Panav Jain

About

Second-year Computer Science undergraduate with a strong foundation in deep learning, uncertainty quantification, and high-performance computing. Adept at optimizing model inference, managing CUDA environments, and building robust data pipelines. Pursuing hands-on experience with MLOps practices to build scalable, hardware-accelerated AI solutions, with internship experience spanning YOLO-based computer vision, RAG systems, GNN modeling, and data analytics.

Experience

• Machine Learning Intern – Innovative Application Consultant · Innovative Application Consultant06-01-2026

  • Building YOLO-based computer vision pipelines for custom object detection, handling dataset curation, augmentation pipelines, and anchor-box optimization. • Architecting RAG systems that integrate vector databases with LLMs via 3rd-party APIs, designing retrieval and context-injection flows for real-time generation tasks. • Developing Graph Neural Network (GNN) models for structured data and relationship modeling, experimenting with message-passing architectures for node-level predictions. • Integrating webhook-driven automation to orchestrate model inference and data synchronization across distributed client services.

• Data Analyst Intern · GlobalShala06-01-2025 – 08-31-2025

  • Analyzed marketing campaign performance across cohorts using Python and Pandas; identified the lowest-ROI initiative and recommended termination to reduce resource drain. • Delivered data-driven insights to stakeholders via technical reports, quantifying engagement and conversion rates.

Education

• Bennett UniversityB.Tech, Computer Science
• Lancers’ ConventGrade 12

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