Christopher Kanan, Ph.D.
Affiliations: | 2004-2006 | Computer Science | University of Southern California, Los Angeles, CA, United States |
| 2007-2013 | Computer Science and Engineering | University of California, San Diego, La Jolla, CA | |
| 2013-2015 | Jet Propulsion Laboratory | California Institute of Technology, Pasadena, CA | |
| 2015-2022 | Chester F. Carlson Center for Imaging Science | Rochester Institute of Technology, Rochester, NY, United States | |
| 2022- | Computer Science | University of Rochester, Rochester, NY |
Area:
Deep Learning, Artificial Intelligence, Computer Vision, Cognitive ScienceWebsite:
http://chriskanan.comGoogle:
"Christopher Kanan"Mean distance: 14.57 (cluster 29) | S | N | B | C | P |
Cross-listing: Computational Biology Tree
Parents
Sign in to add mentor| Michael A. Arbib | grad student | 2005-2007 | USC | |
| Garrison Cottrell | grad student | 2007-2013 | UCSD | |
| (In defense of brain-inspired cognitive models.) | ||||
Children
Sign in to add trainee| Adam Casson | research assistant | 2016-2017 | Rochester Institute of Technology |
| Rodney Sanchez | research assistant | 2016-2019 | Rochester Institute of Technology |
| Robik Singh Shrestha | grad student | 2017- | Rochester Institute of Technology |
| Jhair Gallardo | grad student | 2019- | Rochester Institute of Technology |
| Yousuf Harun | grad student | 2020- | Rochester Institute of Technology |
| Shikhar Srivastava | grad student | 2023- | Rochester (MathTree) |
| Ronald Kemker | grad student | 2015-2018 | Rochester Institute of Technology |
| Kushal Kafle | grad student | 2015-2020 | Rochester Institute of Technology |
| Ryne Roady | grad student | 2017-2020 | Rochester Institute of Technology |
| Zhongchao Qian | grad student | 2018-2020 | Rochester Institute of Technology |
| Tyler L Hayes | grad student | 2016-2022 | Rochester Institute of Technology |
| Manoj Acharya | grad student | 2017-2022 | Rochester Institute of Technology |
| Usman Mahmood | grad student | 2017-2022 | Rochester Institute of Technology |
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Publications
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| Pareja F, Dopeso H, Wang YK, et al. (2024) A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms. Cancer Research |
| Vorontsov E, Bozkurt A, Casson A, et al. (2024) A foundation model for clinical-grade computational pathology and rare cancers detection. Nature Medicine |
| Raciti P, Sue J, Retamero JA, et al. (2022) Clinical Validation of Artificial Intelligence-Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection. Archives of Pathology & Laboratory Medicine |
| Mahmood U, Bates DDB, Erdi YE, et al. (2022) Deep Learning and Domain-Specific Knowledge to Segment the Liver from Synthetic Dual Energy CT Iodine Scans. Diagnostics (Basel, Switzerland). 12 |
| Mahmood U, Shrestha R, Bates DDB, et al. (2021) Detecting Spurious Correlations With Sanity Tests for Artificial Intelligence Guided Radiology Systems. Frontiers in Digital Health. 3: 671015 |
| Hayes TL, Krishnan GP, Bazhenov M, et al. (2021) Replay in Deep Learning: Current Approaches and Missing Biological Elements. Neural Computation. 1-44 |
| Mahmood U, Apte A, Kanan C, et al. (2021) Quality control of radiomic features using 3D-printed CT phantoms. Journal of Medical Imaging (Bellingham, Wash.). 8: 033505 |
| da Silva LM, Pereira EM, Salles PG, et al. (2021) Independent real-world application of a clinical-grade automated prostate cancer detection system. The Journal of Pathology |
| Roady R, Hayes TL, Kemker R, et al. (2020) Are open set classification methods effective on large-scale datasets? Plos One. 15: e0238302 |
| Kafle K, Shrestha R, Kanan C. (2019) Challenges and Prospects in Vision and Language Research. Frontiers in Artificial Intelligence. 2: 28 |