class-weighting

Terminology extraction on ACTER using Transformer-based language models

A fraud detection classifier and investigation dashboard built on banking transaction data, combining SQL, Python, and interactive analytics to support faster fraud investigations and risk-based decisions.

A multi-dataset NLP and machine learning pipeline analyzing 2,833 Reddit posts from r/breakups and r/relationship_advice to uncover what drives community engagement. Confirms the Sentiment Paradox : emotional tone barely predicts virality; instead structure does.

Applies deep learning for time series classification using the LSST (Large Synoptic Survey Telescope) dataset.

This project implements a Darwin-Gödel Machine (DGM) self-improvement framework to optimize class weights for imbalanced bridge damage classification. The system uses LLM-based coding agents to iteratively propose weight configurations, evaluated through LoRA fine-tuning on a Japanese BERT-large model.