ImageXD 2023
ImageXD was held on March 16-17, 2023 at the National Academies Beckman Center in Irvine, CA
ADSA and BIDS co-hosted the sixth annual ImageXD on March 16-17, 2023, bringing together researchers, scientists, and theorists who work with images as a primary source of data, to learn about the latest developments in a variety of fields and to promote interdisciplinary collaboration. The small gathering (<50 people) featured talks, discussions, and time to work in groups to collaborate - either coding or planning for research and funding.
Missed out on ImageXD 2023?
Check out this blog post for a recap of ImageXD 2023!
Speakers

Sara Beery will join MIT as an assistant professor in the Faculty of Artificial Intelligence and Decision-Making in EECS in September 2023 and is currently a visiting researcher at Google working on urban tree mapping across North America. She received her PhD in computing and mathematical sciences at Caltech in 2022, where she was advised by Pietro Perona. Her research focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities, tackling real-world challenges including strong spatiotemporal correlations, imperfect data quality, fine-grained categories, and long-tailed distributions. She partners with nongovernmental organizations and government agencies to deploy her methods in the wild worldwide and works toward increasing the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity building and education.

Wei-Lun (Harry) Chao
Wei-Lun (Harry) Chao is an assistant professor in the Department of Computer Science and Engineering (CSE) at the Ohio State University (OSU). His research interests are in machine learning and its applications to computer vision, autonomous driving, natural language processing, and health care. His recent work focuses on vision recognition in the wild, robust 2D/3D perception, and learning with imperfect data. His research is funded by NSF, ONR, Cisco, AWS, etc. He is a member of the NSF Imageomics Institute and NSF ICICLE Institute. He has published more than 30 peer-review papers in first-tier venues, including CVPR, NeurIPS, ICLR, etc. Prior to joining OSU, he was a postdoctoral associate at Cornell. He received his Ph.D. degree in computer science at the University of Southern California in 2018.

Dr. Dan Chitwood
Dan Chitwood is an Assistant Professor at Michigan State University in the Departments of Horticulture and Computational Mathematics, Science & Engineering. A plant biologist by training, he studies plant morphology and computational approaches to quantify shape. He uses Topological Data Analysis (TDA), a mathematical field that treats shapes as data (and data as shape), to comprehensively extract shape information from leaf shapes, X-ray Computed Tomography reconstructions, and more abstract data types, like gene expression and protein structure. He has also developed Plants&Python, a free, publicly available, interdisciplinary, intercultural, and multilingual coding resource to bridge computational and plant science research across the US and México.

Kira Evans
Kira is a Napari core developer and a scikit-image contributor with a passion for increasing accessibility to open source software and multi-dimensional image viewing, processing, and analysis tools. She has been dedicated to topics related to fundamentals in program design and machine learning, computer vision, human-computer interaction, and web design. The past 4 years, she has worked as a Software Engineer for the Chan Zuckerberg Initiative, and she has also served on the Scientific Python Ecosystem Coordination steering committee.Kira Evans is a napari core developer and a scikit-image contributor with a passion for increasing accessibility to open source software and tools. She serves on the Scientific Python Ecosystem Coordination steering committee.

Dr. Catherine Nakalembe
Dr. Catherine Nakalembe is an Assistant Professor at the University of Maryland’s Department of Geographical Sciences. Her research focuses on developing remote sensing and machine learning applications for smallholder agriculture, early warning of food insecurity, and disaster assessment in Africa. She is the Africa Program Director for NASA Harvest and a NASA SERVIR Applied Sciences team member. Most recently, she has received the 2022 Highest Civilian Award: The Golden Jubilee Medal-Civilians of Uganda and the 2020 Africa Food Prize for her dedication to improving food security in Africa through the enhanced use of Earth observation.

Dr. Sharmila Majumdar
Sharmila Majumdar is a UCSF Professor and is the Vice Chair for Research and Margaret Hart Surbeck Distinguished Professor in Advanced Imaging in the Departments of Radiology and Biomedical Imaging, and joint appointments in Bioengineering and Therapeutic Sciences, Orthopedic Surgery at UCSF. She is executive and Scientific Director of the center for Intelligent Imaging, and Director of the Musculoskeletal Research Interest Group at UCSF, an interdisciplinary group consisting of faculty, post-doctoral scholars and students. Her research work on imaging, particularly magnetic resonance and micro computed tomography, and development of image processing and analysis tools, has been focused in the areas of osteoporosis, osteo-arthritis and lower back pain. Her research, which is supported by grants from the NIH and corporate entities, and is diverse ranging from technical development to clinical trials.

Stéfan van der Walt
Stéfan van der Walt is a researcher at the University of California, Berkeley, the founder of scikit-image, and co-author of "Elegant SciPy: The Art of Scientific Python". Stéfan has been developing scientific open-source software for more than fifteen years, and is a community leader of the Scientific Python project. He serves as a director of NumFOCUS, and on the steering committees of NumPy, SciPy, and the PSF's Scientific Working Group.
More about ImageXD
Incredible advances are being made in image processing techniques and tools, but the researchers who use them typically don’t have the opportunity to communicate with others who work on similar problems in different domains. ImageXD was founded by University of California, Berkeley and University of Washington partners from the Moore-Sloan Data Science Environments (MSDSE) to address these challenges.
At the inaugural ImageXD event, held at UC Berkeley’s Institute for Data Science (BIDS) on June 7-9, 2016, we gathered 50 researchers from 14 institutions representing expertise in computer vision, microscopy, materials imaging, photography, earth science, neuroscience, astronomy, software development, and more.
The common bond between all of these researchers coming from different domains is that they work with images as a primary source of data. Throughout the event, we learned from one another while strengthening ties across disciplinary boundaries and began the development of collaborations that we hope will have a lasting impact on the image processing community.

Attendees of the inaugural ImageXD at UC Berkeley in 2016
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ImageXD 2023 Planning Committee

Daniela Ushizima
Lawrence Berkeley National Laboratory

Cierra Martinez
UC Berkeley

Ashish Sahni
UC Berkeley

Micaela Parker
Academic Data Science Alliance

Mayram Vareth
UC Berkeley; University of San Francisco
