

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Katherine Kim, PhD, is a Research Mentor at ICSI, Adjunct Professor at UC Davis, Senior Scientist at CITRIS/UC Berkeley, and Founder and CEO of Health Tequity.

Chunlei Liu

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Chunlei Liu, PhD, is a Research Mentor at ICSI and a Professor in the Department of Electrical Engineering and Computer Sciences and the Helen Wills Neuroscience Institute at UC Berkeley.

Michael Mahoney

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Michael W. Mahoney, PhD, is Vice President, Principal Scientist, and Group Lead for the AI and Big Data group at ICSI.

Héctor García Martín

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Héctor García Martín, PhD, is a Research Affiliate at ICSI, Director of Data Science and Modeling at the Biofuels and Bioproducts Division at the Joint BioEnergy Institute, and Staff Scientist at Lawrence Berkeley National Laboratory.

Nori Nakata

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Nori Nakata, PhD, is a Research Affiliate and Research Mentor at ICSI, Principal Research Scientist at MIT, and Staff Scientist at Lawrence Berkeley National Laboratory.

Rie Nakata

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Rie Nakata (Kamei), PhD, is a Research Scientist at ICSI and Research Scientist at Lawrence Berkeley National Laboratory.

Malcolm Slaney

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Malcolm Slaney, PhD, is a Research Affiliate at ICSI, Adjunct Professor at Stanford University, and an Affiliate Professor at the University of Washington.

Timothy Stryker

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Timothy Stryker is a Non-Resident Senior Fellow at ICSI and Principal of Hudson Passage, LLC.

Charuleka Varadharajan

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Charuleka Varadharajan, PhD, is a Research Affiliate at ICSI, Staff Scientist at Lawrence Berkeley National Laboratory, and Research Affiliate at the Berkeley Institute for Data Science at UC Berkeley.

Maryam Vareth

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Maryam Vareth, PhD, is a Research Mentor at ICSI and Chief Health Technology Officer at the Berkeley Institute for Data Science (BIDS) at UC Berkeley.

John Wilbanks

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John Wilbanks is a Non-Resident Senior Fellow at ICSI.

John Wu

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Kesheng (John) Wu, PhD, is a Research Affiliate and Research Mentor at ICSI and Senior Computer Scientist at Lawrence Berkeley National Laboratory.

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ICSI offers the best of all worlds—a place to do transformative work without unnecessary bureaucracy. With no teaching obligations, minimal red tape, and flexible employment models, you’re free to do your best work, your way. 

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ICSI is a global research community that feels like home. A visit to ICSI puts you at the center of the action to collaborate with top researchers in a world-class innovation ecosystem. 

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Want to discuss opportunities to work with ICSI? We’d love to hear from you.

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We’re always looking for researchers, visitors, and collaborators. Explore all the benefits of joining our inclusive, interdisciplinary, impacts-oriented team.

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Apply ICSI brainpower to your organization’s most pressing challenges with our technical and strategy consulting services. Or, use our modern office space for workshops and meetings.

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