Safwan Wshah
| Safwan Wshah | |
| Occupation | Computer scientist |
|---|---|
| Employer | University of Vermont |
| Alma mater | University at Buffalo, The State University of New York |
Safwan Wshah is a computer scientist at the University of Vermont, where he holds the rank of Associate Professor in the Department of Computer Science.[1] His research spans machine learning applications including cross-view geolocalization, power systems security, and biomedical prediction.[2]
Education
Wshah received his PhD in Computer Science and Engineering from the University at Buffalo, The State University of New York, completing the degree between 2008 and 2012.[3]
Career
Wshah has been affiliated with the University of Vermont since 2017, where he holds an appointment in the Department of Computer Science.[4]
Research
According to Semantic Scholar, Wshah has authored 39 papers that have collectively been cited 534 times, giving him an h-index of 11.[5] His publications include work on machine-learning-guided design of antimicrobial peptides, prediction of posttraumatic stress disorder risk, geometric disentanglement for cross-view geolocalization, deep learning detection of breathing patterns from wearable sensors, and detection of false data injection and GPS spoofing attacks in power systems.[6]
Wshah received a National Science Foundation award for a project titled "Collaborative Research: III: Toward Robust and Private Cross-view Geo-localization," totaling $678,422, administered through the University of Vermont & State Agricultural College.[7]
Selected publications
- "AMPGAN v2: Machine Learning Guided Design of Antimicrobial Peptides" (2021), Journal of Chemical Information and Modeling[8]
- "Predicting Posttraumatic Stress Disorder Risk: A Machine Learning Approach" (2019), JMIR Mental Health[9]
- "GeoDTR+: Toward Generic Cross-View Geolocalization via Geometric Disentanglement" (2023), IEEE Transactions on Pattern Analysis and Machine Intelligence[10]
- "Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning" (2020), Italian National Conference on Sensors[11]
- "Machine deep learning accurately detects endoleak after endovascular abdominal aortic aneurysm repair" (2020), JVS: Vascular Science[12]
- "Transformer-based deep learning model for forced oscillation localization" (2023), International Journal of Electrical Power & Energy Systems[13]
- "Detection and mitigation of GPS Spoofing Attacks on Phasor Measurement Units using deep learning" (2023), International Journal of Electrical Power & Energy Systems[14]
- "Accurate Detection of False Data Injection Attacks in Renewable Power Systems Using Deep Learning" (2021), IEEE Access[15]
- "ARTS: Automotive Repository of Traffic Signs for the United States" (2019), IEEE Transactions on Intelligent Transportation Systems[16]
- "A Machine Learning Approach to Identification of Unhealthy Drinking" (2020), Journal of the American Board of Family Medicine[17]
External links
- ↑ University of Vermont faculty records.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ ORCID record 0000-0001-5051-7719.
- ↑ ORCID record 0000-0001-5051-7719.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ National Science Foundation award records.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.
- ↑ Semantic Scholar author profile for Safwan Wshah.