North Haven, Connecticut, United States
I’m a Security Engineer focused on building and securing real-world systems across cloud, enterprise, and high-risk environments. My work centers on AWS cloud security, threat detection, and incident response, with hands-on experience designing and improving security controls that reduce real operational risk. I’ve supported security efforts across government, healthcare, academic, and small-business environments, working directly with infrastructure, identity, and detection systems. I bring a strong background in applied cybersecurity research, particularly in AI-driven threat detection, phishing and malware analysis, and adversarial use of large language models. That research informs how I approach security engineering: practical, measurable, and built for scale. I’m especially interested in Security Engineer roles where cloud security, detection engineering, automation, and modern defense strategies are core responsibilities. I work best in environments that value clear thinking, strong engineering fundamentals, and security solutions that actually get deployed.
Developing and prototyping AI-powered solutions to enhance digital productivity and data protection. Integrate security-by-design principles into all phases of software and AI tool development. Collaborating with cross-functional teams to design and implement real-time threat detection, encryption, and secure authentication mechanisms in our apps. Analyze emerging cybersecurity threats in AI systems and advise on mitigation strategies aligned with NIST and OWASP guidelines. Contribute to the creation of ethical AI frameworks that ensure user safety, privacy, and compliance with evolving cybersecurity regulations. Supporting iSenseHUB’s mission to enhance productivity and innovation through advanced technology.
KECCAL, Knowledge & Ethical Cybersecurity, Computing, AI & Law, a cybersecurity clinic focused on helping small businesses, nonprofits, educational institutions, community organizations, and underserved communities improve their digital resilience. The clinic began in 2023 as a community-focused cybersecurity initiative shaped by student involvement, local service needs, and early engagement with Connecticut organizations. It is now being formally developed to connect practical cybersecurity services, AI governance, cloud security, applied research, workforce development, and supervised experiential learning. As Founder, I lead the clinic’s vision, partnerships, service development, student training model, and community engagement. The vision is to grow KECCAL into a leading university-connected cybersecurity, computing, AI, and law clinic that begins in Connecticut and expands its impact across New England and the United States.
Designed, built, and secured AWS-based cloud environments supporting cybersecurity labs and applied research, reducing operational issues by 93% and cutting costs by $15,000. Implemented cloud security controls, including IAM policies, access management, logging, and monitoring to improve system reliability and security posture. Developed and evaluated AI- and ML-based threat detection systems, including phishing and malware detection models achieving up to 97% accuracy. Performed threat modeling, vulnerability analysis, and security testing across networked and cloud-based systems. Analyzed security logs and attack patterns to identify anomalies, misconfigurations, and potential threats. Supported incident response style investigations for simulated and real-world security scenarios in lab and enterprise-aligned environments. Contributed to detection engineering and defense-in-depth strategies for emerging technologies, including intelligent systems and next-generation networks. Collaborated with faculty, students, and security stakeholders to translate research findings into practical security engineering solutions.
Supported incident response operations, including investigation of security alerts, access anomalies, and potential compromise events across enterprise systems. Conducted vulnerability assessments and penetration testing, identifying weaknesses and recommending remediation actions to reduce attack surface. Performed continuous monitoring of security controls, logs, and alerts to detect threats, misconfigurations, and policy violations. Maintained and updated the enterprise security risk register, tracking risks, impacts, likelihoods, and remediation status in alignment with governance and compliance requirements. Assisted with security audits and control validation, ensuring adherence to regulatory and internal security standards. Contributed to business continuity and disaster recovery planning, helping align technical recovery procedures with organizational resilience goals. Collaborated with IT, security, and compliance teams to improve incident readiness, response workflows, and security posture. Documented incidents, findings, and corrective actions to support post-incident analysis and continuous security improvement.
Led AI-driven security engineering research focused on protecting 5G and massive MIMO systems, addressing vulnerabilities relevant to critical infrastructure and high-availability environments. Designed and evaluated physical layer security (PLS) mechanisms using machine learning to reduce attack surfaces and improve system resilience by up to 98%. Applied deep reinforcement learning techniques to improve system performance and reliability while reducing attack feasibility and iteration overhead. Analyzed threat models and adversarial scenarios impacting wireless and distributed systems, translating findings into defensive security strategies. Contributed to phishing detection and threat analysis research, achieving up to 97% detection accuracy using optimized ML models. Collaborated with multidisciplinary teams to integrate AI-based security controls into next-generation network architectures. Documented security findings and mitigation strategies to support defensive system design and secure deployment of advanced technologies.