Aspiring backend engineer, machine learning practitioner, and Android application security researcher with hands-on experience in Python development, mobile pentesting, backend systems, and applied AI workflows. Skilled in FastAPI, Pandas, NumPy, scikit-learn, Power BI, and data visualization, with experience building machine learning pipelines, REST APIs, analytics tooling, and automated processing systems. Experienced in Android reverse engineering and runtime instrumentation using Frida, Objection, Burp Suite, and JADX, focusing on vulnerable app exploitation, native library analysis, debugging workflows, and practical AppSec research. Built projects involving Logistic Regression, Decision Trees, Random Forests, cross-validation, and hyperparameter tuning while strengthening expertise in scalable backend architecture, deployment workflows, and intelligent automation systems. Interested in backend engineering, AI-powered applications, mobile security research, developer infrastructure, and production-oriented system design, with a strong focus on hands-on learning, technical experimentation, and building practical software solutions.