role: Full Stack Software Engineer
education: 
  - BS Computer Science
  - MS Cyber Security (In Progress)
specialties:
  - Cloud Infrastructure & AWS
  - Machine Learning & AI
  - Systems Security
  - Systems Programming

Production-grade over-the-air firmware update engine for distributed embedded fleets

• Built C++17 client daemon with strict 8-state machine managing the full update lifecycle from idle through automatic rollback
• Implemented cryptographic verification pipeline using OpenSSL - SHA-256 hashing and RSA signature validation rejects tampered packages before a single byte is applied
• Delta patch system using bsdiff reduces bandwidth by downloading only what changed between firmware versions
• Rollback engine snapshots firmware pre-update and restores automatically on health check failure with zero manual intervention
• Integrated AWS IoT Core MQTT, S3 artifact storage, DynamoDB fleet state tracking, Lambda rollout controller, and SNS alerting
• Staged canary rollout halts automatically when fleet failure rate exceeds configurable threshold
• Recall tracking system - per-device remediation records with regulatory-grade auditability

End-to-end telemetry platform for monitoring aerospace embedded systems in real time

• C++ agent implements AWS Signature Version 4 from scratch using libcurl and OpenSSL to ship metrics directly to Kinesis
• Dual anomaly detection - threshold and z-score statistical analysis runs on every telemetry record in Lambda
• Node.js API with WebSocket support feeds a live React dashboard with alert management across a 10-device simulated fleet
• DynamoDB with 12-hour TTL auto-expiry keeps storage costs near zero at scale

Automotive intrusion detection combining rule-based engines with ML-powered anomaly analysis

• 5 rule-based detection engines plus Isolation Forest ML model achieving 86% detection accuracy
• Deployed ML from Python training to embedded C inference with zero external dependencies and under 1ms processing per frame
• Detected 23 attacks that bypassed traditional signature-based detection through statistical timing pattern analysis

Automotive CAN 2.0B network simulator with multi-ECU communication and real-time diagnostics

• 4 ECUs with priority-based message arbitration, collision detection, and diagnostic trouble code management
• Embedded systems concepts: circular buffers, state machines, binary protocols, timing-driven execution

Cloud security lab demonstrating real-world attack chains in misconfigured AWS infrastructure

• SSRF exploitation, IMDSv1 abuse, IAM credential theft, and lateral movement across segmented VPC
• End-to-end intrusion chain across DMZ, Internal, and Restricted tiers