Nandakishor Dakka

GPA: 4.0 / 4.0

Coursework

Data Structures & Algorithms · Computer Systems · System Design

Organizations

GreyHat (Cybersecurity) · GTXR · S&TPC · Competitive Programming @ GT · Vertically Integrated Projects

Honors

FBLA Network Design/MIS National Champion · National Cyber League (Top 1%) · GIAC Advisory Board · National Cyber Scholar with Honors · University of North Georgia Cyber Excellence Scholar with Honors

• Engineering and optimizing ML-driven fraud detection models using Python and TypeScript to increase identification of anomalous transaction patterns and decrease false-positive alerts.
• Developing automated role-creation pipelines to evaluate IAM configuration integrity, strengthening least-privilege across cloud-native microservices.
• Implementing Policy-as-Code guardrails within CI/CD pipelines, automating misconfiguration detection to ensure continuous compliance prior to production deployment.

• Optimized modular SOAR orchestration logic within Tines using Python, reducing Mean Time to Remediate by 30% through event-driven automation.
• Designed a Detection-as-Code framework aligned with MITRE ATT&CK, authoring 15+ high-fidelity YAML detection rules with automated validation tests.
• Architected a high-performance Windows Event Log forwarder in C#, optimizing SIEM ingestion for 40+ production machines while interfacing with AWS and OCI APIs.

• Deployed technology infrastructure to new and existing schools; maintained computer labs.
• Utilized Microsoft Active Directory for user and group management.

• Building a high-availability nationwide database to ingest and standardize utility telemetry for resilient power system monitoring against extreme weather events.
• Developing a scalable data pipeline using AWS CloudWatch and web-scraping to facilitate ML-driven analysis of socio-economic vulnerability during outages.

• Engineered YARA-based detection logic to hunt for AI-driven malware, successfully identifying 10+ malicious samples within VirusTotal datasets.
• Performed static and dynamic analysis to reverse 5+ info-stealing samples using IDA Pro, Python, and Angr, producing 4 detailed technical reports summarizing malware behavior and IOCs.

• Developed a Python-based orchestration framework integrating an LLM with security tools (GDB, Ghidra), sponsored by Georgia Tech's SSLab, enabling automated program analysis.
• Benchmarked against real-world CTF challenges in pwn, web, and reverse engineering — consistently 5× faster than a human solver.

• Built a custom malware sandbox leveraging the Libvirt API for VM isolation, enabling programmatic detonation and analysis of untrusted binaries.
• Developed a systems-level telemetry engine to monitor process lifecycle, filesystem mutations, and network socket activity for post-detonation behavioral analysis.

• Analyzed the arms race between synthetic media generation and detection, identifying critical vulnerabilities across 16 U.S. infrastructure sectors.
• Formulated a three-pillar federal intervention framework including mandated algorithmic transparency and creation of an AI-Disinformation Observatory.
• Selected for conditional acceptance by the Journal of Science Policy & Governance (JSPG) following competitive peer review.