Machine learning researcher with 7+ years of experience developing and prototyping innovative algorithms. Proficient in leveraging deep learning techniques for medical image analysis, resulting in 9+ peer-reviewed publications. Proven ability to bridge research and industry through 4+ years of software engineering in a R&D.I graduated in July 2024 and am open to opportunities in either ML research or engineer roles.𝗔𝗿𝗲𝗮 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: Deep Learning, Computer Vision, Medical Image Analysis, Image Segmentation, Semi-supervised learning, Weakly-supervised learning, Uncertainty, Representation learning, Interpretability, Calibration, Image retrieval, Image enhancement, CNN, Generative adversarial network, Geometric deep learning, and Generative AICurrently, I am a Ph.D. candidate at Shapets lab, ETS Montreal, under the supervision of Prof. Herve Lombaert and Prof. Jose Dolz. Previously, I did a master's (by research) at the Center for Visual Information Technology, IIIT Hyderabad, India, under the guidance of Prof. Jayanthi Sivaswamy. Before that, I worked as a Software Engineer at LG Soft India, Bengaluru. I received my B.E. degree in Electronics and Communication Engineering from the SJCE, Mysuru, India, in 2012.My research focuses on applying Machine Learning techniques to medical images. In my doctoral studies, I am working on leveraging uncertainty for medical image segmentation (MR, CT, dermoscopy) under full and limited supervision. Prior to this, I developed algorithms for retinal image enhancement in my Master's. In particular, I improved the quality of smartphone-based fundus and optical coherence tomography (OCT) images using unsupervised and limited supervised techniques.As a researcher, I recognize the importance of reliable and affordable technologies for social good. I would love to connect with you and explore potential opportunities.