Ragul Seetharaman

Generative AI Research Engineer @ Cotiviti

About

Hi! I’m Ragul Seetharaman, an AI enthusiast captivated by the endless ways technology can make life better. My journey began in an "AI for Engineers" class at IIT Madras, where I realized that engineering is about more than building systems—it's about understanding human needs. This curiosity has fueled my path from social impact projects to hands-on AI development, and it’s led to some pretty cool milestones along the way. Currently pursuing my MS in Computer Engineering at Virginia Tech, I’ve had the privilege to contribute to impactful projects, from an FDA-approved model that enhanced heart arrhythmia detection accuracy to getting a patent granted for an AI-powered self-checkout system that rethinks the shopping experience. These experiences have allowed me to work with inspiring experts from Harvard and Mayo Clinic and have deepened my commitment to blending empathy with technology. Whether it’s building scalable ML pipelines, optimizing real-time data models, or finding creative solutions for healthcare and beyond, I’m constantly curious about what’s next. If your team values fresh perspectives and a collaborative spirit, let’s connect—I’m ready to explore, ask bold questions, and help turn ideas into impactful solutions.

Country

City

United States

Industry

Computer Software

Skill

Recurrent Neural Networks (RNN), Deep Neural Networks (DNN), Bioinformatics, Streamlit, Retrieval-Augmented Generation (RAG), Multi-agent Systems, Large Language Model Operations (LLMOps), Machine Vision, Recommender Systems, E-Commerce, Tableau, Deep Learning, Amazon Web Services (AWS), Medical Imaging, PostgreSQL, Database Management System (DBMS), Machine Learning Algorithms, Statistical Modeling, Statistical Data Analysis, Machine Learning

Experience

Generative AI Research Engineer

Cotiviti

2025-6 - Present · 1 yr 4 mos

Utah, United States

Entrepreneurial Lead

National Science Foundation (NSF)

2024-11 - 2024-12 · 2 mos

Connecticut, United States

Post Baccalaureate Fellow

Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI)

2022-11 - 2023-5 · 7 mos

Chennai, Tamil Nadu, India

• Implemented a deep learning model to predict plausible reactions from protein sequences, mapping them to EC numbers for amino acid sequences using 70k training data from the UniProt and Rhea databases. • Developed a user interactive system, locally integrating the ECPred models, to map proteins with sequences of amino acids.

Data Analyst

AmberTAG Analytics Pvt. Ltd.

2021-5 - 2022-11 · 1 yr 7 mos

Bengaluru, Karnataka, India

• Enhanced heart arrhythmia detection in ECG/EEG graphs through optimization of the 1DCNN and Xception models, leveraging signal processing techniques including FFT, derivatives, and EMD. • Managed pipeline code for 3D model extrapolation, data streaming via RabbitMQ, and visualization of results in a Qt application. • Conducted successful live procedures on 11 patients, leading to FDA approval and eventual company acquisition by nference

Programer Analyst

Cognizant

2020-9 - 2021-5 · 9 mos

Bengaluru, Karnataka, India

• Engineered an end-to-end model recommendation system for Shopify stores (Kamakhya, House of Blouse, Cotton World), enhancing product catalog relevance and boosting sales conversion rates for their winter & spring collection. • Automated bi-weekly sales report generation for over 6,000 products across Shopify stores, including top-performing collections, designs, and user engagement, leveraging AWS SageMaker and Tableau for visualization.

Data Research Analyst

Maruti Suzuki India Limited

2020-2 - 2020-7 · 6 mos

Bengaluru, Karnataka, India

•Conducted hypothesis testing and feature engineering utilizing ANOVA and PCA to identify 14 key parameters. •Employed machine learning techniques such as Kaplan Meier and XGBoost to predict the remaining lifespan of over 10,000 Ciaz & S-cross model car batteries, resulting in a highly accurate model.