Research Student
- Developed an anomaly detection model using GANs and WGANs for 3D reconstruction tasks, achieving a high Area Under the Curve (AUC) score of 87%.- Leveraged advanced machine learning techniques to classify and detect anomalies in 3D models, optimizing model accuracy and performance through iterative loss minimization and latent space exploration.- Research presented at the Ugrd Eng Conference at the University of Toronto.