Qualifications:

• 2011-2014 PhD Statistical Genetics, Cambridge

• 2008-2009 MSci Bioinformatics, Imperial College

• 2003-2007 MEng Computer Science, University College

Projects:

• Eye2Gene

• Moorfields AI Pipeline

Expertise:

• Computational Image Analysis

• Machine Learning & Deep Learning

• Genetics & Bioinformatics

• Automated Text Analysis

• Databases

Deputy director of Moorfields Reading Centre & Clinical AI Lab since December 2022. I oversee the data science team. My background is in computer science, bioinformatics and machine learning. I have been working in ophthalmology since 2015. Our multidisciplinary data science team primarily develops and validates algorithms to automate image analysis to detect and quantify disease and monitor progression. Our team also develops algorithms to automate analysis of electronic health records for effects screening and retrieval of relevant data. We work closely with the Department of Digital Medicine to translate our work into improved service delivery for patients. As well as innovating, my team and I work hand in hand round the clock with doctors and graders to ensure all the software tools and services are in place to ensure the high-quality and completion of our clinical trials. I also conduct my own research on rare retinal and corneal conditions at my UCL lab.

Dr Moghul is an expert in data science and software development with experience large-scale, high-throughput image analysis and omics processing.

Dr Naik is a computer scientist with expertise in medical imaging. He develops annotation tools to assist graders and build training datasets for AI. He aspiration is to combine AI and human to build interactive annotation tools (Bayesian online learning).

Dr. Pallavi Bagga is a Postdoctoral Researcher Fellow - Data Science at Moorfields Eye Hospital, London with expertise in multi-modal imaging. She develops AI algorithms for structural (OCT, FAF, OCT-A) and functional microperimetry for eye exams. She has recently started working on a project for diagnosing late stage dry age-related macular degeneration (Geographic Atrophy) from imaging using deep learning.

Before joining Moorfields, Pallavi worked as a Digital Fellow (and a Postdoctoral Researcher) at Barts Health NHS Trust, London, for a year, on another deep learning project for automating the cardiac MRI process. She also worked as a Teaching Assistant/Teaching Fellow in the Department of Computer Science at Royal Holloway, University of London (RHUL). Before joining RHUL, Pallavi worked as an Assistant Professor at Lovely Professional University, India.

She holds a Ph.D. in Computer Science from Royal Holloway, University of London, UK, an M.Tech. in Computer Science & Engineering from DAV University, India, and a B.Tech. in Computer Science & Engineering from Punjab Technical University, India. Her primary areas of research interest include Agent Negotiation and Machine Learning.

Qualifications:

• 2018-2019 MSci Computer Vision, University College London

• 2014-2018 BSci Electrical and Electronics Engineering, University of Liverpool

** Qualifications: ** * 2012: BA, University of Cambridge * 2015: BM BCh, University of Oxford * 2022: FRCOphth, Royal College of Ophthalmologists

** Projects: ** * EyeNote: Extraction of ocular measurements from clinical notes using Natural Language Processing * FACE AI: Automated detection of oculofacial parameters using Artificial Intelligence * HERMES: Teleophthalmology-enabled and artificial intelligence-ready referral pathway for community optometry referrals of retinal disease

Resourceful expert in Scientific Programming and Data Science, with a foundation in Physics. My focus revolves around data infrastructure, AI, and applications in ophthalmology. My background includes a wealth of expertise in computational biology and bioinformatics, complemented by extensive experience in collaborative teamwork and troubleshooting complex problems. My goal is to develop solutions for the automation of scientific research procedures with a passion for innovation.

Robbert is developing AI models to classify AMD and ROP.

Tim is developing models to classify papilledema, predict AMD outcome, and find associations with systemic diseases.

Role:

• National Institute for Health Research Academic Clinical Fellow
• Honorary Clinical Research Fellow, Moorfields Eye Hospital
• Specialty Registrar in Ophthalmology, Imperial College Healthcare NHS Trust

Qualifications:

• 2009: BA (hons), University of Oxford
• 2012: BM BCh, University of Oxford
• 2017: FRCOphth, Royal College of Ophthalmologists

Projects:

• Data linkage: Retinal Imaging and Neurodegenerative Disease (AlzEye)
• Outcomes and Insights from Age-Related Macular Degeneration Analytics
• Automated Machine Learning in Ophthalmology

Expertise:

• Epidemiology
• Biostatistics
• Image analysis
• Oculomics
• Data science