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Prashnna Gyawali

Self-supervised Learning Foundation Models Out-of-distribution Detection AI Interpretability Trustworthy AI In Healthcare

About

I am an Assistant Professor at West Virginia University in the Lane Department of Computer Science and Electrical Engineering. Before my time at WVU, I completed my postdoctoral training at the Stanford University and earned my Ph.D. in Computer Science from RIT. My research focuses on building reliable and trustworthy AI systems with improved generalization and robustness, particularly in critical domains such as healthcare. I emphasize generalization (through self-supervised learning and foundation models), reliability (via out-of-distribution detection), and trustworthiness (through interpretability) as key pillars of my work.

Research Performance Summary

73
Total Papers
1200
Total Citations
18
H-Index
2014-2026
Active Research Span

First Recorded Paper

A Final Year Project Report on Vehicle Over Speed Detection and Recognition

Year: 2014

Citations: 2

Venue: Doctoral dissertation, Tribhuvan University, Kirtipur, Nepal

Latest Recorded Paper

Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare

Year: 2026

Citations: 0

Venue: arXiv preprint arXiv:2602.04416

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
2
2025
17
2024
15
2023
4
2022
5
2021
6
2020
8
2019
5
2018
5
2017
3
2015
2

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 32
Journal 6
Book 2

Top Coauthors

Gyawali Wang

Research Impact by Period

2025-2026

Period Stats
Papers 19
Citations 57
Avg. Citations / Paper 3
H-Index 4

2020-2024

Period Stats
Papers 38
Citations 646
Avg. Citations / Paper 17
H-Index 14

2015-2019

Period Stats
Papers 15
Citations 495
Avg. Citations / Paper 33
H-Index 9

2010-2014

Period Stats
Papers 1
Citations 2
Avg. Citations / Paper 2
H-Index 1

Contact and Professional Links

Contact Information

prashnna.gyawali@mail.wvu.edu

Detected Research Keywords

Multimodal Federated Learning Localizing Origin Ventricular 12 Lead Electrocardiograms Semi Supervised Learning Material Property Prediction Analysis Machine Learning Out Distribution Detection Inverse Imaging Cardiac Imaging Cardiac Transmembrane Cardiac Transmembrane Potential