Rajat Rayaraddi.

Rajat Rayaraddi.

M.S. in Computer Science at The George Washington University.

Education

The George Washington University

Master of Science in Computer Science

August 2024 - May 2026
Washington, D.C.

PES University

Bachelor of Technology in Computer Science and Engineering

December 2020 - May 2024
Banglore, India

Experience

Research Assistant

PES University

Trained and developed a Vision-Language Model to generate metaphorical interpretations from images, combining CNNs for image feature extraction and Transformer-based NLP models, integrating both visual and textual feature representations to analyze visual metaphors for multimodal metaphor detection.

June 2023 - August 2023
Banglore, India

Skills

Projects

BiLSTM-CNN With Attention For Remaining Useful Life Prediction In Turbofan Engines

Created a hybrid deep learning model combining BiLSTM, Transformer, and CNN architectures to estimate Remaining Useful Life (RUL) of aircraft engines using NASA C-MAPSS dataset. Incorporated CBAM attention to enhance focus on key sensor features, positional encoding to preserve temporal structure of sensor sequences, residual dilated convolutions to capture long-range dependencies, and transformer blocks for contextual sequence modeling.

  • TensorFlow
  • scikit-learn

Anomaly Detection in Surveillance Videos

A novel Multiple Instance Learning (MIL) based model architecture to classify surveillance video segments as anomalous or normal. Utilized the I3D feature extraction model to extract RGB and motion flow features. Achieved an Area Under the Curve (AUC) of 0.9022, demonstrating high recall and precision, outperforming current state-of-the-art models on a subset of the UCF-Crime dataset by 2%.

  • PyTorch

AI-Powered Diagnostic Support Tool

Retrieval-Augmented Generation (RAG) based diagnostic support tool using PubMed data and OpenAI API to suggest possible diseases based on patient symptoms, demographics, and medical history. Integrated Agentic AI to provide context-specific responses.

  • Node.js
  • React

Vehicle Detection and Classification

SSD-Mobilenet V1-based traffic monitoring system to detect, count, and classify vehicles in real-time, addressing need for efficient traffic control. Implemented vehicle color and speed prediction, storing images of detected vehicles, and logging detection data to a CSV file for analysis.

  • TensorFlow
  • OpenCV

Evaluating Traditional and Ensemble Learning Techniques for Churn Prediction

Built and evaluated multiple machine learning models to predict customer churn using a telecom dataset. Applied feature engineering and preprocessing, and benchmarked classifiers including Logistic Regression, SVM, Decision Trees, Random Forest, Gradient Boosting, and ensemble methods.

  • pandas
  • NumPy
  • scikit-learn

Certifications

AWS Certified AI Practitioner

AWS Certified AI Practitioner

Issued: September 2025 | Expires: September 2028

AWS Certified Cloud Practitioner

AWS Certified Cloud Practitioner

Issued: September 2025 | Expires: September 2028

Contact

rajat.rayaraddi@gmail.com