Abhinav K. Jha’s research is in the design, evaluation and translation of computational medical imaging methods for optimized performance in diagnostic and therapeutic tasks using quantitative measures of task performance. For this purpose, his group develops novel physics and artificial intelligence (AI)-based methods for image reconstruction, image enhancement, image analysis and task-based image-quality evaluation. One major research direction is in integrating AI and task-based assessment to make medical imaging more comfortable and accessible for patients by reducing acquisition dose and scanning times, and more valuable for physicians by automating image-analysis procedures and providing imaging biomarkers to monitor disease response. This research direction also includes studying the clinical deployment and ethical aspects of AI algorithms. Another major direction of research is developing low-count quantitative imaging methods for personalizing emerging cancer treatments. Towards this goal, his group develops statistical signal-processing approaches that maximize the extracted task-specific information from data measured by imaging systems.

Research keywords: Computational medical imaging; Artificial intelligence; Imaging Science

Basic information

Mentoring statement:Find it here.
Some former postdocs’ career outcomes:Not provided.
Other info:https://jhalab.wustl.edu/positions

Postdoc openings within the next year

Number of postdoc positions:2
Postdoc eligibility:U.S. Citizens or Permanent Residents
Current Visa-Holding Trainees in the U.S.
International Trainees Outside the U.S.