Projects
Full-Stack ML App
Recall — Socratic AI Learning Tutor
A mobile learning application that uses an LLM to guide users through book comprehension using the Socratic method — asking questions rather than giving answers.
- Socratic prompting system for coherent multi-turn teaching conversations
- Book-specific grounding to prevent hallucination and keep responses contextual
- Kotlin Spring Boot REST API backend deployed to GCP Cloud Run
- Supabase (PostgreSQL + Auth) + Groq API for fast inference
- Compose Multiplatform client (Android + iOS)
- Chrome extension for book content extraction
Kotlin Spring Boot Jetpack Compose Compose Multiplatform GCP Cloud Run Supabase PostgreSQL Groq API LLM
In progress — targeting release as a fully end-to-end shipped product
ML Projects
Bean Disease Classification (Computer Vision)
Full end-to-end pipeline from training to mobile deployment.
- Deep CNN with transfer learning, 98% test accuracy on ~1k samples
- Data augmentation to compensate for small dataset
- MLflow experiment tracking + Apache Airflow workflow orchestration
- TFLite deployment to Android for real-time offline inference
- Dockerized Modal cloud GPU training for scalable experimentation
- Flask REST API for configurable model training and hyperparameter control
Keras TensorFlow TFDS TFLite MLflow Airflow Docker Flask HuggingFace Android
Air Quality Prediction — Time-Series Forecasting
Comparative forecasting study with a full MLOps setup.
- Compared ARIMA, Prophet, XGBoost, and LSTM models (best Willmott Index: 0.84)
- Recursive multi-step forecasting with rolling-window cross-validation
- CI/CD pipeline with GitHub Actions and Docker
Python Scikit-Learn XGBoost TensorFlow/LSTM Prophet statsmodels Docker GitHub Actions
Sudoku Solver with Deep CNNs
- TFRecords for efficient large-dataset loading and preprocessing
- Curriculum (progressive) learning — trained on easier puzzles first, gradually increasing difficulty
- Custom loss function and adapted architecture to enforce Sudoku rules
Keras TensorFlow TFRecords Deep CNNs