Team

The IDEAL team investigates computational approaches based on machine learning to interface data-driven models to materials characterization. Our expertise in computer vision has been applied to multimodal imaging for measuring 2D and 3D structure across spatial scales, which is key to advance research and design of new materials imaged using instruments reliant on x-ray, electron, confocal, and other light-matter interactions. Our current focus is on applications such as lithium metal batteries, biofuel, and plant-microbe-environment interactions.

Dani Ushizima

Ph.D. - Principal Investigator

Computer scientist focused on empowering labs to make decisions through Computer Vision and Machine Learning, a researcher with 20+ years of experience in performing data analysis, focused on energy and biomedical research projects. Awarded Latina in Science in 2021. DOE Early Career Awardee [more].

Marcus Noack

Ph.D. - Research Scientist at LBL

Mathematician leading autonomous experiments at CAMERA, collaborating on the modeling of scientific problems dependent on Gaussian Processes. Main Architect of gpCAM [more].

Iryna Zenyuk

Ph.D. - Affiliate Scientist at LBL

Associate Director, National Fuel Cell Research Center; Associate Professor at Chemical and Biomolecular Engineering w/ Joint Appointment at Mechanical and Aerospace Engineering. Renewable energy, fuel cells, electrolyzers, batteries, X-ray imaging techniques, multi-scale modeling, transport phenomena. [more]

Eric Chagnon

M.Sc. - UC Davis

Using Statistics to built Natural Language Processing (NLP) pipelines that include advanced language models to understand scientific text. Interests include analytics and transformers. [more]

Ying Huang

Ph.D. - UC Irvine

Renewable energy, fuel cells, electrolyzers, solid state batteries, X-ray imaging, battery modeling, transport phenomena. [more]

Jerome Quenum

Ph.D. Candidate - UC Berkeley

Investigating algorithms in signal processing, computer vision, and machine learning applied to scientific data. Expert in automated logistics. Awarded a National Defense Science and Engineering Gratuate Fellowship (NDSEG) and the LBNL Bridges Fellow. [more]

Silvia miramontes

Ph.D. Candidate - UC San Francisco

Mathematician discovering new models for representation and quantification of biomedical images. Inventor of Gredient, the first computer vision-based app for automated food label reading, interpretation and allergy warning.

Ke Xu

Ph.D. Candidate - UC Berkeley

Exploring X-ray imaging to understand new concrete design for advanced Civil Engineering, including studies of archeological concrete.

Zineb Sordo

M.Sc. candidate - UC Davis

Statistics and data science, Machine Learning, Algorithm Design and Analysis, Big Data and High Perf Stat Computing, Linear Regression, Time Series Analysis, Optimization for big data analysis..

KatE Johnson

Under-Graduate Intern (SULI) - UC Davis

Statistician working on investigations involving scientific data and machine learning. Segmentation and classification workflows [more].

Alumni

This site contains an ever-growing list of collaborators that are essential to the progress of several of our projects. If you believe your name should be included here, please contact.