I'm a B.Tech Computer Science & Engineering student (AI/ML specialization) at Lovely Professional University. I work across classical machine learning and applied AI: training and evaluating models on one side, building LLM-powered tools and automation on the other, and putting both behind reliable, asynchronous backends.
I'm looking for ML / AI internships where I can work on real experiments, learn from experienced engineers, and grow toward applied AI engineering.
- Education: B.Tech CSE (AI/ML specialization), Lovely Professional University, CGPA 8.90
- GATE 2026 (CS/IT): score 383, AIR 21,411, qualified in the first attempt
- Focus: machine learning (classification, scoring pipelines), applied AI (local LLMs, automation), and the backends that serve them
- Currently: strengthening ML fundamentals and moving into deep learning (PyTorch, Hugging Face)
|
ML-powered career guidance platform that predicts career paths and analyzes skill gaps.
|
Resume analysis and role-prediction platform that evaluates ATS compatibility.
|
Live demos run on free hosting, so the first visit may take a few seconds to wake up.
- AI Clipping Studio: a fully local, offline tool that turns long videos into short vertical clips. It transcribes with faster-whisper, picks the best moments with local LLMs through Ollama, and renders with FFmpeg. No cloud APIs.
- Lead-scoring automation: an n8n workflow that scores incoming contact-form leads as Hot, Warm or Cold and drafts a suggested reply, using a local Ollama model instead of a paid API.
- PDF Toolkit: a web app with around 13 PDF tools (compression, PDF to Word, PDF to image, image to PDF and more), deployed on Render with on-page SEO.
| Area | Tools & experience |
|---|---|
| Machine learning | Scikit-learn XGBoost Pandas NumPy spaCy NLTK Matplotlib Seaborn |
| ML workflow | Feature engineering (TF-IDF) · model benchmarking (Logistic Regression, Random Forest, SVM, XGBoost) · train/test evaluation (accuracy, F1-score) · model-serving optimization |
| Applied AI & LLMs | Ollama Qwen2.5 faster-whisper FFmpeg Prompt engineering |
| Automation | n8n Webhooks GitHub Actions |
| Languages | Python C JavaScript TypeScript |
| Backend & APIs | Django Django REST Framework FastAPI Celery JWT · REST API design · async task queues · caching · query optimization |
| Databases | PostgreSQL Redis |
| Frontend | React Vite HTML CSS MERN stack (training) |
| Tools & deployment | Git Docker Linux Jupyter / Google Colab Postman VS Code Vercel Render Railway |
| CS fundamentals | GATE 2026 (CS/IT) qualified: algorithms, databases, operating systems, computer networks |
| Currently learning | PyTorch Hugging Face Transformers · deep learning fundamentals |
Generated from my GitHub data by a scheduled GitHub Action and refreshed daily.
- GATE 2026 (CS/IT): AIR 21,411 (Feb 2026)
- MEDHA 2024 Hackathon: ranked 10th of 60 teams (Sep 2024)
- Training: FLAMES '25, MERN with Gen AI (W3grads), Jul 2025 · Youth Research Program, Resolute Lab, Mar 2025
- Certificates: Generative AI & Generative AI Tools · ChatGPT-4 Prompt Engineering: Generative AI & LLM (Infosys Springboard, Aug 2025)
The best way to reach me is by email or on LinkedIn. My portfolio has more about my work.