anvay@portfolio:~/dev
~/work ~/stack ~/contact
[available]
$ whoami --full

ANVAY KHANDAGALE

> Full-stack engineer & cloud architect

Computer Science student with hands-on experience across full-stack development, cloud architecture, and AI/ML. My focus centers on the MERN stack, but I adapt quickly to new tech, taking concepts from raw ideas to live, production-ready cloud applications.

[x] Location: Pune, India
[x] Experience: 3+ Years Building
[x] Current CGPA: 9.01 (VIT-AP)
[x] Status: Available
$ ls ~/projects → ./contact --hire
$ neofetch
OS : Human v10.4 (engineer build)
Host : Vellore Institute of Technology (VIT-AP)
Role : B.Tech CSE Undergrad (2023 - 2027)
Uptime : 20 years (Born 2005)
Kernel : AWS Solutions Architect – Associate (SAA-C03)
Shell : zsh (MERN stack, Flask, Python)
Focus : Serverless Architecture • GenAI RAG Pipelines
Status : Active & available for winter internships / cloud work
$ ls -la ~/projects
kinetic_armor/ -rwxr-xr-x 2026

Copyright Infringement Detection Engine built for the Google Solution Challenge 2026. Real-time asset protection using Perceptual Hashing (pHash) to detect copyright violations across the web (identifying near-matches after resizing, compression, or color edits), combined with an AI evaluator that auto-generates DMCA notices.

[GCP Serverless] Flask Cloud Run Firestore pHash
→ Google Solution Challenge (GitHub)
superdesign/ -rwxr-xr-x 2025

Deterministic multi-stage AI App Compiler pipeline. Transforms natural language requirements into complete validated, execution-ready application blueprints (DB, API, UI, Auth schemas). Features a Targeted Repair Engine to isolate and fix validation errors without full regenerations.

[GenAI Pipeline] Pydantic Gemini 2.0 JSON Schema
→ 20-case Benchmarked (GitHub)
course_rec_bot/ -rwxr-xr-x 2025

RAG-based course recommender bot developed under the IBM Watsonx.ai program. Grounded recommendations using semantic queries against a real database to eliminate hallucinations, helping students discover academic pathways based on skill levels.

[IBM Watsonx] RAG Vector DB LLM Integration
→ IBM Watsonx groundings (Profile)
neural_compression/ -rw-r--r-- 2025

An exploration into deep neural network image compression algorithms. Achieved a compression ratio of 197.88:1, yielding significant reduction sizes compared to traditional JPEG compression standards while preserving structural features.

TensorFlow Keras Autoencoders Python
→ 197.88:1 Ratio (GitHub)
intelli_traffic/ -rwxr-xr-x 2024

Automated traffic violation detection system prototype. Spearheaded hardware engineering with an Arduino UNO microcontroller, MFRC522 RFID reader, and LEDs on breadboards. Programmed real-time violation triggers that log offender IDs and dispatch real-time warning alerts via Twilio REST APIs.

[IoT Hardware] Arduino UNO RFID (MFRC522) Twilio API C++ / Embedded
→ Breadboard Hardware & API dispatching (Profile)
$ cat stack.txt | sort -r

[ Languages & Core ]

Python ████████████░░░ 85%
JavaScript █████████████░░ 90%
SQL / DBMS ████████████░░░ 80%
HTML5 / CSS3 █████████████░░ 90%

[ Cloud, AI & Tools ]

AWS / S3 / EC2 ████████████░░░ 85%
GCP / Cloud Run ███████████░░░░ 75%
GenAI / RAG ████████████░░░ 80%
MERN / Flask █████████████░░ 90%

> Certifications & Training:

  • [x] AWS Certified Solutions Architect – Associate (SAA-C03, 03/2026)
  • [x] AWS Academy Graduate – Cloud Architecting & Cloud Foundations (10/2025)
  • [x] IBM Watsonx Gen AI Career Education Badge
  • [x] HackerRank Skill Badges: 3-Star Python & 3-Star SQL
  • [x] German Language Certifications (A1 & A2)

> Spoken Languages: English, Hindi, Marathi, German (A1 & A2)

$ ./contact --hire

INITIATE INCOMING CALL / TRANSMISSION

Let's discuss serverless architecture, full-stack React projects, or cloud migrations. Click below to copy my primary terminal address.

anvay@portfolio:~/dev$