CDS Faculty Fellows
The Faculty Fellows Program in the Faculty of Computing & Data Sciences (CDS) is conceived to develop and nurture a strong community of exceptional faculty members who pursue novel computational and data-driven research with strong potential for long-term impact. To that end, the program endeavors to identify and support newly recruited faculty members in various disciplines at BU, and to provide them with opportunities for connecting with the faculty members and programs in CDS. Below is a list of our CDS Faculty Fellows.
Learn about the CDS Faculty Fellows Program
Patrick Keys (2025)
Dr. Patrick Keys is an Assistant Professor in the Department of Earth & Environment at Boston University. His overarching aim is to explore how society will navigate climate and societal turbulence toward a sustainable and just future. Pat's research is highly interdisciplinary, focusing on a broad range of global challenges, including climate change futures, moisture recycling and society, and improving anticipation of Anthropocene change. To explore these topics, his research group uses climate data and models, societal simulations, and creative futures methods. Before joining Boston University, Pat served as an Assistant Professor in the Department of Atmospheric Science at Colorado State University. Previously, Pat founded an environmental consultancy that worked with local and international partners. In collaboration with different partners, he explored food security in the UAE, the link between drought and conflict in sub-Saharan Africa, and climate change adaptation and mitigation in Fort Collins.
Brian DePasquale (2025)
Brian DePasquale is an Assistant Professor in the Department of Biomedical Engineering. He leads the Artificial and Biological Intelligence Lab and is an affiliate faculty member in the Center for Systems Neuroscience. He conducts quantitative neuroscience research at all scales, from cognitive neuroscience and circuit biophysics to protein biochemistry. He uses approaches from machine learning, dynamical systems, and probabilistic modeling to uncover neural algorithms underlying decision-making, movement, and sensory processing. During his doctoral training at Columbia University and postdoctoral work at the Princeton Neuroscience Institute, Brian pioneered methods for constructing biologically realistic network models, establishing a bridge between networks in the brain and AI systems. In collaboration with experimental neuroscientists, his lab designs machine learning approaches to uncover structure in large neural datasets and develops artificial neural networks to understand the neural dynamics underlying computation.
Boqing Gong (2025)
Boqing Gong is an Assistant Professor in Computer Science at Boston University, where his research in computer vision and machine learning focuses on generalization, efficiency, and the visual analytics of objects, scenes, human activities, and their relationships. Dr. Gong is also an affiliated faculty member of Systems Engineering. Dr. Gong is an associate editor for IEEE T-PAMI and has served as a program co-chair for WACV 2023, tutorial co-chair for CVPR 2022, and (senior) area chair for CVPR, ICCV, ECCV, NeurIPS, ICML, and ICLR.
Deepti Ghadiyaram (2023)
Deepti Ghadiyaram joined the Department of Computer Science as an assistant professor in July 2024. She is currently a staff research scientist at Runway, where she focuses on improving the quality and safety of generative models. Previously, she was a senior research scientist at Fundamental AI Research (FAIR) in Meta AI, focusing on broad topics in computer vision and machine learning. Deepti received her PhD in computer science from the University of Texas at Austin in 2017. Her research interests span topics including visual scene understanding, fair and inclusive computer vision, explainability, and perceptual visual quality. She has served her professional community in many ways, including as area chair and program committee member in major machine learning and AI conferences. Discover more about Deepti.
Najoung Kim (2023)
Najoung Kim is an assistant professor at the Department of Linguistics, an affiliated faculty in the Department of Computer Science at Boston University, and a visiting faculty researcher at Google. Before joining BU, she was a faculty fellow at the Center for Data Science at New York University and received her PhD in cognitive science at Johns Hopkins University. Najoung is interested in studying meaning in both human and machine learners, especially ways in which they generalize to novel inputs and ways in which they treat implicit meaning. Her research has been supported by the National Science Foundation (NSF) and has received awards at venues such as the Meeting of the Association for Computational Linguistics and *SEM.
Archana Venkataraman (2023)
Archana Venkataraman is an associate professor of electrical and computer engineering and an affiliate faculty in the Departments of Biostatistics and Biomedical Engineering at Boston University. From 2016-2022, she was an assistant professor at Johns Hopkins University. Currently, Archana directs the Neural Systems Analysis (NSA) Laboratory, which works at the intersection of biomedical imaging, artificial intelligence, and clinical neuroscience. Her work has yielded novel insights into neurological disorders such as autism, schizophrenia, and epilepsy, with the long-term goal of improving patient care. Archana has won numerous awards, notably an NSF CAREER and recognition by MIT Technology Review as one of 35 Innovators Under 35. Her research is supported by NSF and the National Institutes of Health.