Python Developer | AI/ML Developer | Full Stack Developer | MERN Stack | Next.js
Hi, I'm Ashwin Chauhan, a Computer Science Engineering student focused on full-stack development, artificial intelligence & machine learning, and MERN stack development.
- B.Tech Computer Science Student (8.1 CGPA)
- Developed SkillSync AI - AI Career Guidance Platform
- Developed Credential Stuffing Attack Detection System using Machine Learning
- Building AI-powered platforms and data-driven applications to solve the real-world problems
- Exploring Data Science, Visualization, and AIML
- Always learning and improving my software engineering skills
AI-Based Marine Heatwave Detection and Forecasting System
Status: In Development
An AI-driven marine intelligence system designed to detect, analyze, and forecast Marine Heatwaves (MHWs) using oceanographic and climate datasets. The project aims to support marine climate research through data-driven analysis and predictive modeling.
Key Contributions & Features
- Marine heatwave detection and forecasting using historical oceanographic datasets.
- Integration of NOAA and Copernicus marine data sources.
- Climate data preprocessing, exploratory analysis, and visualization.
- Temporal trend analysis and marine climate monitoring.
- Interactive dashboard for climate intelligence and analytical insights.
Technology Stack: Python, Machine Learning, FastAPI, Next.js, React.js, PostgreSQL, NOAA Data, Copernicus Data.
Wildlife Population Intelligence System
An AI-powered wildlife monitoring platform leveraging computer vision to automate species detection, support population estimation, and provide analytical insights for biodiversity monitoring and conservation.
Key Contributions & Features
- Automated wildlife detection and species identification using YOLO.
- Computer vision-based wildlife population monitoring.
- Analytical dashboards for detection statistics and population insights.
- Geospatial visualization and wildlife monitoring.
- RESTful APIs for detection, reporting, and population analytics.
Technology Stack: Python, YOLO, OpenCV, FastAPI, Next.js, React.js, Tailwind CSS, SQLite, Docker.
Future of Digital Banking Security
An advanced digital banking security initiative focused on exploring AI-powered, privacy-preserving, and quantum-resilient approaches to strengthening next-generation financial infrastructure.
Key Contributions & Focus Areas
- AI-driven digital banking security architecture.
- Privacy-preserving financial data protection.
- Exploration of quantum-resilient security mechanisms.
- Secure digital transaction infrastructure.
- Research into emerging cybersecurity challenges in financial systems.
Technology Focus: Artificial Intelligence, Cybersecurity, Privacy-Preserving Computing, Quantum-Resistant Cryptography, Digital Banking Security.
Machine Learning-Based Authentication Anomaly Detection
A machine learning-based cybersecurity solution designed to identify suspicious authentication patterns and detect potential credential stuffing attacks through anomaly detection techniques.
Key Contributions & Features
- Developed an anomaly detection system using Isolation Forest.
- Implemented login activity monitoring and suspicious behavior identification.
- Analyzed authentication patterns to identify potentially malicious activities.
- Developed an interactive security dashboard for attack visualization and analytical insights.
- Integrated a FastAPI backend with a Streamlit-based monitoring interface.
Technology Stack: Python, Scikit-learn, Isolation Forest, FastAPI, Streamlit.
AI-Powered Career Guidance and Skill Development Platform
A full-stack AI-powered career development platform designed to help individuals assess their professional skills, identify skill gaps, explore industry trends, and build personalized career development roadmaps.
Key Contributions & Features
- Developed an AI-powered career guidance and skill development platform.
- Implemented intelligent skill-gap analysis and personalized learning recommendations.
- Built an ATS-friendly resume builder with AI-assisted content generation.
- Integrated AI-powered cover letter generation.
- Developed automated industry insights covering salary trends, market demand, and relevant skills.
- Implemented scheduled background processing for industry insights.
Technology Stack: Next.js, Prisma ORM, Clerk, PostgreSQL, Google Gemini API, Inngest, Tailwind CSS.
Full-Stack Movie Discovery and Ticket Booking Platform
A full-stack web application designed to provide an interactive movie discovery experience with integrated movie information, user authentication, and ticket booking workflows.
Key Contributions & Features
- Developed a full-stack movie discovery and ticket booking application.
- Implemented user authentication and booking workflows.
- Integrated TMDB API for dynamic movie information and metadata.
- Developed movie browsing, search, and discovery functionality.
- Designed responsive user interfaces for an enhanced browsing experience.
Technology Stack: MongoDB, Express.js, React.js, Node.js, TMDB API.
I actively work on open-source initiatives focused on machine learning infrastructure, artificial intelligence, financial technology, and scalable software engineering. These projects aim to explore emerging technologies and develop practical, extensible solutions.
A Research-Oriented Hybrid Python/C++ Machine Learning Framework
An independent machine learning framework designed around a native C++ computational core and an accessible Python API, with an emphasis on mathematical foundations, numerical correctness, and reproducible experimentation.
Key Highlights
- Developing a native C++ computational engine for matrix operations and numerical computing.
- Integrating Python and C++ through Pybind11.
- Designing modular machine learning algorithms and mathematical components.
- Researching automated data leakage detection and prevention in ML pipelines.
- Exploring reproducible experimentation, numerical validation, and performance benchmarking.
Technology Stack: C++20, Python 3.11+, Pybind11, CMake, Scikit-learn, Pytest, GitHub Actions.
Development Status: Early Development (Phase 1).
Repository: EliteML
AI-Powered Personal Finance Management Platform
An intelligent personal finance management platform designed to transform financial data into actionable insights through AI-assisted analysis, financial analytics, and predictive intelligence.
Key Highlights
- Personal finance management, including income, expense, and budget tracking using reinforcement learning.
- AI-powered financial assistance and personalized recommendations using Google Gemini.
- Financial analytics, spending trends, and cash flow analysis.
- Researching machine learning capabilities for expense classification, spending forecasting, and anomaly detection.
- Secure application architecture with authentication, database management, and cloud deployment.
- Open-source collaboration opportunities across frontend, backend, AI/ML, and DevOps.
Technology Stack: Next.js, React.js, Tailwind CSS, Prisma ORM, PostgreSQL, Google Gemini API, Clerk, Inngest, Arcjet, Resend, Vercel.
Development Status: Active Development.
Repository: Fintra-AI
- Best Academic Performance Award (2024–2025)
- Inter-College Volleyball Medalist
- Event Anchor & Volunteer
- Class Representative