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Guillermo Sapiro, James B. Duke Distinguished Professor of Electrical and Computer Engineering and Professor of Mathematics and Computer Science and Faculty Network Member of Duke Institute for Brain Sciences

Guillermo Sapiro

Guillermo Sapiro received his B.Sc. (summa cum laude), M.Sc., and Ph.D. from the Department of Electrical Engineering at the Technion, Israel Institute of Technology, in 1989, 1991, and 1993 respectively. After post-doctoral research at MIT, Dr. Sapiro became Member of Technical Staff at the research facilities of HP Labs in Palo Alto, California. He was with the Department of Electrical and Computer Engineering at the University of Minnesota, where he held the position of Distinguished McKnight University Professor and Vincentine Hermes-Luh Chair in Electrical and Computer Engineering. Currently he is the Edmund T. Pratt, Jr. School Professor with Duke University.

G. Sapiro works on theory and applications in computer vision, computer graphics, medical imaging, image analysis, and machine learning. He has authored and co-authored over 300 papers in these areas and has written a book published by Cambridge University Press, January 2001.

G. Sapiro was awarded the Gutwirth Scholarship for Special Excellence in Graduate Studies in 1991,  the Ollendorff Fellowship for Excellence in Vision and Image Understanding Work in 1992,  the Rothschild Fellowship for Post-Doctoral Studies in 1993, the Office of Naval Research Young Investigator Award in 1998,  the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1998, the National Science Foundation Career Award in 1999, and the National Security Science and Engineering Faculty Fellowship in 2010. He received the test of time award at ICCV 2011. He was elected to the American Academy of Arts and Sciences on 2018.

G. Sapiro is a Fellow of IEEE and SIAM.

G. Sapiro was the founding Editor-in-Chief of the SIAM Journal on Imaging Sciences.

Contact Info:
Office Location:  140 Science Drive
Office Phone:  (919) 660-5252
Email Address: send me a message
Web Pages:  http://www.math.duke.edu/~gs108
http://sapirolab.pratt.duke.edu/

Office Hours:

By appointment. Contact via e-mail.
Education:

D.Sc.Israel Institute of Technology (Israel)1993
MSTechnion, Haifa, Israel1991
BSTechnion, Haifa, Israel1989
Research Interests:

Image and video processing, computer vision, computer graphics, computational vision, biomedical imaging, brain imaging, cryo-tomography of viruses, computational tools in cryo-tomography, computational tools in early diagnosis of psychiatric disorders, differential geometry and differential equations, scientific computation, learning and high dimensional data analysis, sparse modeling and dictionary learning, applied mathematics.

Recent Publications   (More Publications)

  1. Solomon, O; Palnitkar, T; Patriat, R; Braun, H; Aman, J; Park, MC; Vitek, J; Sapiro, G; Harel, N, Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI., Human Brain Mapping (March, 2021) [doi]  [abs]
  2. Carpenter, KLH; Hahemi, J; Campbell, K; Lippmann, SJ; Baker, JP; Egger, HL; Espinosa, S; Vermeer, S; Sapiro, G; Dawson, G, Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism., Autism Res, vol. 14 no. 3 (March, 2021), pp. 488-499 [doi]  [abs]
  3. Perochon, S; Di Martino, M; Aiello, R; Baker, J; Carpenter, K; Chang, Z; Compton, S; Davis, N; Eichner, B; Espinosa, S; Flowers, J; Franz, L; Gagliano, M; Harris, A; Howard, J; Kollins, SH; Perrin, EM; Raj, P; Spanos, M; Walter, B; Sapiro, G; Dawson, G, A scalable computational approach to assessing response to name in toddlers with autism., The Journal of Child Psychology and Psychiatry and Allied Disciplines (February, 2021) [doi]  [abs]
  4. Emani, PS; Warrell, J; Anticevic, A; Bekiranov, S; Gandal, M; McConnell, MJ; Sapiro, G; Aspuru-Guzik, A; Baker, JT; Bastiani, M; Murray, JD; Sotiropoulos, SN; Taylor, J; Senthil, G; Lehner, T; Gerstein, MB; Harrow, AW, Quantum computing at the frontiers of biological sciences., Nature Methods (January, 2021) [doi]
  5. Hashemi, J; Dawson, G; Carpenter, KLH; Campbell, K; Qiu, Q; Espinosa, S; Marsan, S; Baker, JP; Egger, HL; Sapiro, G, Computer Vision Analysis for Quantification of Autism Risk Behaviors, Ieee Transactions on Affective Computing, vol. 12 no. 1 (January, 2021), pp. 215-226, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
Recent Grant Support

  • Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET), National Science Foundation, 2020/09-2025/08.      
  • Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET), Simons Foundation, 2020/09-2025/08.      
  • Point-of-care cellular and molecular pathology of breast tumors on a cell phone, National Institutes of Health, 2020/03-2025/02.      
  • Learning and Explaining Information Dynamics from Overhead Imagery, National Geospatial-Intelligence Agency, 2019/09-2024/09.      
  • Novel Approaches to Infant Screening for ASD in Pediatric Primary Care, National Institutes of Health, 2019/09-2024/06.      
  • Novel see and treat strategies for cervical cancer prevention in low-resource settings, National Institutes of Health, 2019/02-2024/01.      
  • Learning Utility-Preserving Private, Fair, and Invariant Representations, Office of Naval Research, 2020/05-2023/05.      
  • Scalable Computational Platform For Active Closed-Loop Behavioral Coding in Autism Spectrum Disorder, National Institutes of Health, 2019/07-2023/04.      
  • Fundamentals and Applications in Learned Information Representation, Office of Naval Research, 2020/04-2023/04.      
  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2022/09.      
  • Uncovering Population-Level Cellular Relationships to Behavior via Mesoscale Networks, National Institutes of Health, 2019/09-2022/09.      
  • SCH: INT: Computational Tools for Avoidant/Restrictive Food Intake Disorder, National Institutes of Health, 2019/09-2022/08.      
  • Digital Behavioral Outcome Measures for Autism, Simons Foundation Autism Research Initiative, 2019/07-2022/06.      
  • REU Site for Meeting the Grand Challenges in Engineering, National Science Foundation, 2017/05-2022/04.      
  • Duke Expanded Access Protocol Proposal for the Cord Blood Association Foundation, Cord Blood Association Foundation, 2020/01-2021/12.      
  • GitPaper: A Networked Model of Scientific Review and Dissemination, Office of Naval Research, N00014-17-1-2781, 2017/09-2021/08.      
  • Tailoring treatment targets for early autism intervention in Africa, National Institutes of Health, 2019/08-2021/07.      
  • Building a streamlined birth cohort to study autism risk factors and biomarkers, Drexel University, 2020/01-2021/05.      
  • Learning Privacy for the Internet of Visual Things, Cisco Systems, Inc, 2018/06-2021/05.      
  • Learning and Privacy in a Closed Environment, Office of Naval Research, N00014-18-1-2143-01, 2018/02-2021/01.      
  • CIF: AF: Small: Foundations of Multimodal Information Integration, National Science Foundation, 1712867, 2017/09-2020/08.      
  • The Foundations of Dynamic Drone-based Threat Detection, National Science Foundation, 1737744, 2017/09-2020/08.      
  • Explainability and Trade Secrecy in AI-Enabled Clinical Decision Support, Diagnostic, and Predictive Software, Greenwall Foundation, 2019/01-2020/06.      
  • Training in Medical Imaging, National Institutes of Health, 2003/07-2020/06.      
  • Network Inference and Analysis of Big Dynamic Data, National Geospatial-Intelligence Agency, HM04761610001, 2016/02-2020/01.      
  • Modeling, Computations, and Applications in Multimodal Information Integration, Office of Naval Research, N00014, 2016/04-2019/10.      
  • Multimodal Subspace Learning and Modeling of Complex Systems, Army Research Laboratory, W911NF-16-1-0088, 2016/04-2019/09.      
  • Network motifs in cortical computation, University of California - Los Angeles, 1430 G UA755, 2016/09-2019/06.      
  • Synaptomes of Mice and Men, Allen Institute for Brain Science, 2014-0567, 2014/09-2019/06.      
  • Nonparametric Bayes Methods for Big Data in Neuroscience, National Institutes of Health, 2014/09-2019/06.      

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320