Prashnna Gyawali

Prashnna Gyawali serves as an Assistant Professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University's Benjamin M. Statler College of Engineering and Mineral Resources. His research centers on developing trustworthy AI systems for healthcare applications, with emphasis on unbiased methodologies and clinical translatability.

His academic credentials include:

• Ph.D. in Computing and Information Sciences from Rochester Institute of Technology (2021)
• B.E. in Electronics and Communication from Institute of Engineering (Pulchowk Campus), Tribhuwan University (2014)

Gyawali's research program investigates fundamental challenges in healthcare AI, particularly focusing on algorithmic fairness in diagnostic systems, interpretable neural architectures for clinical decision support, and multimodal fusion techniques integrating medical imaging with electronic health records. His work addresses critical gaps in deploying AI solutions that maintain equity across diverse patient populations while providing clinicians with transparent reasoning processes.

Prior to his faculty appointment, he completed postdoctoral training at Stanford University School of Medicine, where he developed AI frameworks for medical image analysis and clinical predictive modeling.