Deep Learning Engineer focused on Computer Vision. Experienced in generation and evaluation of artificial data for data augmentation and improved Deep Learning methods. Expert in network design and training

Skills

• Python
• C/C++
• MATLAB
• PyTorch
• TensoFlow
• Keras

Projects

• Iris Segmentation for AR/VR cases using Deep Neural Networks
• Training Framework for Conditional Generative Adversarial Networks
• Evaluation Methodology for GAN generated facial images used for Synthetic Identiti
• Towards Fully Neural Face Authentication – Quantifying and Retraining to Compensate for Directional Lighting Effects on Face Samples
• Automatic Dataset Cleaning - A Validation Methodology for Large Facial Datasets using Face Recognition
• Face Occlusion Classification for Driving Monitoring System (industrial project)
• Deep Generative Models including BEGAN, ACGAN, DCGAN, Pix2Pix, CycleGAN, StyleGAN etc.
• Ocular Pathologies Classification using DNNs (collaboration with Central Washington University)
• Classification of Iris images captured in different Illuminations