Dr. Prashnna K Gyawali is an Assistant Professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University. His research operates at the intersection of machine learning and healthcare, developing robust and fair AI models that address real-world medical challenges. He earned his PhD in Computing and Information Sciences from Rochester Institute of Technology and completed his Bachelor of Engineering at IOE Pulchowk Campus, Nepal. During his doctoral studies, he gained practical experience through internships at Google Health and Verisk Analytics. Dr. Gyawali's research emphasizes enhancing model generalizability across diverse patient populations, particularly focusing on underserved communities. He has authored over 20 peer-reviewed research articles published in premier venues including ICLR, ICDM, MICCAI, IPMI, and journals such as Nature Medicine, Nature Communications, and Nature Communication Biology. His work has been supported by prestigious funding sources including WVHPEC, DARPA, and NSF CITeR. At NAAMII, he contributes to advancing AI research relevant to resource-constrained healthcare settings.