---
title: "Roohan Poppoppu - Generative AI Intern in India | Tal"
description: "Meet Roohan Poppoppu, AI/ML Student | Generative AI | MachineLearning. based in India."
image: "https://tal.club/meet/roohan/share-image"
---

# Roohan Poppoppu on Tal

## Headline

AI/ML Student \| Generative AI \| MachineLearning\.

## About

Computer Science graduate specializing in Artificial Intelligence and Machine Learning, with a passion for building intelligent systems that solve real\-world problems\. I have hands\-on experience developing and deploying machine learning solutions using Python, PyTorch, and modern AI frameworks\. My key projects include a Retinal OCT Analyzer that achieved 94% accuracy on a dataset of 84,000\+ medical images and a Heart Disease Prediction System built using end\-to\-end machine learning pipelines\. My technical expertise includes Machine Learning, Deep Learning, Python, Java, SQL, Data Structures & Algorithms, PyTorch, and AWS Cloud technologies\. I enjoy tackling complex challenges, optimizing model performance, and developing scalable, data\-driven applications\. I hold the Oracle Generative AI Professional certification and the Amazon Web Services Cloud Practitioner certification\. Additionally, I have solved 100\+ coding problems on LeetCode to strengthen my problem\-solving and software engineering skills\. Currently seeking opportunities in AI/ML Engineering, Software Engineering, and Data Science, where I can contribute to impactful projects, continue learning, and grow as a technology professional\.

## Location

India

## Work experience

Generative AI Intern at Prodigy InfoTech, Jun 2026 \- Jul 2026 · 2 mos, Hyderabad, Telangana, India, • Currently serving as a Generative AI Intern at Prodigy InfoTech\. • Gaining hands\-on experience in Generative AI, Large Language Models \(LLMs\), and AI application development\. • Learning and applying prompt engineering techniques to build AI\-powered solutions\. • Working with Python and modern AI tools/frameworks to develop practical projects\. • Exploring real\-world applications of Machine Learning and Natural Language Processing \(NLP\)\. • Enhancing problem\-solving, research, and technical development skills through industry\-oriented tasks\.

Deep Learning Engineer at Vellore Institute of Technology, Jan 2026 \- Apr 2026 · 4 mos, Developed a hybrid ensemble–deep learning framework for credit card fraud detection on highly imbalanced transaction data\. Built and evaluated multiple machine learning models including Logistic Regression, Random Forest, SVM, XGBoost, and a custom Deep Neural Network architecture\. Applied SMOTE\-based oversampling, feature preprocessing, hyperparameter tuning, and model optimization to improve fraud detection performance\. Designed a Deep Learning \+ XGBoost hybrid model achieving 0\.77 F1\-score, 0\.79 PR\-AUC, and real\-time inference latency suitable for production environments\. Implemented the solution using Python, PyTorch, Scikit\-learn, XGBoost, Pandas, NumPy, and Machine Learning pipelines\. Collaborated with a team member to conduct experimentation, performance analysis, and comparative evaluation on the Kaggle Credit Card Fraud Detection dataset\.

## Education

Bachelor of Technology, Computer Engineering, Vellore Institute of Technology

INTERMEDIATE, MPC, sasi junior college

[View the original profile](https://tal.club/meet/roohan)

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