Jieyu Cheng
About Jieyu Cheng
Jieyu Cheng is a Scientist Algorithm Developer with a strong academic background, holding a PhD from City University of Hong Kong and a Master's and Bachelor's degree from Huazhong University of Science and Technology. Cheng specializes in developing algorithms for medical imaging, including an attention-based LSTM neural network for 3D vessel tracking and an automatic carotid vessel segmentation algorithm.
Work at Canon Medical Informatics
Jieyu Cheng currently serves as a Scientist Algorithm Developer at Canon Medical Informatics. Since joining the company in 2020, Cheng has focused on developing advanced algorithms to enhance medical imaging technologies. This role involves applying expertise in algorithm development to improve diagnostic capabilities and patient outcomes.
Education and Expertise
Jieyu Cheng holds a Doctor of Philosophy (PhD) from City University of Hong Kong, completed between 2013 and 2018. Prior to this, Cheng earned a Master's degree from Huazhong University of Science and Technology from 2010 to 2013, and a Bachelor's degree from the same institution from 2006 to 2010. This educational background provides a strong foundation in algorithm development and medical imaging.
Research Experience at Harvard Medical School
From 2018 to 2020, Jieyu Cheng worked as a Research Fellow at Harvard Medical School and Massachusetts General Hospital in the Greater Boston Area. During this period, Cheng contributed to various research projects, focusing on the application of algorithms in medical imaging and analysis.
Previous Research at Robarts Research Institute
In 2015, Jieyu Cheng was a Visiting Researcher at Robarts Research Institute in London, Ontario, Canada, for a duration of four months. This position allowed Cheng to engage in collaborative research efforts, furthering expertise in medical imaging technologies.
Algorithm Development Projects
Jieyu Cheng has developed significant algorithms in the field of medical imaging. Notably, Cheng architected an attention-based LSTM neural network designed for 3D vessel tracking using TensorFlow. Additionally, Cheng created an automatic carotid vessel segmentation algorithm specifically for 3D computed tomography angiography images utilizing C++. These projects demonstrate a commitment to advancing medical imaging techniques.