University at Albany · Undergraduate Cybersecurity Researcher
Building expertise in Network Defense, Zero Trust Architecture, Cryptography, Threat Intelligence, and IoT security through active research at the Center for Computational Research and hands-on security projects.
I'm a cybersecurity student and undergraduate researcher at University at Albany with a passion for protecting digital assets and understanding the evolving threat landscape. Through my work at the Center for Computational Research and Interships, I'm developing hands-on expertise in Zero Trust Architecture, IoT security, Cryptography, Threat Intelligence, and AI-assisted malware analysis — translating academic research into practical security insights.
I am currently preparing for two certifications — the Google Cybersecurity Certificate (expected April 2026) followed by CompTIA Security+ (expected May 2026) — that certify knowledge in threat analysis, cryptography, identity management, and security operations.
My long-term focus areas include penetration testing, AI governance, cloud security, and security operations, with a particular interest in how modern network architectures and AI-driven tooling can better defend against emerging threat vectors.
Bachelor's in Cybersecurity — coursework in network security, cryptography, security operations, and risk management through hands-on projects.
Completing hands-on security projects: network infrastructure design, vulnerability assessments, incident response simulations, and system hardening exercises.
Researching Zero Trust Architecture and IoT security at the Center for Computational Research, building experimental testbeds and analyzing real-world device traffic and threat scenarios.
Studying AI-assisted ransomware detection at the CAFE Lab, building malware analysis environments with Cuckoo Sandbox and analyzing behavioral patterns across ransomware families.
Analyzing kernel-level anti-cheat systems to understand how cryptographic integrity checks and trust mechanisms are used to prevent tampering and unauthorized code execution in Windows environments.
Foundational certification covering security fundamentals, network security, Linux, SQL, Python automation, and SIEM tools.
Preparing to validate skills in threat management, cryptography, identity & access management, and security operations.
As an undergraduate researcher at a UAlbany's lab, I investigate how Zero Trust Architecture principles can reduce the attack surface of IoT devices operating in mixed or legacy network environments. The research builds an experimental testbed using Kali Linux, Wireshark, Nmap, and the WiFi Pineapple to simulate adversarial techniques and evaluate the impact of micro-segmentation on device exposure and attack success rates.
A core focus is the ASUS Zenbo IoT robot and analyzing its communication patterns, traffic flows, and resilience against MITM interception and unauthorized access under various Zero Trust policy configurations. Findings contribute to a broader understanding of how Zero Trust network design can prevent cascading failures caused by compromised IoT devices in real-world deployments.
At the Cognitive Security, Accountability, Fairness & Explainability (CAFE) Lab, I research how AI techniques can support ransomware detection in enterprise environments. The work involves analyzing ransomware behavior to identify patterns that distinguish malicious activity from normal system operations with a focus on building a foundation for machine learning-assisted detection pipelines.
To support the research, I built a controlled malware analysis environment using Ubuntu virtual machines and Cuckoo Sandbox, allowing ransomware samples to execute safely while capturing behavioral indicators like file modifications, process creation, registry changes, and network activity. A current focus is the recently observed 01Flip ransomware; comparing its encryption patterns, persistence techniques, and network behavior against known ransomware families to understand how emerging variants evolve and where earlier detection might be possible.
This research project examines kernel-level security mechanisms employed by modern anti-cheat systems, with a focus on how cryptographic techniques are applied to enforce software integrity and prevent unauthorized code execution. Using a Windows virtual machine environment with Visual Studio and the Windows Driver Kit (WDK), I analyze open-source anti-cheat frameworks and kernel drivers to understand how they implement cryptographic verification, secure memory validation, and trust enforcement at the operating system level.
Through reverse engineering and structured code analysis, the research evaluates how cryptographic primitives and integrity checks establish trust between user-mode applications and kernel-mode drivers. The goal is to understand how cryptographic trust models operate at the OS level and how these same principles can be applied more broadly to strengthen system security and prevent tampering or unauthorized modification in production environments.
Produced a structured intelligence assessment analyzing the strategic threat posed by AI-generated deepfakes across financial institutions, political communication, and public trust. The report applies a formal intelligence methodology which includes key judgments, confidence assessments, and sourced substantiation to evaluate trends from 2020–2025 and project forward-looking risks through 2028.
Conducted comprehensive vulnerability assessments on virtual oil rig environment using industry-standard tools. Documented findings and provided remediation recommendations following NIST framework guidelines.
Analyzed Stuxnet incident with a focus of AI assisted tools and threat modeling (MITRE ATT&CK) to determine best practices for future application of cybersecurity practices.
CDO is University at Albany's premier cybersecurity club, dedicated to teaching students real-world security skills through weekly workshops, team-based competitions, and hands-on server infrastructure projects. Members engage in both offensive and defensive security disciplines which includes red teaming, blue teaming, digital forensics, and network defense. The club competes in multiple CTF and cyber competitions throughout the year and hosts its own event, GDDC. CDO also runs certificate study groups to help members prepare for industry credentials like CompTIA Security+.
Won a multi-discipline cybersecurity competition combining OSINT, digital forensics, and network analysis. Teams raced to complete a series of technical challenges across investigation, intelligence gathering, and network problem-solving. First team to complete all tasks wins. Placed first against all competing teams.
Earned a place on the Dean's List at the University at Albany for both the Spring 2025 and Fall 2025 semesters, recognizing outstanding academic performance and a demonstrated commitment to excellence in the Cybersecurity program.
Student at the University at Albany, a nationally designated National Center of Academic Excellence in Cyber Defense (CAE-CD); a program jointly sponsored by the NSA and DHS. This designation recognizes institutions meeting rigorous federal standards in cybersecurity education, and reflects the depth and quality of the academic environment in which this work is conducted.
Developed a cybersecurity research showcase poster analyzing the Stuxnet malware and its impact on industrial control systems(ICS). The project examnied how the malware targeted Siemens PLC controllers and manipulated centrifuge operations while masking malicious activity from systems. The analysis highlighted how AI-assited security tools and anomaly detection could help identify unsual system behavior earlier and potentially prevent similar attacks.
Looking for cybersecurity full time opportunities and ways to contribute to security teams. Feel free to reach out anytime.