Software Developer | AI/ML Undergraduate | Hyderabad, India

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• Practicing Data Structures & Algorithms daily in Python, currently at 76+ problems solved across LeetCode and CodeChef
• Building end-to-end machine learning systems — from data cleaning through model evaluation and deployment
• 3rd-year B.Tech Computer Science (AI & ML) student at Sreenidhi Institute of Science and Technology, Hyderabad, graduating in 2028
• Working toward a Summer 2027 Software Engineering / Applied Science internship, targeting Google, Microsoft, Wells Fargo, Amazon, Goldman Sachs, Atlassian, NVIDIA, and Adobe

Concurrent Weather Performance Analyzer — deployed on Streamlit Replaced sequential weather-API calls with concurrent execution using Python's ThreadPoolExecutor, cutting benchmark runtime by 81% (5.30x speedup). Built an interactive dashboard comparing sequential vs. concurrent performance. Stack: Python, Streamlit, Plotly · Live App

Medical Insurance Cost Prediction Trained and benchmarked 5 regression models, improving R² from 0.784 to 0.862. Identified smoking status and BMI as the strongest cost drivers. Stack: scikit-learn, XGBoost, Pandas

Customer Churn Feature Engineering Pipeline Built an ML-ready data pipeline for a ~440,000-row Kaggle churn dataset, engineering 3 derived features with outlier removal via the IQR method. Stack: Pandas, NumPy

EATIS — Event Traffic Intelligence System — hackathon, team project Built the React frontend for an AI traffic-prediction platform displaying congestion forecasts and risk scores from a FastAPI backend. Stack: React, FastAPI, Vercel

TransitOps — hackathon, team project Odoo-based transit operations management system. Owned the core backend and trip-rules engine — vehicle, driver, and trip lifecycle models. Stack: Odoo, PostgreSQL, Python

AI/ML Virtual Internship — AICTE EduSkills, supported by Google for Developers · Oct–Dec 2025 Earned the highest grade tier ("Outstanding") in a 10-week applied AI/ML program covering supervised and unsupervised learning, NLP, model deployment with Flask, and MLOps fundamentals.

Machine Learning & Data Science Internship — EduSkills Academy · 2025–2026 Completed a capstone customer-sentiment-analysis project applying ensemble methods, hyperparameter tuning, SQL integration, and Power BI dashboards.

Languages: Python, Java, C, R Machine Learning / Data Science: scikit-learn, XGBoost, Pandas, NumPy, Matplotlib, Seaborn Data & Databases: MySQL, Oracle SQL, MongoDB Backend & Deployment: Flask, FastAPI, Odoo, Streamlit, React Tools & Platforms: Git, GitHub, Jupyter Notebook, Power BI, Vercel

B.Tech, Computer Science (AI & ML) — Sreenidhi Institute of Science and Technology, Hyderabad 2024–2028 · GPA: 9.56/10.0

12th Grade (CBSE) — D.A.V. Public School, Hyderabad 2022–2024 · GPA: 10.0/10.0

• Intro to Machine Learning — Kaggle
• Pandas — Kaggle
• Learning MongoDB — Infosys Springboard
• AI-Powered Chatbots — IBM SkillsBuild
• How OTT Platforms Handle Millions of Concurrent Viewers Using HLD — Scaler Masterclass

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