As a child, my curiosity about how things worked led me to disassemble and reassemble toys, a practice that fostered my patient and step-by-step approach to learning. I developed expertise in software development, Docker, deep learning, and image processing, which was crucial during my tenure as an R&D Engineering Intern at Kitware Inc., where I contributed to open-source tools for whole slide image analysis. Although I initially pursued Biotechnology, my passion for technology and involvement with my college Robotics club led to a career as a Robotics and AI consultant, developing robots for medical device companies. This diverse background helped me bridge theory and application, providing innovative solutions across domains. Pursuing a Ph.D. in Biomedical Engineering in the University of Iowa - USA, I have worked on MRI analysis, developing AI infrastructure for upper airway analysis and advancing the understanding of diseases like OSA. My current focus is on creating generalizable AI algorithms that work across various MRI protocols and hardware with minimal data.

Currently, I'm in my last semester of PhD at University of Iowa, Working on my thesis 'Data efficient segmentation methods for upper airway imaging'.As I'm getting closer to my PhD defense and I'm in lookout for full time opportunities after that. It would great to connect if you are looking for an entry-level Machine Learning (ML) Specialists / Researcher in the field of Machine learning & Imaging.

• Automatic Multiple Articulator Segmentation in Dynamic Speech MRI Using a Protocol Adaptive Stacked Transfer Learning U-NET Model link
• Accelerated Pseudo 3D Dynamic Speech MR Imaging at 3T Using Unsupervised Deep Variational Manifold Learning link
• Network Analysis of MPO and Other Relevant Proteins Involved in Diabetic Foot Ulcer and Other Diabetic Complication link