Faculty
Faculty List
Mr. N. V. S. Sai Pavan
M.Tech
Assistant Professor
CSE
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Educational Qualifications
- M.Tech in
Computer Science and Technology (2024β2026) β Gayatri Vidya Parishad
College for Degree & PG Courses, Andhra University (CGPA: 8.9/10.0).
- B.Tech in
Computer Science and Engineering (2020β2024) β Gayatri Vidya Parishad
College for Degree & PG Courses, Andhra University (CGPA: 7.20/10.0).
Professional Experience
- ο»ΏPresently Working
as Assistant Professor at MVGR College of Engineering (Autonomous) since
August 2026.
Research Experience
- Worked as a
Research Intern in Deep Learning and Computer Vision at the Naval Science
and Technological Laboratory (NSTL), Ministry of Defence, in 2023.
- Developed an
underwater object detection system using CNN and YOLO, achieving 90% mean
Average Precision (mAP) and real-time detection performance.
- Worked as an
Ethical Hacking and Cybersecurity Intern at Skills Uprise in 2025, gaining
practical experience in penetration testing, vulnerability assessment, and
secure web application development.
Publications and Research
Contributions
- Worked on a
research paper titled βPost-Quantum Secure Banking System using
CRYSTALS-Kyber and Dilithium with Facial Biometric Authentication.β
- Contributed
to research on post-quantum cryptography, quantum-resistant banking
security, facial recognition, and multi-factor authentication, integrating
CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital
signatures.
Research Projects
- Developed a
Post-Quantum Secure Banking Framework using CRYSTALS-Kyber and Dilithium,
incorporating quantum-resistant cryptography, facial biometric
authentication, liveness detection, and password-based fallback
authentication.
- Worked on
Industrial Safety Monitoring using Computer Vision as a B.Tech major
project, developing a real-time Personal Protective Equipment (PPE)
detection system using YOLOv8 and a Flask-based web application.
- Developed an
underwater object detection system using CNN, YOLO, image preprocessing,
and dataset augmentation during the NSTL internship.
Research Interests
- Interested
in Post-Quantum Cryptography, Artificial Intelligence, Deep Learning, Computer
Vision, Cybersecurity, Lattice-Based Cryptography, Secure Banking Systems, and
Multi-Factor Authentication.
Mr. N. V. S. Sai Pavan
M.Tech
Assistant Professor
CSE
Educational Qualifications
- M.Tech in
Computer Science and Technology (2024β2026) β Gayatri Vidya Parishad
College for Degree & PG Courses, Andhra University (CGPA: 8.9/10.0).
- B.Tech in
Computer Science and Engineering (2020β2024) β Gayatri Vidya Parishad
College for Degree & PG Courses, Andhra University (CGPA: 7.20/10.0).
Professional Experience
- ο»ΏPresently Working
as Assistant Professor at MVGR College of Engineering (Autonomous) since
August 2026.
Research Experience
- Worked as a
Research Intern in Deep Learning and Computer Vision at the Naval Science
and Technological Laboratory (NSTL), Ministry of Defence, in 2023.
- Developed an
underwater object detection system using CNN and YOLO, achieving 90% mean
Average Precision (mAP) and real-time detection performance.
- Worked as an
Ethical Hacking and Cybersecurity Intern at Skills Uprise in 2025, gaining
practical experience in penetration testing, vulnerability assessment, and
secure web application development.
Publications and Research
Contributions
- Worked on a
research paper titled βPost-Quantum Secure Banking System using
CRYSTALS-Kyber and Dilithium with Facial Biometric Authentication.β
- Contributed
to research on post-quantum cryptography, quantum-resistant banking
security, facial recognition, and multi-factor authentication, integrating
CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital
signatures.
Research Projects
- Developed a
Post-Quantum Secure Banking Framework using CRYSTALS-Kyber and Dilithium,
incorporating quantum-resistant cryptography, facial biometric
authentication, liveness detection, and password-based fallback
authentication.
- Worked on
Industrial Safety Monitoring using Computer Vision as a B.Tech major
project, developing a real-time Personal Protective Equipment (PPE)
detection system using YOLOv8 and a Flask-based web application.
- Developed an
underwater object detection system using CNN, YOLO, image preprocessing,
and dataset augmentation during the NSTL internship.
Research Interests
- Interested in Post-Quantum Cryptography, Artificial Intelligence, Deep Learning, Computer Vision, Cybersecurity, Lattice-Based Cryptography, Secure Banking Systems, and Multi-Factor Authentication.