Chase Duncan

Background

About Chase Duncan

As a research assistant at the University of Illinois Urbana-Champaign, I applied my software engineering and machine learning skills to design, implement, and deploy innovative AI solutions for biomedical engineering and language. I led a project that developed a deep learning pipeline for glioma segmentation for use in 3D presurgical planning, using Python and convolutional neural networks. I also engineered a system that used Bing queries of naively transliterated tokens for grounding entities from text in low-resource languages, using Java and natural language processing. I presented my work at DARPA Demo Days and other academic venues, demonstrating the potential impact of AI in diverse domains. I graduated with a Master of Science degree in Computer Science from the University of Illinois Urbana-Champaign, where I also obtained my Bachelor of Science degree in the same field. During my studies, I collaborated with faculty and college administration to create curriculum and prerequisites for a new machine learning course, and designed course materials and coding problems in Python and Numpy. I am passionate about applying using tech to solve real-world problems and helping the people I work with flourish. I am proficient in C++, Python, Java, and various machine learning frameworks and tools, such as PyTorch, and Scikit-learn. I am also eager to learn new skills and technologies, and to work with diverse and talented teams.