Graduate student

EDUCATION

BADRINATH

*******************@*****.*** +1-571-***-**** GitHub LinkedIn Portfolio Eastern Illinois University Jan. 2024 – Dec 2025

Masters in Computer Engineering (Machine Learning, Database Management, Data Science) Charleston, IL TECHNICAL SKILLS

Languages: Python (Object-Oriented Programming), SQL Machine Learning & Data Science: Scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, Pandas, NumPy Data Visualization: Matplotlib, Seaborn, Plotly, Power BI, Tableau Tools & IDEs: Jupyter Notebook, VS Code, PyCharm, Eclipse, Git, GitHub WORK EXPERIENCE

Data Science MedTech Hyderabad, India Aug 2022 – Dec 2023

Collaborated on a healthcare analytics initiative to predict patient readmission risk using logistic regression on 5K+ hospital records.

Cleaned and transformed patient records using Pandas and performed EDA to uncover key indicators like age, comorbidity, and length of stay.

Built and evaluated classification models (Logistic Regression, Random Forest), achieving 80% AUC score in forecasting readmission likelihood.

Created interactive Power BI dashboards visualizing patient risk levels, enhancing clinical decision-making and reducing review time by 30%

Data Science Intern Triad Software Hyderabad, India Sep 2022 – Dec 2022

Developed and deployed machine learning–based anomaly detection models using TensorFlow, SVM, and SOM, achieving 95% accuracy and reducing false positives by 22%.

Conducted exploratory data analysis (EDA) on large-scale cybersecurity logs to uncover trends, feature correlations, and outliers critical for robust model performance.

Automated ingestion and preprocessing of 100K+ records using advanced SQL, cutting data pipeline latency by 25% and enabling near real-time detection.

Designed interactive Power BI dashboards to visualize anomaly trends and incident heatmaps, improving stakeholder visibility and reducing report turnaround by 30%.

Partnered with analysts and engineers to define KPIs and gather dashboard requirements, ensuring alignment with operational and security goals

ACADEMIC PROJECTS

Fake Shield: Image,Video Deepfake Detector Python, ML,DL January 2025

Built a deep learning system to detect manipulated images and videos, leveraging CNNs for spatial features and RNNs for temporal sequence analysis.

Preprocessed and augmented 16K+ samples from the Deepfake Detection Challenge dataset to address class imbalance and improve generalization.

Analyzed dataset patterns and training performance with Matplotlib and Plotly, enabling deeper insights into model behavior.

Boosted detection accuracy to 90% using transfer learning (Xception), regularization, and optimized training strategies

Designed to support misinformation detection by identifying manipulated media content. Edu Bot: AI-Powered Learning Assistant Python, TensorFlow, Scikit-learn, SQL, Pandas, NumPy April 2025

Developed an AI chatbot leveraging GPT and ML models to assist students with Data Science and Machine Learning concepts.

Integrated SQL database to manage FAQs, track user progress, and store interaction history.

Implemented intent classification using Scikit-learn and fallback models with TensorFlow/PyTorch.

Designed interactive data visualizations (Matplotlib, Seaborn, Plotly) to analyze usage patterns and optimize chatbot responses.

Deployed the chatbot as a Streamlit web application, enhancing accessibility and usability.

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