Narsi Reddy

About Me:

Sai Narsi Reddy, Donthi Reddy, is a Ph. D. candidate at UMKC currently working on Deep Learning applications in mobile ocular biometrics. His research also includes multi and single frame image enhancement and generalizable feature extraction methods to improve ocular biometrics. He received the Biometric and Forensics Best Paper Award at IEEE Homeland Security Technologies Symposium in 2017.


University of Missouri-Kansas City, Kansas City — Ph.D.
2016 - PRESENT
Research on applications of deep learning in mobile biometrics.
University of Missouri-Kansas City, Kansas City — MSEE
2014 - 2020
Masters in Electrical Engineering with majors in signal processing and machine learning.
Jawaharlal Nehru Technological University, Hyderabad, India — B.Tech
2009 - 2013
Bachelor of Technology (B.Tech.) Electronics and Communications Engineering.

Work Experience:

Jabra , Cupertino — AI/ML Researcher.
Feb 2021
  • AI/ML applications for Embedded video devices..
Zoloz (formerly EyeVerify Inc.), Kansas City — Research Internship.
Jun-Aug 2017 & Jan 2018 - Jan 2021
  • Image enhancement techniques such as super-resolution, denoising, blur models, and illumination normalization techniques for mobile ocular biometrics.
  • Deep Learning-based feature extraction and matching for biometrics.
  • Face and partial face localization and attribute analysis.
  • Biometrics system analysis.
University of Missouri-Kansas City, Kansas City — Research Assistant.
Jul 2015 - Dec 2017
  • Research in image enhancement and segmentation algorithms for ocular images.
  • Efficient deep learning model mobile ocular biometrics.
  • Soft biometrics applications in the face and ocular biometrics.