CV

Senior Data Scientist

University of Colorado Anschutz Medical Campus

Pioneered novel image processing pipelines using computer vision and deep learning, enabling automated analysis longitudinal ophthalmic images.

• Leveraged transformers and convolution networks for various tasks - image registration, segmentation, classification, object detection.
• Optimizing our large ophthalmology EHR database using SQL techniques to correct systemic issues, enhancing operational efficiency of our lab.
• Contributed to NIH R01 and R21 grants.
• Published and presented research at top medical and ML venues (MICCAI, ARVO).

Software Engineer Intern

Phenopolis

• Deployed deep learning models on Amazon Web Services using AWS Lambda and Serverless Framework.
• Contributed to the development of Eye2Gene web app which inputs fundus autofluorescence, OCT and infrared imaging and outputs automated disease diagnosis – this app was recently integrated into the Heidelberg Spectralis imaging device diagnostic platform.
• Learning software Development best practices – unit-testing, documentation, version-control, agile development.

Honorary Researcher

Pontikos Lab, University College London

• Researched generative AI methods for retinal image analysis.
• Collaborated with world-leading ophthalmologists at Moorfields Eye Hospital.
• Presented research at UCL Healthcare Engineering Symposium (2021), UCL Institute of Ophthalmology Symposium (2022), and Stanford AI+Health Conference (2022).

Data Science Intern

Perfios Software Solutions

• Investigated supervised deep learning models (convolutional neural networks) for cardiac image analysis.
• Implemented segmentation algorithms (UNets) from scratch using Keras.
• Studied cardiac imaging fundamentals with the help of clinicians at Barts Cardiac Centre.

Student Researcher

St. Bartholomew’s Hospital

• Investigated supervised deep learning models (convolutional neural networks) for cardiac image analysis.
• Implemented segmentation algorithms (UNets) from scratch using Keras.
• Studied cardiac imaging fundamentals with the help of clinicians at Barts Cardiac Centre.

Doctor of Philosophy (Ph.D.)

University of California, San Francisco and University of California, Berkeley

Computational Precision Health

• Advisor - Dr. Rima Arnaout

Master of Science (MSc)

University College London

Machine Learning

• GPA - 3.81
• Thesis Title - SynthEye - Generating Realistic Retinal Images using Generative Adversarial Networks

Bachelors of Science (BSc)

University College London

Applied Medical Sciences

• GPA - 3.84
• Thesis Title - An Investigation into Automating Cardiac MRI Planning Using Deep Learning

Best overall student at UCL

Physiological Society

Nominated by Prof. Nephtali Marina-Gonzalez among all students in UCL Division of Medicine.

Second Prize - Team Traverse

UCL COVID-19 Innovation Challenge

Lead the team “Traverse” in a mock Dragon’s Den competition. Proposed an RFID-based tracking system with graph-AI for identifying transmission hotspots in hospitals. Featured on UCL Website.