Our Vision
This workshop aims to address the challenges of applying advanced computer vision techniques to small datasets involving infants and animals. CV4Smalls workshop is an attempt to foster a comprehensive discussion on data efficiency, exploring novel strategies to achieve high-performing machine learning models with minimal data, a critical requirement in fields such as healthcare and animal behavior research.
By homing in on Small Data, the workshop seeks to promote inclusivity and fairness in AI applications, highlighting the importance of these considerations in the current era of data-driven technology.
Keynote Speaker:
Dr. Michael Black
Dr. Michael Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. from Yale University (1992). After post-doctoral research at the University of Toronto, he worked at Xerox PARC as a member of research staff and area manager. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is an Honorarprofessor at the University of Tuebingen and one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director.. He was also a Distinguished Amazon Scholar (VP, 2017-2021). His work has won several awards including the IEEE Computer Society Outstanding Paper Award (1991), Honorable Mention for the Marr Prize (1999 and 2005), and all three major test-of-time awards including the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017. Black is a co-founder and Chief Scientist of Meshcapade GmbH.
Dr. Sara Beery
Dr. Sara Beery is an assistant professor in the MIT Faculty of Artificial Intelligence and Decision-Making. She was previously a visiting researcher at Google, working on large-scale urban forest monitoring as part of the Auto Arborist project. She received her PhD in Computing and Mathematical Sciences at Caltech in 2022, where she was advised by Pietro Perona and awarded the Amori Doctoral Prize for her thesis. Her research focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities, tackling real-world challenges including geospatial and temporal domain shift, learning from imperfect data, fine-grained categories, and long-tailed distributions. She partners with industry, nongovernmental organizations, and government agencies to deploy her methods in the wild worldwide. She works toward increasing the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity building and education, and has founded the AI for Conservation slack community, serves as the Biodiversity Community Lead for Climate Change AI, and founded and directs the Summer Workshop on Computer Vision Methods for Ecology.
Our Organizing Team
Sarah Ostadabbas, General Chair
Northeastern University
Sarah Ostadabbas is an associate professor in the Electrical and Computer Engineering Department of Northeastern University (NU), Boston, Massachusetts, USA. At Northeastern, Professor Ostadabbas is the director of the Augmented Cognition Laboratory (ACLab) and the Co-Director of The Center for Signal Processing, Imaging, Reasoning, and Learning (SPIRAL). Professor Ostadabbas is the co-author of more than 100 peer-reviewed journal and conference articles and her research has been awarded by the National Science Foundation (NSF), including Pre-CAREER and CAREER awards, Department of Defense (DoD), Mathworks, Amazon AWS, Verizon, Oracle, Biogen, and NVIDIA. She served in the organization committees of many workshops in renowned conferences (such as CVPR, ECCV, ICCV, ICIP, ICCASP, Bio- CAS, CHASE, ICHI) in various roles including Lead/Co-Lead Organizer, Program Chair, Board Member, Publicity Co-Chair, Session Chair, Technical Committee, and Mentor.
email: Ostadabbas@ece.neu.edu
Elaheh Hatamimajoumerd, Workshop Chair
Northeastern University
Elaheh Hatamimajoumerd is a Postdoctoral Researcher at Northeastern University’s Department of Computer and Electrical Engineering, specializing in artificial intelligence with a focus on computer vision and machine learning in the small data domain. Her research aims to develop AI-guided systems for monitoring and assessing motor function in infants, enabling non-invasive tracking of motor impairments within their natural environment. She has published her findings in MICCAI2023 and CVPRW2023, with the ultimate goal of facilitating early detection and intervention of neurodevelopmental disorders in infants and children through affordable computer vision models.
Michael Wan, Workshop Chair
Northeastern University
Michael Wan is a Research Scientist at Institute for Experiential AI (EAI) at Northeastern University, based at the Roux Institute campus in Portland, Maine. He does research in computer vision, machine learning, and applications to healthcare, working closely with scientific collaborators on projects in infant state and pose estimation, infant neurodevelopmental health, medical image analysis, and more. Dr. Wan grew up in Toronto, Canada. He completed an HonBSc in mathematics, physics, and philosophy at the University of Toronto and a PhD in mathematical logic at the University of California, Berkeley, and held a Postdoctoral Research Fellowship in mathematics at the Ben-Gurion University.
email: mi.wan@northeastern.edu
Silvia Zuffi, Workshop Organizer
CNR Institute for Applied Mathematics
Silvia Zuffi, Ph.D. is Research Scientist at the CNR Institute for Applied Mathematics (IMATI-CNR) and Affiliated Researcher at the Max Planck Institute for Intelligent Systems (MPI-IS). She is also part of the National Biodiversity Future Center (NBFC) and Future Artificial Intelligence Research center (FAIR), in Italy. Her research interests span from color imaging and reproduction to machine learning, computer vision and graphics, with focus on motion capture and 3D modeling of humans and animals. She created the SMAL model, the first interspecies 3D articulated shape model of animals. She served as program chair for the IEEE Conference on 3D Vision (3DV) 2021 and area chair for the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 and 2023, and IEEE/CVF International Conference on Computer Vision (ICCV) 2023.
Chen Chen, Workshop Organizer
University of Central Florida
Chen Chen is an Assistant Professor at the Center for Research in Computer Vision, University of Central Florida. He received the Ph.D. degree from the Department of Electrical Engineering, University of Texas at Dallas in 2016 where he received the David Daniel Fellowship (Best Doctoral Dissertation Award). His research interests include computer vision, efficient deep learning, and federated learning. He has been actively involved in several NSF-sponsored research projects, focusing on ubiquitous machine vision on the edge and federated learning over-the-air for large-scale camera networks. Dr. Chen was an Area Chair for CVPR 2022, ECCV 2022, ACM Multimedia 2019-2022, ICME 2021-2023, and WACV 2019. He was an organizer of CVPR 2021 tutorial on Cross-view and Cross-modal Visual Geo-Localization. He was the lead organizer of the Workshop on Federated Learning for Computer Vision (FedVision) in conjunction with CVPR 2022 and 2023.
Haibo Wang, Workshop Organizer
Inari Medical
Haibo Wang is a Principal Applied Scientist at Inari Medical. He received his PhD degree in computer vision from Chinese Academy of Sciences, China and University of Sciences and Technology of Lille, France in 2011. He was an Assistant Professor at Shandong University for 2011 and worked as a postdoc at Case Western Reserve University from 2012 to 2015. He then joined Philips Research North America in 2015 and moved to Inari Medical in 2022. His research mainly covers human-centered computer vision, its applications to healthcare and medical image processing. He has published 40+ papers and 20+ patents, which attract 2000+ citations.
Workshop Committee
- Henry Clever, NVIDIA Research
- Somaieh Amraee, Roux Institute,Northeastern University
- Yanjun Zhu , Institute for Experiential AI, Northeastern University
- Rajagopal Venkatesaramani, Northeastern University
- Ce Zheng , University of Central Florida
- Lingfei Luan, University of Minnesota
- Xiaofei Huang, Northeastern University
- Zhouping Wang, Northeastern University
- Le Jiang, Northeastern University
- Shaotong Zhu, Northeastern University
- Pooria Daneshvar Kakhaki, Northeastern University