Highly accomplished AI and Cybersecurity professional with a strong research background and practical expertise in developing advanced multimodal AI models, securing enterprise applications, and conducting in-depth vulnerability assessments. Proven ability to innovate at the intersection of AI and security, evidenced by significant publications and hands-on experience in intrusion detection, penetration testing, and system hardening. Eager to leverage a unique blend of machine learning, data science, and robust cybersecurity skills to drive impactful research and development in cutting-edge environments.
Application Development Associate / Analyst – Maximo Developer
Chennai, India, India
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Summary
Spearheaded the development and security of enterprise-scale applications and automation workflows for large operational deployments, integrating advanced security practices and database solutions within Agile frameworks.
Highlights
Engineered and secured enterprise applications and automation workflows with Java, Python/Jython, and IBM Maximo, optimizing operational deployments for asset, work order, and inventory management.
Implemented robust encryption and access control mechanisms within application workflows, ensuring compliance with audit requirements and protecting sensitive data.
Designed and deployed critical system customizations, including UI enhancements, validations, business rules, and BIRT reporting pipelines, to enable KPI tracking, enhance asset performance monitoring, and ensure maintenance compliance.
Optimized data retrieval and processing by integrating enterprise applications with Oracle databases, developing complex SQL queries and procedures for cross-functional Agile teams.
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MS
Digital Forensics and Cybersecurity - Cyber Operations
Grade: 4.0 GPA
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BE
Computer Science and Engineering
Grade: 3.37 GPA
Awarded By
University at Albany, SUNY
Achieved 4th place in a competitive Capture The Flag event, demonstrating advanced practical skills in penetration testing, vulnerability analysis, and incident response.
Awarded By
University at Albany, SUNY
Recognized for outstanding academic achievement in the Master of Science program.
Awarded By
TryHackMe
Achieved OMNI rank by completing over 100 cybersecurity labs and CTFs, showcasing hands-on expertise in exploitation, enumeration, and red/blue teaming, with continuous learning in advanced offensive and defensive topics.
Awarded By
Computer Society of India
Organized events for the Computer Society of India during undergraduate studies.
Published by
IEEE Transactions on Affective Computing (manuscript in preparation)
Summary
Co-authored a manuscript detailing an explainable multimodal framework for depression detection, designed for submission to IEEE Transactions on Affective Computing.
Published by
IEEE Open Journal of Vehicular Technology
Summary
Co-authored a publication on generating synthetic attack datasets for AI-based intrusion detection in industrial networks, contributing to enhanced security protocols.
Issued By
CompTIA
Issued By
Microsoft
Issued By
TryHackMe
Wireshark, Snort, Git, IDA Pro, Autopsy, Burp Suite, Binwalk, Nmap, Security Onion, ELK stack, Metasploit, Splunk, Ghidra.
Network Security, Cryptography, Application Security, Incident Response, Penetration Testing, Malware Analysis, Risk Mitigation, System Hardening, Vulnerability Assessment, Exploitation.
Python, Java, Bash, PowerShell, Linux, Windows, Kali Linux, NIST CSF, MITRE ATT&CK, ISO 27001, OWASP Top 10, CIA Triad, Cyber Kill Chain, Azure, Docker, VMware, VirtualBox, IBM Maximo.
PyTorch, Scikit-learn, XGBoost, CatBoost, BERT, LSTM, GRU, MLP, Transformers.
Classification, Anomaly Detection, Feature Engineering, Dimensionality Reduction, Model Tuning, Systematic Evaluation.
Pandas, NumPy, Data Preprocessing, Statistical Modeling, Model Evaluation, Data Exploration & Visualization, Jupyter Notebooks, SQL.
Java, Python, Jython, Bash, PowerShell, SQL.
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Summary
Developing a multimodal AI framework for depression and PTSD detection using audio, video, and text features. Conducting systematic feature extraction, feature selection, model tuning, and evaluation to study reliability and robustness in early-stage mental health assessment using PyTorch, XGBoost, CatBoost and Scikit-learn.
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Summary
Proposed and evaluated a synthetic attack dataset generation pipeline using the ID2T toolkit, validating dataset fidelity and effectiveness through an AI-powered intrusion detection pipeline on PCAP-derived features. Conducted feature engineering, anomaly detection, and performance evaluation using Scikit-learn classifiers to demonstrate applicability for IDS research.
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Summary
Developed an automated research pipeline using large language models and Lean 4 to generate formal specifications from unit tests, achieving 100% verification across 354 test cases through iterative refinement and correctness validation.
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Summary
Built a remote-controlled car using Raspberry Pi and implemented system and network hardening with real-time monitoring to study security controls in industrial control system environments.
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Summary
Performed binary analysis of IoT firmware; proposed encryption and security enhancements.
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Summary
Identified and exploited critical vulnerabilities (CVEs) in 10 web applications using Burp Suite, Nmap, and Metasploit, demonstrating Remote Code Execution, Command Injection, and Privilege Escalation.