Krishnapriya K S

Assistant Professor

kkottakkalsugath{at}valdosta{dot}edu | GA, U.S.A

Department of Computer Science,
Valdosta State University, Valdosta, GA 31698

Welcome to KP’s note 

I am an Assistant Professor in the Department of Computer Science at Valdosta State University. I received the Ph.D. degree in Computer Science from Florida Institute of Technology, Melbourne, FL, USA. I worked as a Postdoctoral Research Associate in the Identity Lab at Florida Tech. Before joining Florida Tech, I completed Master’s degree and Bachelor’s degree in Computer Science and worked as an Assistant Professor in the Computer Science department.

My research is primarily focused on face recognition with an objective to characterize the face recognition accuracy relative to demographic factors and provide mitigation strategies to improve it.

“Imagination will often carry us to worlds that never were. But without it we go nowhere.”

Carl Sagan

Research Interests

Biometrics

Computer Vison

Pattern Recognition

Machine Learning

Cybersecurity

Education

 

  • PhD in Computer Science – 2021
    Florida Institute of Technology
  • M.Tech in Computer Science – 2016
    Rajiv Gandhi Institute of Technology (RIT)
  • B.Tech in Computer Science – 2014
    SCMS School of Engineering and Technology 

Work Experience

  • Assistant Professor in Computer Science – Present
    Valdosta State University
  • Research Associate II – 2021
    Florida Institute of Technology
  • Graduate Research Assistant – 2021
    Florida Institute of Technology
  • Assistant Professor in Computer Science – 2017
    Sahrdaya College of Engineering and Technology
  • Teaching Assistant in Computer Science – 2016
    Rajiv Gandhi Institute of Technology (RIT)

Paper Publications

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Journal Publications

  • Krishnapriya K. S., Vítor Albiero, Kushal Vangara, Michael C. King, and Kevin W. Bowyer. “Issues related to face recognition accuracy varying based on race and skin tone.” IEEE Transactions onTechnology and Society 1, no. 1, pp. 8-20. 2020.
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Paper Publications

  • Krishnapriya K. S., Kushal Vangara, Michael C. King, Vitor Albiero, and Kevin Bowyer. “Characterizing the variability in face recognition accuracy relative to race.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 0-0. 2019.

  • Albiero, Vítor, Krishnapriya K. S., Kushal Vangara, Kai Zhang, Michael C. King, and Kevin W. Bowyer. “Analysis of gender inequality in face recognition accuracy.” In Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops, pp. 81-89. 2020.
  • Krishnapriya K. S., “Denoising of fingerprint images by exploring external and internal correlations,” 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), Chennai, 2017, pp. 1-6, doi: 10.1109/ICCCSP.2017.7944056.

Recent Blogs

Selected Media Coverage 

As Cameras Track Detroit’s Residents, a Debate Ensues Over Racial Bias
Report indicates facial biometric accuracy improving but image quality could help further
Study urges reappraisal of alleged racial bias in face recognition
The Feds May Be Peeking at Your Driver's-License Photo, and You Can't Do Anything about It
Issues of bias in facial recognition technology need further study, Notre Dame expert says

Research

Variability in Face Recognition

Variability in Face Recognition Accuracy Relative To Race

Face Recognition Relative to Gender

Assessment of Gender Inequality in Face Recognition Accuracy

Skin Tone Influence on Face Recognition

Issues Related to Face Recognition Accuracy Varying Based on Skin Tone

KP's note
KP's note