Laura Waller works on computational imaging and microscopy methods for biological, industrial, and commercial applications. She is an associate professor at UC Berkeley in the Department of Electrical Engineering and Computer Sciences (EECS), with affiliations in Bioengineering, QB3, and Applied Sciences & Technology. She was a postdoctoral researcher and lecturer of physics at Princeton University from 2010 to 2012 and received BS, MEng, and PhD degrees from the Massachusetts Institute of Technology in 2004, 2005, and 2010, respectively. She is a Moore Foundation Data-Driven Investigator, Bakar fellow, NSF CAREER awardee, and Packard fellow.
Alvin Cheung is an assistant professor of Electrical Engineering and Computer Science at UC Berkeley. His research interests include all aspects of data management and programming systems. He is also interested in helping non-technical users write code by developing new programming languages, user interfaces, and different modalities. Before joining Berkeley, he was on the faculty at the University of Washington’s school of computer science & engineering, where he was also an faculty affiliate at the eScience Institute. Alvin's research has been recognized through multiple early career awards such as the US Presidential Early Career Award for Scientists and Engineers, the Sloan Fellowship, along with a number of best paper and demo awards.
Alex de Siqueira is a postdoctoral researcher at BIDS, working on open source algorithms for processing computed tomography (CT) 3D images. He received his MS and PhD from the State University of São Paulo, Brazil, applying image processing tools to tackle challenges in materials science and geochronology. A core developer of scikit-image, he is an open source and free software enthusiast since his first contact with Linux, in 2000, contributing to several projects and events in Latin America and Europe. Alex also worked as a postdoctoral fellow at the State University of Campinas, Brazil, and the TU Bergakademie Freiberg, Germany, where he created pytracks and wrote Octave - Your first steps on scientific programming (in Brazilian Portuguese).
Marsha Fenner is the Communications/Program Manager for the Berkeley Institute for Data Science. In this role, she works to connect researchers and data science practitioners across a wide array of academic disciplines, facilitate interdisciplinary collaboration, and implement training and education programs that engage and expand BIDS' and Berkeley’s active and diverse research community. Fenner has managed communications, training/education/outreach programs, and administrative operations for scientific programs and research initiatives at UC Berkeley and Lawrence Berkeley National Laboratory, including the Innovative Genomics Institute, the DOE Joint Genome Institute, and Berkeley Lab's Advanced Light Source. She holds an MA in philosophy and comparative religious studies, and a BA in classics, philosophy and mathematics.
BIDS Senior Fellow Maggi Kelly is Professor and Cooperative Extension Specialist in the Environmental Science, Policy and Management department at UC Berkeley. Her group uses a range of geospatial data and analytics – from spatial modeling, remote sensing, drones, liDAR, historical archives, surveys, participatory mapping, and the field - to gain insights about how and why California landscapes are changing, and what that change means for those who live on, use, and manage our lands. Her work enables interdisciplinary collaboration, data-rich analytics research, and active outreach across a number of scientific domains (forests, agriculture, wetlands, climate change) with significant societal impact. She is faculty director of the Geospatial Innovation Facility and Director of the ANR Statewide Program in Informatics and Geographic Information Systems (IGIS).
David Mongeau, now the Founding Director of the School of Data Science at the University of Texas at San Antonio, was the Executive Director of BIDS from April 2018 to June 2021. During that time, in collaboration with the Faculty Director and Faculty Council, he set strategic direction and oversaw the BIDS research, training, and outreach. He also led the institute’s industry and foundation relations and its engagement with other UC and global research institutes, all toward the overarching mission at BIDS to create and deploy data science methods, practices, and technologies to enable discovery. Previously, David co-led the data analytics institute at Ohio State; worked at Battelle, where he championed its proposal for an AI and cybersecurity company, now Covail; and worked for many years at Bell Labs – starting on the team that introduced the first C++ compiler and UNIX System V and leaving after building a global business and technology consulting practice, now part of Nokia Bell Labs Consulting. David earned his undergraduate degree at Carnegie Mellon University, and later earned a graduate degree at Rensselaer Polytechnic Institute and an MBA from Purdue University. Many of his interests lie beyond data science, embracing the humanities and arts.
BIDS Faculty Affiliate Dani Ushizima is a Staff Scientist in the Machine Learning and Analytics Group in the Computational Research Division at Berkeley Lab, where she leads the Image Processing/Machine Vision team at CAMERA, and an Affiliate Faculty of the Bakar Computational Health Sciences Institute (BCHSI) at the University of California, San Francisco. She also leads the Center for Recognition and Inspection of Cells (CRIC), where her research focuses on imaging cancer cells for early-stage disease diagnosis. With 20 years of research and development experience in Computer Vision, Dani has focused primarily on quantitative microscopy and microstructure classification, from materials science to biomedical imaging.
Maryam Vareth leads BIDS’ data science research efforts in the Health & Life Sciences. Dr. Vareth is a Co-Director of the Innovate For Health initiative, a collaboration among UC Berkeley, UCSF, and Janssen Pharmaceutical Companies of Johnson & Johnson. As an experienced engineer, researcher, and data scientist, she applies mathematics, statistics and physics to solve unmet needs in healthcare to enhance patients’ experience during their medical journey. She is an advocate for “data-driven” medicine, and in particular for linking medical imaging data with medical diagnostics and therapeutics to extract clinically-relevant insights through the use of open research and open source practices. Dr. Vareth received her BS and MS training in Electrical Engineering and Computer Science (EECS) from UC Berkeley, where she was awarded the prestigious Regent’s and Chancellor’s Scholarship. She completed her PhD through the joint UC Berkeley-UCSF Bioengineering program as a National Science Foundation Fellow, where she was awarded the Margaret Hart Surbeck Endowed Fellowship for Interdisciplinary Research for her work on developing new techniques and algorithms for the acquisition, reconstruction and quantitative analysis of Magnetic Resonance Spectroscopy Imaging (MRSI), with the goal of improving its speed, sensitivity and specificity to improve the management of patients with brain tumors. She conducted her post-doctoral fellowship at UCSF, combining structural, physiological and metabolic imaging data from large clinical trials to quantitatively characterize heterogeneity within malignant brain tumors.