Computer Science undergraduate (PES University, 2027) with hands-on experience applying machine learning to RF data, including an adversarially robust LoRa fingerprinting pipeline on raw IQ samples that achieved over 0.90 AUROC. Experience in anomaly detection, NLP-based text classification and log-driven security monitoring, backed by software engineering skills in Python, Git, CI/CD and cloud platforms (AWS, Azure). Research paper submitted to Applied Intelligence.
Experience
Research Intern
BITS Pilani, Hyderabad · Hyderabad, India
Jun 2026 – Aug 2026 · 2 mo
• Implemented an adversarially robust LoRa RF fingerprinting pipeline in Python/PyTorch for IoT device authentication, using contrastive self-supervised learning and a hybrid anomaly detection framework on raw IQ samples • Evaluated the pipeline against FGSM, BIM, PGD, and C&W attacks using a physically calibrated adversarial evaluation methodology, achieving over 0.90 AUROC across adversarial and synthetic rogue-device (anomaly) detection
Teaching Assistant – Computer Networks
PES University · Bengaluru, India
Jan 2026 – May 2026 · 4 mo
Software & Cybersecurity Intern
Statnetics (CloudQA) · Hyderabad, India
Jun 2025 – Aug 2025 · 2 mo
• Performed web application security assessments using OWASP methodologies, identifying and remediating vulnerabilities and tracking risk through to resolution • Developed and deployed a full-stack DemoSaaS application (React, Node.js, MongoDB) simulating real-world customer workflows for the CloudQA automation testing platform • Hosted test environments on AWS and Azure
Education
B.Tech Computer Science & Engineering
PES University
2023 – 2027
Skills & stack
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