Cybersecurity Professional
Master's student in Computer Science at The Ohio State University with a focus in Systems and Network Security. Open to full-time opportunities starting May 2026 and available for internships.
Network forensic automation tool with live analysis capability that parses PCAP files to generate interactive topology graphs. Features automated ISP geolocation, color-coded malicious actor identification via AbuseIPDB API integration, and real-time Zeek log analysis.
Advanced threat intelligence platform featuring automated malicious IP detection and email alerting system. Implements intelligent API fallback mechanisms and comprehensive reporting. Collaborative project with formal setup and final reports demonstrating enterprise-level documentation.
Python-based automation tool that dynamically generates Suricata blocking rules by querying threat intelligence APIs. Identifies malicious IPs and creates IPS rules for real-time network protection. Featured in published Medium article with complete setup guide.
Deployed a Hybrid ELK (HELK) stack to simulate an enterprise SOC environment. Configured ElastAlert to detect Active Directory attacks (e.g., Zerologon) via log correlation, enabling proactive threat hunting and incident response.
Built a machine learning model for malware classification into families using Convolutional Neural Networks (CNN). Trained on static features extracted from PE, ELF files to identify and categorize malware specimens.
Clustered PE, ELF based malware families using static feature extraction with the EMBER pipeline, then applied K-Means and DBSCAN to group samples for triage and label enrichment. Built analysis notebooks to explore feature importance and cluster quality.
Industry-standard tools and frameworks for enterprise security
Open to full-time opportunities starting May 2026 | Available for internships
Ready to move faster on detection and response?