I build Python-first AI systems, computer vision tools, cyber-physical experiments, and full-stack applications that turn machine learning ideas into usable software.
| Signal | Evidence |
|---|---|
| Primary fit | AI/ML engineering, Python development, applied ML systems |
| Strongest proof | E-challan fraud detection, SCADA anomaly detection, GestureX computer vision |
| Backend / app delivery | FastAPI, React, Next.js, Firebase, Docker-backed project work |
| Research direction | Cyber-physical systems, explainable fraud detection, AI + IoT experiments |
| Interview prep | Python DSA repository covering core data structures and algorithms |
I am an M.Tech Artificial Intelligence and Machine Learning student focused on applied AI engineering, Python development, and research-driven project building. My work spans fraud detection, cyber-physical anomaly detection, computer vision interaction systems, academic workflow platforms, and AI-powered web applications.
I care about building systems that are explainable, useful, and organized enough for another engineer to understand, run, and extend.
Languages
AI / Machine Learning
Frameworks / App Development
Databases / Platforms / Tools
- Advanced Python and data structures for stronger problem solving.
- Machine learning and deep learning systems with explainable evaluation.
- Generative AI, AI agents, NLP, and computer vision workflows.
- Production-ready AI applications with FastAPI, React, Next.js, Docker, and Firebase.
- AI + IoT and cyber-physical system experiments.
- Applied ML / security: E-Challan Fraud Detection.
- Research + ML systems: Physics-Aware SCADA Digital Twin.
- Computer vision: GestureX / Computer Vision Project.
- Full-stack engineering: Research Paper Management Platform and Portfolio.
- Python fundamentals: DSA by Python.
Multimodal fraud detection system for suspicious traffic challan messages, URLs, PDFs, APKs, and QR codes.
- Problem: Helps identify phishing-style e-challan scams and suspicious payment flows.
- Tech: Python, FastAPI, scikit-learn, XGBoost, SHAP, PDF parsing, OCR/QR tooling, React, Tailwind CSS.
- Highlights: Text, URL, PDF, APK, and QR analysis; explainable risk scoring; admin/reporting workflows; checked-in fused model metrics report F1 0.907 and ROC AUC 0.963.
Cyber-physical anomaly detection framework combining process constraints with ML models for SCADA telemetry.
- Problem: Detects anomalies and cyber-physical attack patterns in industrial telemetry.
- Tech: Python, PyTorch, scikit-learn, FastAPI, Docker, Matplotlib, Seaborn.
- Highlights: Physics twin rules, ML scoring, REST API, dashboard, benchmark scripts, and research paper assets; checked-in hybrid benchmark summary reports 92.88% F1 on
paper/metrics_summary.json.
Personal portfolio web app for project showcases, certificates, resume, contact, and live demo pages.
- Problem: Centralizes professional proof-of-work and project discovery.
- Tech: React, TypeScript, Vite, Tailwind CSS, Firebase, Framer Motion, Vercel.
- Highlights: Project catalog, certification gallery, resume page, GitHub project data, and static demos.
Computer vision interaction suite for hand gesture control, image editing, lighting controls, and SAM-assisted segmentation.
- Problem: Explores touchless human-computer interaction and gesture-based visual editing.
- Tech: Python, OpenCV, MediaPipe, Segment Anything Model, Streamlit, NumPy.
- Highlights: Gesture cursor control, pinch selection, object segmentation, inpainting, room presets, and keyboard controls.
Full-stack academic repository and workflow platform for student research submissions.
- Problem: Organizes research metadata, review stages, plagiarism records, and department-level analytics.
- Tech: Next.js, NestJS, TypeScript, Prisma, SQLite, Tailwind CSS.
- Highlights: Submission flow, workflow history, tag model, dashboard APIs, and academic project report.
Python learning repository for core data structures, algorithms, and complexity analysis.
- Problem: Builds a stronger foundation for technical interviews and software engineering fundamentals.
- Tech: Python.
- Highlights: Arrays, linked lists, stacks, queues, trees, graphs, traversal, sorting, and searching modules.
- GitHub: github.com/aaryaninvincible
- LinkedIn: linkedin.com/in/aryanraikwar
- Portfolio: aaryaninvincible-portfolio.vercel.app
Focused on AI/ML engineering, Python systems, and practical intelligent applications.