Flatiron Health
I am excited to be joining Flatiron Health as a machine learning research intern for the summer of 2021. I look forward to contributing to their machine learning endeavours as part of their mission to improve cancer care.
Hello, my name is Dani Kiyasseh and I am a PhD student at the Computational Health Informatics Lab., at the University of Oxford. My research focuses on designing deep learning algorithms to do 'more with less' in the context of cardiac data. Before this, I graduated from The Johns Hopkins University with a degree in biomedical engineering.
I am excited to be joining Flatiron Health as a machine learning research intern for the summer of 2021. I look forward to contributing to their machine learning endeavours as part of their mission to improve cancer care.
Throughout my PhD, I have focused on designing clinical deep learning algorithms that are less dependent on data, labels, and medical supervision. This has involved leveraging generative modelling, self-supervised learning, and continual learning.
In the summer of 2020, I interned at Merck & Co where I designed a meta-learning paradigm for data-efficient cardiac MRI segmentation.
In the summer of 2019, I interned at the Department of Cardiovascular Medicine at the Mayo Clinic where I implemented self-supervised algorithms for coronary angiograms.
In the summer of 2017, I interned at the Machine Learning Center of Excellence at Ford Motor Company where I used diagnostic trouble codes to predict vehicular malfunction.
In the summer of 2016, I performed research at the Musculoskeletal Lab at Imperial College London to identify pressure distributions within lower-limb prosthetic cuffs.
During my undergraduate studies, I performed research at the Neuroengineering Lab at The Johns Hopkins University to design and manufacture an upper-limb prosthetic device for data collection purposes.
Feel free to contact me