Safwan Wshah
Associate Professor, Department of Computer Science
Affiliate, Gund Institute for Environment
Innovation E417
82 University Place
Burlington, VT 05405
United States
- Ph.D., Computer Science and Engineering - SUNY Buffalo
Department of Computer Science
Gund Institute for Environment
Areas of expertise
Machine Learning, Image & Video Processing, Deep Learning, Pattern Recognition, Computer Vision, Document Imaging & Digital Signal Processing.
BIO
Wshah joins UVM CEMS from PARC (Palo Alto Research Center)- A Xerox company, where he worked as a research scientist in the fields of machine learning/deep learning, computer vision, and image/ video processing. Dr. Wshah holds a Ph.D. in Computer Science and Engineering from SUNY-Buffalo. He received nineteen issued U.S. patents and has authored 25 conference and journal publications. He is currently investigating machine learning algorithms to be applied in Energy, Transportation and Healthcare fields.
Courses
- CS 3540 - Machine Learning
- CS 6990 - Deep Learning
Bio
Wshah joins UVM CEMS from PARC (Palo Alto Research Center)- A Xerox company, where he worked as a research scientist in the fields of machine learning/deep learning, computer vision, and image/ video processing. Dr. Wshah holds a Ph.D. in Computer Science and Engineering from SUNY-Buffalo. He received nineteen issued U.S. patents and has authored 25 conference and journal publications. He is currently investigating machine learning algorithms to be applied in Energy, Transportation and Healthcare fields.
Courses
- CS 3540 - Machine Learning
- CS 6990 - Deep Learning
Publications
Selected Publications:
- S. Wshah, N. Chaube, C. Skalka and M. Price, Machine Learning Methods for
Post Traumatic Stress Disorder Patient Prediction, to be Submitted to Journal
of Biomedical and Health Informatics. In press, 2019. - S. Hahn, J. Allison, R. Watts, S. Wshah, Automatic Deep Learning Based
Cervical Spinal Fracture Diagnosis, submitted to IEEE International Symposium
on Biomedical Imaging (ISBI), 2019. - S. Hamshaw, D. Denu, M. Holthuijzen, S. Wshah, and D. Rizzo, Automating the
Classification of Hysteresis in Event Concentration-Discharge Relationships,
poster submitted to SedHyd conference, 2019. - Applying Deep Learning to Event Concentration-Discharge Hysteresis Patterns
to Reveal Differences in Sediment Dynamics across Contrasting Watersheds, SD
Hamshaw, D Denu, MM Dewoolkar, M Holthuijzen, S Wshah, D Rizzo, AGU Fall
Meeting, 2018. - L. Bonnell, B. Littenberg, S. Wshah, G. Rose, Automated identification of
unhealthy drinking using routinely collected data: A machine learning
approach, accepted poster to APHA 2018.