Ayushi Sinha

About

Principal Scientist at Mayo Clinic. Formerly, Sr. Scientist at Philips Research, and Assistant Research Scientist in the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University. Interests include foundation models, computational pathology, radiology, medical image analysis and segmentation, statistical shape modelling, deformable registration using statistics, and unsupervised disentanglement of modes in surgical data.

Employment

• Mayo Clinic Principal Data Scientist
  2025 - Present
• Philips Senior Scientist
  2023 - 2025
• Philips Senior Scientist
  2021 - 2023
• Philips Scientist
  2019 - 2021
• Johns Hopkins University Assistant Research Scientist
  2019 - 2019
• Johns Hopkins University Provost's Postdoctoral Fellow
  2018 - 2019
• Intel Corporation Graphics Graduate Technical Intern
  2013 - 2013
• Johns Hopkins University Graduate Research Assistant
  2011 - 2018

Education

• Johns Hopkins University M.S.E., Ph.D.
  2011 - 2018
• Providence College B.S., B.A.
  2007 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Tunable and real‐time automatic interventional x‐ray collimation from semi‐supervised deep feature extraction
  Medical Physics 2025 DOI: 10.1002/mp.17522
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• A Novel Method for the Generation of Realistic Lung Nodules Visualized Under X-Ray Imaging
  Tomography 2024 DOI: 10.3390/tomography10120142
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• Dense Depth Estimation in Monocular Endoscopy With Self-Supervised Learning Methods
  IEEE Transactions on Medical Imaging 2020 DOI: 10.1109/TMI.2019.2950936
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• Endoscopic navigation in the clinic: registration in the absence of preoperative imaging
  International Journal of Computer Assisted Radiology and Surgery 2019 DOI: 10.1007/s11548-019-02005-0
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• The deformable most-likely-point paradigm
  Medical Image Analysis 2019 DOI: 10.1016/j.media.2019.04.013
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• Evaluation and Stability Analysis of Video-Based Navigation System for Functional Endoscopic Sinus Surgery on <italic>In Vivo</italic> Clinical Data
  IEEE Transactions on Medical Imaging 2018 DOI: 10.1109/TMI.2018.2833868
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• Endoscopic Navigation in the Absence of CT Imaging
  Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 2018 DOI: 10.1007/978-3-030-00937-3_8
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• Simultaneous segmentation and correspondence improvement using statistical modes
  Medical Imaging 2017: Image Processing 2017 DOI: 10.1117/12.2253533
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• Automatic segmentation and statistical shape modeling of the paranasal sinuses to estimate natural variations
  Medical Imaging 2016: Image Processing 2016 DOI: 10.1117/12.2217337
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• Endoscopic-CT: learning-based photometric reconstruction for endoscopic sinus surgery
  Medical Imaging 2016: Image Processing 2016 DOI: 10.1117/12.2216296
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