I am an AI Security Researcher focused on building intelligent, data-driven systems using machine learning and large language models (LLMs). My work combines data analysis, network programmability, and AI-driven architectures to address real-world challenges in cybersecurity and intelligent systems. I have worked on projects involving malicious link detection, predictive modeling, and behavioral analysis, along with research on LLM integration in programmable future networks. I use tools such as Python, SQL, PyTorch, and TensorFlow to transform complex data into meaningful insights and scalable solutions. Alongside my research, I enjoy exploring emerging technologies and sharing knowledge through my platform rinote.co, reflecting my commitment to continuous learning and impactful innovation.
Analyzed Amazon reviews using Python & SQL for sentiment classification. Visualized insights with Power BI & Tableau, pie charts for sentiment, word clouds, rating correlation, and category-wise trends. NLP preprocessing used to extract key themes.
View on GitHub View on GitHubAnalyzed real-time stock data for multiple companies using Python and yfinance. Visualized daily closing prices, moving averages, Bollinger Bands, and volume-price trends. Includes sector-wise comparison to uncover investment patterns. Tools: Python, SQL, Power BI, Tableau.
View on GitHub View on GitHubSegmented customers using RFM (Recency, Frequency, Monetary) analysis to identify loyal, at-risk, and churned users. Used Python for scoring and clustering, and visualized insights in Power BI/Tableau to support targeted marketing and retention strategies through interactive dashboards.
View on GitHub View on GitHubExplored IBM HR data to identify factors influencing employee attrition using Python, SQL, and Power BI/Tableau. Analyzed trends by department, job role, salary, and work-life balance. Built a binary classification model for attrition prediction using integrated visuals in BI tools.
View on GitHub View on GitHubDeveloped a sales dashboard using Python, SQL, Power BI, and Tableau to analyze retail data. Tracked revenue, profit, and quantity sold across regions and categories. Included time-series trends, region-wise breakdowns, and profit heatmaps for actionable business insights.
View on GitHub View on GitHubDesigning multi-layered security architectures for data centers and distributed systems.
Leveraging machine learning and deep learning models to detect and mitigate cyber threats.
Exploring SDN and large language model integration for network automation.
Designing secure, autonomous AI agents with controlled decision-making and tool integration.
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