Shrikant Chikhalkar is a senior engineering leader with over two decades of experience designing and delivering high-performance software for regulated healthcare, neuromodulation, and medical imaging systems. His work spans safety-critical medical devices, PET/MR reconstruction platforms, and cloud-native, AI-enabled software architectures developed under IEC 62304 and FDA 510(k) regulatory frameworks.
Currently a Senior Staff Software Engineer, Shrikant leads backend and platform initiatives supporting clinician and patient applications, including consent management systems, dynamic configuration platforms, secure telemetry pipelines, and cross-platform MAUI architectures spanning iOS, Android, and Windows. He has played a key role in enabling global neuromodulation therapy launches across 27 European countries while ensuring GDPR, HIPAA, and regional data-sovereignty compliance. His work includes regulated SDLC execution, microservice modernization, DevOps automation, and the application of generative AI to improve engineering productivity and regulatory documentation workflows.
Previously, Shrikant spent a decade at GE Healthcare as a Staff Software Architect, where he led PET/MR reconstruction and acquisition software for clinical imaging systems. He was responsible for productizing advanced MR attenuation correction (MRAC) algorithms, motion-corrected PET/MR reconstruction pipelines, fault-tolerant imaging systems, and GPU-accelerated reconstruction frameworks that achieved up to 200× performance gains. His contributions supported FDA 510(k) submissions and were validated through phantom and clinical image-quality studies.
Earlier in his career, Shrikant held technical leadership and engineering roles at IGATE, Persistent Systems, Accenture, Manchitra, and a computational research lab, working on legacy modernization, distributed graph mining, seismic simulation, GIS rendering engines, and large-scale HPC systems using MPI, OpenMP, and GPU computing.
Shrikant holds a Bachelor’s degree in Computer Science from the University of Pune and has completed graduate-level coursework in artificial intelligence, deep learning, cloud computing, and algorithm analysis at the University of Wisconsin–Milwaukee. He has earned certifications in Generative AI with Large Language Models, SAFe, and project management, and has submitted intellectual property related to AI-assisted code analysis. He has also presented at international conferences, including ISMRM, and has served as an architecture lead and mentor across global engineering teams.