Guy C. Hembroff
دانشیار · Human Health-focused Machine Learning/Deep Learning
Michigan Technological Universityمعرفی
Dr. Guy C. Hembroff is an Associate Professor in the College of Computing at Michigan Technological University (MTU), serving as Graduate Program Director for the MS in Health Informatics and PhD in Computational Science and Engineering programs. He holds a PhD in Computational Science and Engineering from MTU, alongside an MPA in Public Administration (Northern Michigan University) and a BS in Finance and Economics (MTU). His research focuses on human health applications of machine learning, computer vision, cybersecurity, and medical device innovation, particularly in areas like medical image analysis and mHealth solutions. He leads the Biomedical Data Science (BDS) Lab, a multidisciplinary team addressing pressing healthcare challenges through AI-driven solutions.
- Education:
- PhD, Computational Science and Engineering, Michigan Tech
- MPA, Public Administration, Northern Michigan University
- BS, Finance and Economics, Michigan Tech
Research Interests: Dr. Hembroff’s work spans healthcare AI (deep learning, medical image segmentation, generative AI), cybersecurity for healthcare systems, and biometric development. His lab collaborates with medical institutions to advance disease surveillance, healthcare interoperability, and secure patient data systems. Recent projects include automated quality control of radiographs and blockchain-based patient data auditing.
Advising & Grants: Advises four PhD students on topics like medical image segmentation, mental health intervention modeling, and privacy-preserving LLMs. His work integrates clinical, engineering, and cybersecurity expertise to drive practical healthcare solutions. While specific grant details are not listed, his research emphasizes translational applications in global health equity and rural healthcare access.
Labs/Teams: The BDS Lab combines clinical informatics, AI, and cybersecurity to innovate in areas such as medical device development and health data security. Current projects include blockchain for secure patient data and AI-driven mHealth tools for underserved regions.
