👋🏼 Hello there, I’m Kaushik!
👨🏻💻 I’m fifth year PhD Student in Imaging Science which is an interdisciplinary program between McKelvey School of Engineering and Washington University School of Medicine. I am part of the Quantitative Molecular Systems and Imaging Lab in Washington University School of Medicine under the supervision of Dr. Kooresh I. Shoghi.
🔬 My research interests lies in the interface of developing machine-learning/deep-learning algorithm in context of medical imaging and computer vision. Specifically, my PhD dissertation research focuses on developing novel deep-learning based computational frameworks for multi-modal and multi-scale preclinical quantitative imaging for assessing therapeutic response. I am particularly passionate about designing foundational models which are quantitatively interpretable, reproducible, scalable and hence can be deployed for translational purposes in co-clinical imaging.
🛠️ In the Summer of 2023, I worked as a Data Science Intern for Bristol Myers Squibb under the supervision of Dr. Mariann Micsinai-Balan and David Paulucci. I developed deep learning-based pipelines for automatic analysis of large dataset of multi-modal medical images, radiomics feature extraction, and prediction of patient outcomes, utilizing Clinical Trial Data and Real-World Data (RWD) to predict survival and therapeutic response.
📰 Recent News
- May 2024 - Journal Paper on preclinical Standard-Count PET image generation from multiple Low-Count PET using Attention Residual Dilated Network (ARD-Net) followed by multi-objective task-based performamce assesment published in Medical Physics
- April 2024 - Awarded certificate for Leadership and Management in Action Programme (L-MAP) for completing 12-hours of formal leadership, management, and inclusive teamwork skillset training.
- January 2024 - Passed the Annual Doctoral Committee Update Examination
- November 2023 - Oral Paper on self-supervised PET Denoising presented and Trainee Grant Awarded at 2023 IEEE NSS/MIC Vancouver Canada
- May 2023 - Started working as Data Science Intern for Bristol Myers Squibb
- April 2023 - Elected as the Graduate Student Representative to the WashU Board of Trustees
- March 2023 - Outstanding Leadership Award from Imaging Science Program at McKelvey School of Engineering.
- December 2022 - Passed WashU Imaging Science PhD Dissertation Proposal Examination.
- October 2022 - Abstract Presented at Oral Presentation in 2022 WMIC Miami.
- August 2022 - Poster Award Winner (1st Place) in 2022 NCI Informatics Technology for Cancer Research (ITCR)
- June 2022 - Abstract presented on quantitatively accurate PET image generation in 2023 SNMMI Vancouver Canada.
- April 2022 - Poster Award Winner (1st Place) in Oncologic Imaging Program at Siteman Cancer Center.
- March 2022 - Best Poster Award in WashU Imaging Science Retreat 2022.
- February 2022 - Oral Paper on deep-learning based high-count preclinical PET image generation simulated phantoms presented at 2022 SPIE Medical Imaging San Diego USA.
- July 2021 - Passed WashU Imaging Science PhD Qualifying Examination
- June 2021 - Journal Paper on multi-contrast MR Segmentation and quantitative analysis accepted in Cancers [IF:6.2].