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
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.
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
RSA 2020, San Francisco, CA | Experience 🙂
Experience of the "Human Element"!San Francisco, CA It was 1 am and I could not sleep because...
Prominent Face Image Datasets
There have been an ever-growing collection of face image datasets in the past decade and a...
CVPR 2019, Long Beach, CA | Experience 🙂
This was my first time attending one of the largest computer vision conferences, Conference...
Selected Media Coverage
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
