Shankar, Anirudh
CanPrecise AI, OncoFlow AI, University of Warwick, M S Ramaiah University of Applied Sciences
About
I am an AI STEM engineer and researcher passionate about bridging the gap between medical science and engineering. My work focuses on precision medicine, generative AI, and optimising clinical workflows in oncology.
Currently, I serve as the Co-Founder and Chief Technology Officer (CTO) of CanPrecise AI, where I spearhead the development of predictive AI frameworks that link imaging biomarkers to therapy responses. This research aids in simulating patient physiology to improve individualised treatment planning. Concurrently, as the Lead AI Engineer at OncoFlow, I architect scalable AWS cloud frameworks and develop specialised Small Language Models (SLMs) tailored for clinical decision-making.
I hold an MSc with Distinction in Data, Diagnostics, and Digital Health from the University of Warwick. My research interests include deep-learning radiomic platforms, federated learning, and physics-informed models in oncology theranostics. I have authored or co-authored over 15 peer-reviewed publications including work on the landscape of AI in PET imaging across the cancer continuum and hold a pending patent for a novel approach to medical image preprocessing. My overarching goal is to translate complex oncological biomarkers into robust, scalable software implementations that improve patient outcomes.
Employment
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CanPrecise AI CTO2026 - Present
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OncoFlow AI AI Engineering Lead2025 - Present
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M S Ramaiah University of Applied Sciences2020 - 2024
Education
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University of Warwick Master of Science in Diagnostics, Data and Digital Health2024 - 2025
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M S Ramaiah University of Applied Sciences Bachelors in Artificial Intelligence and Machine Learning2020 - 2024
Projects & Funding
Projects & funding information is unavailable.
Publications (26)
- Artificial intelligence–assisted treatment decision-making for cancer multidisciplinary team meetings: A proof of concept study. Save
- Intelligence-driven data extraction for the breast cancer multidisciplinary team meeting case preparation: Results from a prospective external validation. Save
- 632P Integrating artificial intelligence into cancer multidisciplinary team treatment decision-making: A proof-of-concept study Save
- 649eP Evaluating AI-driven extraction of radiology data for breast cancer MDT decision support Save
- The Current Landscape of Artificial Intelligence in Positron Emission Tomography (PET) Imaging Across the Cancer Continuum Save
- Artificial intelligence vs human-based frameworks for breast cancer molecular biomarker status assessment: A benchmarking analysis from 2500 patients. Save
- Enabling Autonomous and Intelligent Device Functionality Through IoT Integration Save
- Enabling autonomous and intelligent device functionality through IoT integration Save
- Synergising 6G technologies, artificial intelligence, and green innovations: A path towards sustainable and intelligent connectivity Save
- Gaze Corporate: A Corporate Profiling Website Save