
Priyanka Manjunatha
@priyankamanjunatha
Cybersecurity student developing adaptive threat detection for simulated healthcare networks; experienced in IT administration at Wipro Technologies.
What I'm looking for
At Wipro Technologies, I administered Windows servers, Active Directory, and Group Policies. I also performed security updates, system monitoring, and troubleshooting to support secure IT operations.
I'm pursuing an M.Tech in Cyber Security at Bapuji Institute of Engineering and Technology, with a project developing an adaptive threat detection framework for a simulated healthcare network.
For my network traffic analysis project, I examined packets, TCP/IP communication, DNS queries, and unusual traffic patterns using Wireshark. I also developed an IoT-based facial access control system for secure, contactless entry.
As a Machine Learning Intern at Inventeron Technologies, I preprocessed datasets and built and tested predictive models using TensorFlow and Scikit-learn. I’m seeking to apply my practical technical skills in cybersecurity.
Experience
Work history, roles, and key accomplishments
Administered Windows servers, Active Directory, and Group Policies; performed security updates, system monitoring, and troubleshooting to support secure and reliable IT operations.
Machine Learning Intern
Inventeron Technologies
Feb 2024 - Mar 2024 (1 month)
Preprocessed datasets and built/tested predictive models using TensorFlow and Scikit-learn in PyCharm; reviewed model performance metrics.
Education
Degrees, certifications, and relevant coursework
Bapuji Institute of Engineering and Technology, Davangere
M.Tech, Cyber Security
2025 -
Grade: 84% (8.8 CGPA)
Pursuing M.Tech in Cyber Security with an expected graduation in May 2027. Achieved 84% (8.8 CGPA) so far.
Vidyavardhaka College of Engineering, Mysore
B.E., Electronics and Communication Engineering
2020 - 2024
Grade: CGPA: 7.0
Completed Bachelor of Engineering in Electronics and Communication Engineering with a CGPA of 7.0.
Sadvidya Semi Residential PU College
PUC, PCMB
2018 - 2020
Grade: 66.75%
Completed Pre-University Course in PCMB with 66.75%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Social media
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