Abhejit Rajagopal

I am a Postdoctoral Fellow in the Dept. of Radiology and Biomedical Imaging at UCSF working with Peder Larson and Thomas Hope. I am a deep learning expert, and my research involves designing robust machine learning algorithms for image reconstruction and classification of MRI, PET, CT, SPECT, LIDAR, and radar. My current work and funding is focused on prostate cancer imaging, recognition, and radiotherapy planning, and has broad applicability to other organ systems. My foundational work is focused on understanding and quantifying the generalization properties of deep networks.

I also hold appointments at the San Francisco VA Medical Center (Staff Researcher), and Toyon Research Corp. (Senior Analyst), where I am translating solutions for high resolution intelligence in defense and healthcare.

Current Appointments

Postdoctoral Fellow (2019-Present)
Department of Radiology and Biomedical Imaging, University of California, San Francisco

Staff Researcher - (2021-Present)
San Francisco Veterans' Affairs Medical Center

Senior Analyst - (2021-Present)
Toyon Research

Experience

Director of Imaging - (2021-2022)
Ziteo Medical

Graduate Student Researcher - 2014-2019
Scientific Computing Group, University of California, Santa Barbara

Analyst - 2017-2021
ISR Algorithms Group, Toyon Research

Research Intern - 2015-2017
ISR Algorithms Group, Toyon Research

Research Intern - Summer 2015
Akela Inc.

Consultant - 2014 - 2016
Neural Analytics (now NovaSignal)

Researcher - 2014 - 2016
Staba Lab, Department of Neurology, University of California, Los Angeles

Research Assistant - 2013 - 2014
Neurovascular Imaging Research Core, University of California, Los Angeles

Research Assistant - 2013 - 2014
Integrated NanoMaterials Core Lab, University of California, Los Angeles

Education

Ph.D., Electrical and Computer Engineering (2014-2019)
University of California, Santa Barbara
Advisor: Dr. Shivkumar Chandrasekaran
Thesis: High-Dimensional Polynomial Approximation with Applications in Imaging and Recognition

M.S., Electrical and Computer Engineering (2014-2016)
University of California, Santa Barbara
Advisor: Dr. Shivkumar Chandrasekaran

B.S., Electrical Engineering (2010-2014)
University of California, Los Angeles
Advisor: Dr. Diana L. Huffaker

Publications   [Scholar]

Under Review

1. Predicting Generalization of CNNs Without Labels   
   A. Rajagopal, V.C Madala, T.A. Hope, P.E.Z. Larson
   under review, December 2021.
2. A Privacy-Optimizing Streaming Data Architecture   
   D. Dangwal, A. Rajagopal, A.G. Glova, R. Gretsch, P. Jain, J. Balkind, and T. Sherwood
   under review, November 2021
3. Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network   
   J. Scholey, A. Rajagopal, E. Vasquez, A. Sudhyadhom, P.E.Z. Larson
   under review, November 2021.
4. Synthetic PET via Domain Translation of 3D MRI   
   A. Rajagopal, Y. Natsuaki, K. Wangerin, M. Hamdi, R. Laforest, H. An, P.E. Kinahan, J.J. Sunderland, T.A. Hope, P.E.Z. Larson
   under review, October 2021.
5. Lesion Insertion Tool to Assess PET-MR Attenuation Correction Methods: Matched Contralateral and Localized Uptake Lesion Insertions in Pelvis PET-MR Data   
   R. Laforest, M. Khaligi, Y. Natsuaki, , D. Chandramohan, D. Byrd, H. An, P.E.Z Larson, S.S. James, J.J. Sunderland, P.E. Kinahan, T.A. Hope Y. Natsuaki, A.P. Leynes, K. Wangerin, M. Hamdi, A. Rajagopal, P.E. Kinahan, R. Laforest, P.E.Z. Larson, T.A. Hope, S. St. James
   under review, January 2021.

