Rupsa Bhattacharjee,PhD

Rupsa Bhattacharjee,PhD

Principal Investigator:

Rupsa Bhattacharjee, PhD

Assistant Professor, Department of Medical Sciences & Technology,
Indian Institute of Technology (IIT), Madras, Chennai, India

Previously: Associate Specialist, Department of Radiology & Biomedical Imaging
University of California, San Francisco

I am an Imaging Scientist, an Assistant Professor in The Department of Medical Sciences & Technology, IIT Madras (joined in July 2025).

I was a Postdoctoral Researcher (Associate Specialist) in the Department of Radiology and Biomedical Imaging, University of California, San Francisco (UCSF) during 2021-2025. There, I had been working under the supervision of Professor Sharmila Majumdar, Vice Chair, Research, Radiology, and Margaret Hart Surbeck Distinguished Professor, since November 2021. (https://radiology.ucsf.edu/research/labs/musculoskeletal-quantitative-imaging/labs/majumdar-lab). At UCSF, my work focusing on musculoskeletal imaging involved close collaboration with and co-supervision on individual projects from Dr. Thomas Link (Musculoskeletal Imaging Section and Clinical Director of the Musculoskeletal and Quantitative Imaging Research), Dr. Richard Souza (Vice Chair for Research and Professor in the Department of Physical Therapy and Rehabilitation Science), and Dr. Yang Yang (Associate Professor, Mid and Low-Field MRI expert). Details about my postdoctoral research projects are highlighted in the "Postdoctoral Experiences" section.

Prior to this, I completed my PhD (Biomedical Engineering) at the Indian Institute of Technology (IIT) Delhi, in Dr. Anup Singh's Lab (https://profile.iitd.ac.in//~anupsm/ ), in October 2021. My thesis was titled as “Quantitative Susceptibility Weighted Imaging in the Grading of Intracranial Mass Lesions and Assessment of Acute Ischemic Stroke Penumbra”.

I have also worked at Philips Health Systems, MRI Division, as an MRI Application Specialist, collaborating with renowned radiologists across India, including Fortis Memorial Research Institute, All India Institute of Medical Sciences (AIIMS), PGI, Apollo Hospitals, Mahajan Group of Imaging, Max Hospitals and many more. Relevant experiences are highlighted in the "Predoctoral Experiences" section".

Area of Expertise:

Medical Imaging (Primarily Magnetic Resonance Imaging and also CT, PET, X-ray)
Image Processing: Acquisition, Reconstruction, Post-processing, Analysis,
Computational and Quantitative Techniques
Applications of Deep Learning in Medical Imaging and Health Informatics

Specifics:

Musculoskeletal MRI & PET (NaF) Imaging and Osteoarthritis research: 3.0T & 0.55T
Disease Progression, Follow-up: T1p, T2, Bone, Cartilage, Muscle, Menisci health, compositional, metabolic, and morphological Biomarkers in Osteoarthritis
Machine Learning & Deep Learning: synthetic imaging, grading, image assessment, anomaly detection, denoising, and segmentation
Working and curating larger image databases, conducting and evaluating Health-Data specific AI challenges for Conferences (MICCAI-2022)
Experience working with Biomechanical data analysis (kinetics, kinematics, gait analysis)
Exploring the technical feasibility of utilizing new-generation MRI scanners (0.55T) for Osteoarthritis evaluation
Specialized in Neuro MRI Imaging Evaluation: Glioma & Acute Ischemic Stroke
Susceptibility Weighted Imaging (SWI) and its utilization in novel scopes

Specific Vision and Passion Projects:

Understanding progression of musculoskeletal degenerative diseases: Intra & Inter-joint, Intra & Inter-Tissue (Hip and Knee connections, Bone, Cartilage, Muscle, Menisci) via assessment of metabolic, compositional, and morphological biomarkers
Identifying demographic-specific differences in musculoskeletal disease progression: via Imaging and Biomechanical analysis (Sports and rehabilitation conditions, geography, and lifestyle-specific changes)
Decoding the understanding of musculoskeletal pain via joint-brain connections
Translating existing biomarker evaluations/developments down to economic scanners of lower capabilities

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