Machine Learning • Deep Learning • GenAI • LLMs • RAG • AI Agents • MLOps • Cloud Computing
Driven by curiosity, consistency, and code—building intelligent systems with Machine Learning, Generative AI, and real-world impact.
I am passionate about leveraging Artificial Intelligence to solve real-world problems and build intelligent systems that create meaningful impact. My journey in technology is driven by curiosity, continuous learning, and a desire to understand how intelligent systems can transform the way we live, work, and interact with technology.
I am particularly interested in Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and the broader field of Applied AI. What excites me most is the opportunity to bridge the gap between cutting-edge AI research and practical applications that deliver real value to people and organizations. I believe that building impactful AI solutions requires more than training models. It involves understanding problems deeply, designing scalable systems, working with data effectively, and creating solutions that are reliable, efficient, and user-focused.
This perspective motivates me to continuously explore new technologies, build projects, and strengthen my understanding of the rapidly evolving AI landscape. My goal is to contribute to the development of intelligent products that enhance productivity, improve decision-making, and solve meaningful challenges. I am especially fascinated by the future of AI-powered applications, autonomous agents, and generative AI systems that reshape industries and everyday experiences. Beyond technology, I value curiosity, consistency, and lifelong learning. I enjoy tackling complex problems, learning from challenges, and collaborating with others who share a passion for innovation and growth. I am always eager to connect with students, developers, researchers, and professionals in Artificial Intelligence and emerging technologies.
Python, JavaScript
Git/GitHub, CI/CD, Docker
MySQL, PostgreSQL, MongoDB
TensorFlow, PyTorch
Pandas, NumPy, SciPy, Scikit-learn
HTML, CSS, React.js, Flask
GPT, Claude, Copilot, Hugging Face
AWS, Azure
Matplotlib, Seaborn, Tableau, Excel
MLflow, Kubeflow, FastAPI, Kubernetes
LangChain, LlamaIndex, RAG, Prompt Engineering
Linear Algebra, Calculus, Probability, Statistics, Optimization
Present
AI-powered research assistant that answers questions from uploaded PDFs and documents using Retrieval-Augmented Generation (RAG), semantic search, and vector embeddings.
Jan 2026 – Mar 2026
Autonomous AI agent system that plans tasks, delegates subtasks between specialized agents, and generates actionable outputs for complex user requests.
Aug 2025 – Oct 2025
LLM-powered application that analyzes resumes, extracts skills, identifies gaps, and matches candidates with relevant job descriptions using semantic similarity.
Jul 2025 – Aug 2025
Production-ready customer support assistant using custom knowledge bases, conversation memory, and RAG architecture for intelligent responses.
Mar 2025 – Jun 2025
Computer vision system that detects and tracks objects in real-time video streams using deep learning models and live inference pipelines.
Nov 2024 - Jan 2025
Full machine learning platform for training, experiment tracking, deployment, monitoring, and automated retraining workflows.
Wright State University
Jan 2025 – Dec 2026 | GPA: 3.5
Jan 2021 – Aug 2024
Email: meenagurrram25@gmail.com
LinkedIn: Meena Gurram
GitHub: meenagurram02