Projects

🧠 Featured Projects

Recognized with Garmin’s Data & AI Innovation Award (2024) and Compliance Excellence Award (2024) for leadership in GenAI-driven compliance automation and EU RED readiness.

📊 Cloud-Native Data Compliance Lakehouse — Garmin International

Designed and implemented a secure, scalable AWS + Databricks Lakehouse for integrating telemetry, SBOM, and compliance datasets.
Enabled real-time analytics, traceability, and regulatory readiness across 250+ product lines.

Highlights:

  • Unified SAST, Pentest, and SBOM datasets for vulnerability intelligence and lifecycle tracking.
  • Automated data ingestion and lineage modeling using PySpark and Delta Lake.
  • Built governance dashboards in Tableau for executive compliance visibility.

Tech Stack: AWS Glue · Databricks · PySpark · Delta Lake · AWS Redshift · Tableau · EU RED / CRA Compliance

🤖 GenAI-Powered Data Insights & Compliance Automation — Garmin International

Built GenAI workflows using AWS Bedrock, OpenAI APIs, and LangChain to automate document comprehension and compliance mapping.
Reduced manual review effort by 40% and accelerated risk triage.

Highlights:

  • Trained LLM-based extractors for structured insights from vulnerability reports.
  • Deployed automation pipelines correlating telemetry and compliance data.
  • Integrated findings into a centralized compliance data lake.

Tech Stack: AWS Bedrock · OpenAI APIs · LangChain · Python · Databricks · Redshift · Delta Lake · CompTIA Frameworks

🧩 SBOM & Vulnerability Analytics Framework

Developed an enterprise-ready framework to generate and analyze Software Bills of Materials (SBOMs) using CycloneDX.
Mapped dependencies and vulnerabilities across multiple build systems (Waf, Zephyr, Android, Yocto).

Highlights:

  • Implemented automated compliance datasets for EU RED / CRA validation.
  • Integrated PySpark validation pipelines for data quality governance.
  • Established metadata-driven dashboards for leadership visibility.

Tech Stack: Python · PySpark · CycloneDX · AWS Glue · Databricks · Tableau

🔬 Research — DARPA STAC Program, Iowa State University

Contributed to DARPA’s Space/Time Analysis for Cybersecurity (STAC) initiative by developing static-analysis and ML-based vulnerability detectors.
Co-authored award-winning research in program analysis and security automation.

Highlights:

  • Built ML classifiers for identifying loop-based vulnerabilities in Linux kernel code.
  • Developed Python/C++ feature extraction pipelines for large-scale analysis.
  • Published and presented research at IEEE DySDoc3 (Madrid, Spain).

Tech Stack: Python · C/C++ · Machine Learning · Linux · Program Analysis

These projects represent my professional journey — from GenAI-driven data compliance at Garmin to static-analysis research at Iowa State University — uniting data engineering, cloud security, and AI into resilient, compliant systems.