System Online

THE
AI ENGINEER

Aspiring AI Researcher & Software Engineer. Building robust machine intelligence and full-stack solutions, with a deep passion for Reinforcement Learning and Neural Architecture.

polyline
network_node

Neural Infrastructure

Specialized stacks engineered for high-performance agent training, web systems, and environment simulation.

code

Core Languages

Low-level performance handling with C/C++ alongside rapid iteration in Python & JS.

C / C++PythonJavaScript
webhook

Web Architecture

Building full-stack systems, dynamic dashboards, and bespoke interfaces.

React/Next.jsTailwind CSSNode.js / PHP
memory

Deep / Reinforcement Learning

Implementation and tuning of state-of-the-art AI algorithms. From Deep-Q networks in simulated environments to custom RAG ingestion pipelines and object detection architectures.

PyTorchLangChainDeep-Q LearningR-CNNLLMs / RAG

Applied Intelligence

Reinforcement LearningOpenAI Gym

RL Dangerous Dave

Created a Reinforcement Learning agent to play the classic platformer 'Dangerous Dave' by building a custom game environment. Optimized a DQN agent to achieve a 95% success rate in level completion within 500 training episodes through trial-and-error learning and effective reward structure design.

View Live Demo arrow_forward
search_insights

RAG System with LLMs

Developed a Retrieval-Augmented Generation (RAG) system to enhance language model responses via LangChain & Hugging Face. Implemented document processing workflows and integrated open-source models for contextual query inference.

Traffic System Optimization

Implemented an R-CNN model using PyTorch to detect vehicle density in real-time. Built a custom UI in Streamlit to observe traffic footage on which image detection and fuzzy logic are actively visualized.

PyTorchFuzzy Logic
Live Demo arrow_forward

Class Portal

Full-stack web app tailored for Administrators, Teachers, and Students using PHP and MySQL.

Maze-Runner

A 2D interactive maze game written in raw C, deploying collision logic and UI loops.

Full-StackSystems C
Solve Maze arrow_forward

Education & Experience

BE in Computer Engineering

Purbanchal University

Formal training in Data Structures & Algorithms, Computational Theory, Artificial Intelligence, Computer Networks, and DBMS.

Real World Availability

Actively Seeking Opportunities

Ready to deploy skills into an internship or entry-level software/AI engineering role. Looking forward to tackling practical challenges.