Refereed Conference Papers

1. Understanding and Visualizing Generalization in UNets   
   A. Rajagopal V.C Madala, T.A. Hope, and P.E.Z. Larson
   Medical Imaging with Deep Learning (MIDL '21)
2. Enhanced PET/MRI Reconstruction via Dichromatic Interpolation of Domain-Translated Zero-Dose PET   
   A. Rajagopal, N. Dwork, T.A. Hope, and P.E.Z.Larson
   SPIE Medical Imaging: Physics of Medical Imaging (SPIE-MI '21)
3. DeepOSM-3D: recognition in aerial LiDAR RGBD imagery   
   A. Rajagopal, W. Nelson, N. Stier, S. Chandrasekaran, and A.P. Brown
   SPIE Defense and Commercial Sensing: Geospatial Informatics (SPIE-DCS '20)
4. Remote Heart Monitoring via Medical Telemetry   
   V.R. Radzicki, A. Rajagopal, and H. Lee
   International Telemetry Conference (ITC '19)
5. Towards deep iterative-reconstruction algorithms for computed tomography (CT/SPECT) applications   
   A. Rajagopal, N. Stier, J. Dey, M.A. King, and S. Chandrasekaran
   SPIE Medical Imaging: Physics of Medical Imaging (SPIE-MI '19)
6. Fast Algorithms for Displacement and Low-Rank Structured Matrices   
   S. Chandrasekaran, N. Govindarajan, and A. Rajagopal
   2018 ACM International Symposium on Symbolic and Algebraic Computation (ISSAC '18)
7. Towards non-invasive electrocardiographic imaging using regularized neural networks   
   A. Rajagopal, V.R. Radzicki, H. Lee, and S. Chandrasekaran
   SPIE Medical Imaging: Physics of Medical Imaging (SPIE-MI '18)
8. Tracking Information in RaDAR Image Formation and Classification Algorithms   
   A. Rajagopal, V.R. Radzicki, S. Chandrasekaran, and H. Lee
   International Telemetry Conference (ITC '17)
9. A machine learning pipeline for automated registration and classification of 3D LiDAR data   
   A. Rajagopal, V.R. Radzicki, S. Chandrasekaran, and H. Lee
   SPIE Defense and Commercial Sensing: Geospatial Informatics (SPIE-DCS '17)
10. High-efficiency nanopillar solar cells employing wide-bandgap surface recombination barrier   
    G. Mariani, M. Haddad, A. Rajagopal, and D.L. Huffaker
    SPIE Photonics West

Journal Papers

1. A Harmonization of PET image Reconstruction HyperParameters in Simultaneous PET/MRI   
   R. Laforest, M. Khaligi, Y. Natsuaki, A. Rajagopal, D. Chandramohan, D. Byrd, H. An, P.E.Z Larson, S.S. James, J.J. Sunderland, P.E. Kinahan, T.A. Hope
   European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI) Physics, September 2021.
2. A Path to Qualification of PET/MR Scanners for Multicenter Brain Imaging Studies: Evaluation of MR-based Attenuation Correction Methods Using a Patient Phantom   
   C. Ciprian, H. An, F. Boada, T. Cao, D. Faul, B. Jakoby, F. Jansen, B.J. Kemp, P.E. Kinahan, P.E.Z. Larson, M.A. Levine, P. Maniawski, O. Mawlawi, J.E. McConathy, A. McMillan, J. Price, A. Rajagopal, J. Sunderland, P. Veit-Haibach, K.A. Wangerin, C. Ying, T.A. Hope
   Journal of Nuclear Medicine, July 2021.
3. Nonlinear electrocardiographic imaging using polynomial approximation networks   
   A. Rajagopal, V.R. Radzicki, H. Lee, and S. Chandrasekaran
   APL Bioengineering, October 2018.
4. Fast indefinite multi-point clustering   
   S. Chandrasekaran and A. Rajagopal
   Calcolo, April 2016.
5. Noise reduction in intracranial pressure signal using causal shape manifolds   
   A. Rajagopal, R. Hamilton, and F. Scalzo
   Biomedical Signal Processing and Control, March 2016.
6. Plasmonic field confinement for separate absorption-multiplication in InGaAs nanopillar avalanche photodiodes   
   A. Farrell, P. Senanayake, CH. Hung, G. El-howayek, A. Rajagopal, M. Currie, M. Hayat, and D.L. Huffaker
   Scientific Reports, December 2015.

Funding

• Pilot Project, Benioff Initiative for Prostate Cancer Research, Principal Investigator (with J.Scholey), $50K, (Aug 2021 - present), "AI-assisted Targeted Prostate Radiotherapy"

• NIH/NIBIB F32 Fellowship, Principal Investigator, $138K, (Dec 2020 - present), "Multi-modal and Extreme PET/MRI Reconstruction Methods"

• DoD/SBIR Phase-I, SCO 182-008, Principal Investigator, $225K, (Dec 2018 - Jun 2019), "Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning"

• DoD/STTR Phase-I, N18B-T033, Principal Investigator, $125K, (Oct 2018 - Apr 2019), "Blending Classical Model-Based Target Classification and Identification Approaches with Data-Driven Artificial Intelligence"

• DoD/SBIR Phase-II AF161-138, Principal Investigator, $750K, (Nov 2017 - Feb 2020), "Cognitive Processing and Exploitation of 3D Laser Imaging Detection and Ranging (LIDAR) Imagery Data"