Ekansh SareenView profile
Research Fellow
Ekansh Sareen is a Doctoral Assistant at the Medical Image Processing Laboratory (MIPLAB) within the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is concurrently enrolled in the Doctoral Program in Electrical Engineering (EDEE) under the Doctoral School (EDOC), reflecting his dual role as a researcher and PhD candidate. His work is based at Campus Biotech in Geneva, where MIPLAB conducts cutting-edge research in biomedical imaging and computational methods for healthcare applications. His research interests lie at the intersection of engineering and medicine, with a focus on medical image processing , signal processing , and machine learning . These areas are central to developing automated tools for disease detection, image segmentation, and diagnostic support systems. Given his affiliation with MIPLAB, his work likely involves deep learning models applied to MRI, CT, or ultrasound data, contributing to advancements in precision medicine and digital health. While no publications are listed in the provided text, the research output from MIPLAB typically spans computer vision, artificial intelligence in healthcare, and biomedical signal analysis. The lab’s work often emphasizes translational research, aiming to bridge the gap between algorithmic innovation and clinical utility. Future trends in his research may include explainable AI, federated learning for medical data, and integration with electronic health records. Scientific Awards: No awards mentioned. As a Doctoral Assistant, Ekansh is involved in research and potentially teaching or mentoring, though no advisees are listed. He does not appear to lead independent grants, but likely contributes to larger collaborative projects within EPFL or with clinical partners. MIPLAB is part of a broader ecosystem of health technology innovation at EPFL, collaborating with hospitals and industry partners to develop real-world medical solutions. The laboratory environment fosters interdisciplinary collaboration, combining expertise from electrical engineering, computer science, and clinical medicine. Ekansh’s position places him at the forefront of academic research in medical AI, with opportunities to publish in top-tier journals and present at international conferences. His career trajectory is aligned with academic or industrial research in biomedical engineering and AI-driven healthcare technologies.







