Associate Professor, Computer Science

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.


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.


Areas of Expertise and/or Research

Machine Learning, Image & Video Processing, Deep Learning, Pattern Recognition, Computer Vision, Document Imaging & Digital Signal Processing.


  • Ph.D., Computer Science and Engineering - SUNY Buffalo


  • 802-656-8086
Office Location:

Innovation 417

Courses Taught

  • CS254 - Machine Learning
  • CS395 - Deep Learning