Projects
Selected systems and applied ML work
A mix of application engineering, model development, data analysis, MLOps, LLMOps, and computer vision projects.
QC-Leap
AI-Powered Manufacturing Quality Control System
Next.js, React, TypeScript, FastAPI, PostgreSQL, Redis, Celery, PyTorch, OpenCV, Docker
- Built a full-stack quality-control dashboard for defect detection model management, training, inference, and reporting.
- Implemented ML workflows with segmentation masks, Copy-Paste augmentation, class balancing, and MobileNetV3-Small classification.
- Developed FastAPI services with JWT auth, PostgreSQL models, Redis/Celery jobs, and real-time training progress updates.
SiteSage AI
Construction procurement intelligence copilot
Python, Streamlit, FAISS, SQLite, Scikit-learn, Plotly, Ollama (optional), Docker
- Built a multi-page procurement dashboard for document upload, cited AI question answering, delay prediction, vendor risk, and alerts.
- Implemented local RAG with document chunking, HashingVectorizer embeddings, FAISS retrieval, SQLite persistence, and grounded-answer fallbacks.
- Developed Random Forest delay-risk scoring, vendor reliability ranking, schedule-impact alerts, synthetic demo data, tests, and a reproducible Docker image.
Local Chapter Activity Dashboard
Synthetic-data LC activity and follow-up prototype
Python, Flask, SQLAlchemy, SQLite, Jinja, Bootstrap, Chart.js, Docker
- Built a standalone dashboard for latest-year LC activity, historical trends, and chapter-level timelines.
- Added validated CSV ingestion with upserts, JSON analytics endpoints, and inactive-chapter export.
- Published synthetic sample data and clearly separated this showcase from NPTEL's production Local Chapter systems.
Satellite Image Cloud Removal
Generative AI reconstruction for remote sensing imagery
Python, PyTorch, ResUNet, GAN, OpenCV, NumPy, Pandas, Matplotlib, Kaggle GPU
- Built a cloud-removal pipeline mapping cloudy optical imagery and masks to reconstructed cloud-free satellite outputs.
- Prepared RICE1/RICE2 manifests, trained a mask-guided ResUNet with cloud-aware L1 and SSIM loss, and exported visual predictions.
- Reached about 22.74 dB PSNR and 0.796 SSIM on RICE2 testing, then explored GAN refinement and Bhoonidhi LISS-IV data automation.
Multilingual Speech Recognition
Routed ASR pipeline under compute constraints
Python, PyTorch, Hugging Face, Whisper, Faster-Whisper, Indic Conformer, Librosa, Torchaudio, Kaggle
- Built an English, Hindi, and Tamil transcription pipeline for a Kaggle speech recognition challenge.
- Added language identification and dynamic model routing across Whisper large-v3-turbo and Indic Conformer models.
- Implemented transcript normalization, WER evaluation, beam-search inference, FP16 GPU execution, caching, and Kaggle submission generation.
Multilingual Sentiment Analysis
LLM fine-tuning for Indian-language sentiment classification
Python, Hugging Face Transformers, Gemma, LoRA, PEFT, bitsandbytes
- Fine-tuned google/gemma-3-1b-it with LoRA/PEFT for binary sentiment classification across 13 Indian languages.
- Built preprocessing, label encoding, tokenization, training, validation, diagnostics, and Kaggle submission workflows.
- Used memory-efficient training with bitsandbytes and Hugging Face Trainer, reaching 0.9778 local validation Macro F1.
Low-Light Image Restoration
Denoising, illumination correction, and 4x super-resolution
Python, PyTorch, NumPy, Pandas, PIL, Matplotlib, Seaborn, U-Net, PixelShuffle, CUDA
- Built a PyTorch restoration pipeline for the RELLISUR/Kaggle dataset with denoising, illumination correction, and 4x super-resolution.
- Designed a custom SR U-Net with encoder-decoder blocks, skip connections, PixelShuffle upscaling, and refinement layers.
- Reduced private RMSE from a 41.8 baseline to about 18.7 using EDA-driven modeling, loss tuning, mixed precision, TTA, and calibration.
End-to-End MLOps Pipeline
Cloud-native ML deployment and observability
Python, Scikit-learn, MLflow, DVC, GCS, Feast, BigQuery, FastAPI, Docker, GKE, OpenTelemetry
- Built an Iris classification pipeline with cloud artifact storage, data versioning, feature store setup, and experiment tracking.
- Automated CI/CD with GitHub Actions, pytest, CML reports, Dockerized FastAPI serving, Kubernetes deployment, HPA, and load testing.
- Added model explainability, fairness checks, drift monitoring, guardrails, and LLMOps/MLSecOps experiments.
RAG Document QnA
Local retrieval-augmented document assistant
Python, FAISS, Streamlit, Gemini, NLP chunking, semantic embeddings
- Built a local RAG system that synthesizes grounded answers from proprietary documents with refusal behavior for unsupported queries.
- Optimized CPU-bound vector similarity search with FAISS flat L2 indexing and overlapping text chunking.
- Created a Streamlit dashboard for PDF ingestion, session-state memory, constrained Gemini prompting, and citation-aware responses.
System Threat Forecaster
System vulnerability classification
Python, Scikit-learn, Pandas, Matplotlib
- Built a classification model to predict system vulnerabilities.
- Implemented preprocessing, evaluation, and model performance analysis.
Household Services Platform
Role-based services marketplace
Vue.js, JWT, Celery, Redis, Mailhog
- Built a full-stack application with admin, customer, and professional roles.
- Developed APIs, authentication, async task handling, and workflow automation.
Influencer Marketing App
Brand and influencer collaboration backend
Flask, SQLite, Python
- Designed database schema and REST APIs for campaign and user data handling.
- Built backend flows to connect brands with influencers.
Business Data Analysis
Local dairy shop sales analysis
Python, Pandas, Excel, Matplotlib, Seaborn, SQLite, Flask
- Analyzed sales and customer data to identify trends and improve inventory decisions.
- Created visualizations to communicate insights clearly.
