SWE • AI • Cybersecurity

Building practical AI systems for security, automation, and real-world impact.

Computer Engineering graduate from Virginia Tech (May 2025), currently driving industrial AI and OT-security automation at TMELC.

About

I build data-driven products where AI meets reliability: RAG systems, reinforcement learning security tools, and telemetry-aware dashboards. My recent work spans industrial anomaly detection, 5G/O-RAN fuzz testing, and full-stack ML experiences.

Python LangChain PyTorch Cybersecurity RAG Industrial AI

Education

Virginia Tech

Master's in Computer Engineering · Graduated May 2025 · GPA: 3.80/4.0

Birla Vishvakarma Mahavidyalaya

Bachelor's in Electronics and Communication Engineering · Aug 2019 - May 2023 · CPI: 3.60/4.0

Experience

TMELC, USA · Process Automation Engineer

  • Developing AI models for anomaly detection and predictive maintenance in OT systems.
  • Building Python telemetry pipelines for industrial time-series forecasting.
  • Supporting security teams with behavior analytics in industrial environments.

Commonwealth Cyber Initiative & Booz Allen · Graduate Research Assistant

  • Designed RL-based fuzzers using Q-learning for 5G/O-RAN message testing.
  • Built encoder/decoder validation tools for protocol-level testing.
  • Identified vulnerabilities across ORAN workflows in lab environments.

Indian Space Research Organization (SAC), India · Researcher

  • Developed automated hardware harness testing with Python, Raspberry Pi, and Zigbee.
  • Integrated multi-device controls for real-time monitoring and validation.

Projects

Live demos and repositories for recent and highlighted work.

Open Source

LlamaFarm

Developer-experience enhancements and debugging contribution work.

Publications

Reinforcement Learning-Based Fuzzer for 5G RRC Security Evaluation (IEEE Access, 2026)

RL-driven fuzzing framework for security evaluation of 5G RRC workflows.

Read Paper

5G/O-RAN Security Automated Testing (MILCOM, 2024)

Automated testing architecture for 5G/O-RAN security validation.

Read Paper

Adaptive Reinforcement Learning-Based Fuzzer for 5G RRC Security Evaluation (Virginia Tech, 2025)

Master's thesis detailing adaptive RL strategy design for 5G protocol fuzzing.

View Thesis

Contact & Credentials

Open to software engineering, AI, and cybersecurity opportunities.