AIML undergraduate with strong foundations in Python, full-stack development, machine learning, and statistical modeling. Experienced in building React/Node.js applications and data-driven projects involving finance, cybersecurity, and predictive analytics.

currently focused on:

• Data structure and Algorithms
• AI / Machine Learning
• Full Stack Web Dev
• Linux & System programming
• Exploring Open Source contributions

• Developed a machine learning model to predict residential building heating and cooling energy loads.
• Implemented Bayesian Optimization (TPE/Hyperopt) to automatically tune XGBoost hyperparameters, improving model performance over manual tuning

• Modeled stock return distributions using Student's t-distribution to capture heavy-tail behavior ignored by normal distribution assumptions.
• Analyzed historical market data using Python, NumPy, SciPy, and Matplotlib.

• Engineered an API-integrated malware detection system that processes file inputs, communicates with a remote threat intelligence service, and displays descriptive analytical reports.

Learning → Building → Contributing → Improving 🚀