Pallavi Tiwari

Associate Professor

School of Medicine and Public Health | Departments of Radiology and Biomedical Engineering

Hometown: Indore, India

Pallavi Tiwari, PhD is an Associate Professor (tenure) in the Departments of Radiology, Biomedical Engineering, and Medical Physics;and serves as the Co-Director of Imaging and Radiation Science at the Carbone Cancer Center. Dr. Tiwari’s research interests lie in pattern recognition, data mining, and image analysis for automated computerized diagnostic, prognostic, and treatment evaluation solutions using radiologic imaging in oncology and neurological disorders. So far, her research has evolved into over 60 peer-reviewed publications, 50 peer-reviewed abstracts, and 14 patents (8 issued, 6 pending). Dr. Tiwari has been a recipient of several scientific awards, most notably, being named as one of 100 women achievers by the Government of India for making a positive impact in the field of Science and Innovation. In 2018, she was selected as one of Crain’s Cleveland Business Forty under 40. She has also been awarded the J&J Women in STEM (WiSTEM2D) scholar award in Technology, the Honorary Early Career Achievement Award (2021) and Imaging Innovator Award (2024) through the Society for Imaging Informatics in Medicine (SIIM). In 2023, Dr. Tiwari was inducted as a senior member of the National Academy of Inventors. Dr. Tiwari’s research is funded through the National Cancer Institute, Veterans Affairs, Department of Defense, and various foundation and state grants.

This talk can also be offered in Hindi.

Talks:

Artificial Intelligence and Computational Imaging: Opportunities for Precision Medicine

Dr. Tiwari will focus on her lab’s efforts in developing AI and machine learning techniques to capture insights into the underlying tumor biology as observed across non-invasive imaging, histopathology, and omics data. She will focus on applications of this work for predicting disease outcome, recurrence, progression, and response to therapy specifically in the context of oncology. She will also discuss current efforts in developing new image-based features for post-treatment evaluation and predicting response to chemo-radiation treatment. Dr. Tiwari will conclude her talk with a discussion of some of the translational aspects of her work from a clinical perspective.

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