Devashish Khairnar's Linkedin Analytics

Devashish is a recent graduate of the University of Toronto, where he earned a Master’s degree in Applied Computing. Throughout his academic journey, he was honored with prestigious scholarships, including the Vector Scholar in AI and the JN Tata scholarships, for his outstanding academic performance. With a solid foundation built over four years of experience in software development and as a Machine Learning Engineer, Devashish brings a unique blend of research acumen and technical expertise. During his tenure at SOTI.inc, Devashish delved into machine learning and mathematical modeling, focusing on optimizing and predicting lithium-ion battery health. His Research and Development Intern role gave him valuable insights and practical experience in this specialized domain. Before this, he served as a Data Scientist at 16bit, where he curated image and textual data and implemented multi-modal AI models to generate radiology reports using DICOMs and clinical comments leveraging Large Language Models (LLMs). Devashish's contributions at DeepTek.ai were marked by his proficiency in developing FDA-approved chest X-ray segmentation models for various pathologies, showcasing his prowess in PyTorch, computer vision, image, and language processing domains. Furthermore, his tenure at ACI Worldwide as a Software Engineer equipped him with in-depth FinTech domain knowledge and honed his software engineering skills, including working with large databases, C#, .NET, GitHub, APIs, and Cloud. Devashish is eager to leverage his diverse skill set and rich experiences to make meaningful contributions to his future endeavors, and he is confident that his profile aligns seamlessly with the requirements of the software engineering, ML Engineering, and data science roles he aspires to undertake.