Recent PhD Graduate from the Biomedical Image Analysis Group (BioMedIA) at Imperial College London specialising in computer vision and machine learning tasks for image analysis.

Projects included:

• Automated Quality Control of Image Segmentations (repo)
• Algorithmic Bias Mitigation via Domain Adaptation (repo)
• Explainability of Deep Learning Frameworks

Udacity Data Engineering Nanodegree Graduate

Projects included:

• Data Modelling with PostgreSQL (repo)
• NoSQL Databases with Apache Cassandra (repo)
• Data Warehouses with Amazon Redshift (repo)
• Data Lakes with Apache Spark (repo)
• Data Pipelines with Airflow (repo)
• Capstone Project (repo)

• Image-level Harmonization of Multi-Site Data with Image-and-Spatial Transformer Networks - MICCAI 2020
• Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects - MedNeurIPS 2019
• Automated Quality Control in Image Segmentation: Application to UK Biobank Cardiac MRI Study - JCMR 2019
• Real-time Prediction of Segmentation Quality - MICCAI 2018
• Automatic Quality Control of Cardiac MRI Segmentation in Large-Scale Population Imaging - MICCAI 2017
• Electrophysiological Substrate for a Dominant Re-entrant Source during Atrial Fibrillation - IEEE EMBS 2009
• Subject-level Prediction of Segmentation Failure using Real-Time Convolutional Neural Nets - MIDL 2018