Big Biomedical Data in Brain Informatics

02/13/2017 - 3:00pm
Ruogu Fang, Ph.D., Assistant Professor, School of Computing and Information Sciences, Florida International University
Communicore, C1-17


Big data has made significant impacts in every aspect of our life. Biomedical and health fields have accumulated huge amount of data (with 500 petabytes in 2012 and 25 exabytes in 2020 expected). However, the explosive growth of digital health data does not mean the same increase of knowledge growth. In this talk, I will present the big picture of the challenges faced by the world and the US healthcare system in the age of big biomedical data, and opportunities open for research, and our advances on using the big biomedical data for more accurate and safer medical diagnosis and treatment. This talk will focus on the leveraging of Big Biomedical Data for robust, safe and effective brain informatics. With the ever-increasing amount of biomedical data and health informatics in the hospitals and medical centers across the world, exploitation of the large-scale biomedical data would provide invaluable information for the biomedical data processing and analysis. The quality of biomedical data is a great challenge at low radiation dose and short acquisition time. Learning-based biomedical data is an inter-disciplinary field that bridges machine learning, data mining, neural engineering, genomics, health informatics and medical imaging. It offers flexible and effective approaches to exploit the inherent structure of the massive biomedical data.



Dr. Ruogu Fang is an Assistant Professor of the School of Computing and Information Sciences at Florida International University. Dr. Fang received her Ph.D. from Cornell University in 2014, and B.Eng. from Zhejiang University with highest honor in 2009. Dr. Fang's research interests focus on big medical data, neuron imaging, biomedical informatics, brain dynamics, machine learning and data mining. She is the recipient of numerous grants, honors and awards, including NSF CRII (pre-CAREER) award as PI, ORAU’s Ralph Lowe Young Faculty Enhancement Award, Robin Sidhu Memorial Young Scientist Award from Society of Brain Mapping and Therapeutics, Best Paper Award at IEEE International Conference on Image Processing, Hottest Paper in Medical Image Analysis, Hsien Wu and Daisy Yen Wu Memorial Award and Irwin and Joan Jacobs Fellowship, to name a few. She has published over 30 peer-reviewed articles, including flagship journals such as IEEE Transaction on Medical Imaging, Medical Image Analysis, ACM Computing Survey, etc. She served as the Co-Chair of the International Workshop on Sparsity Techniques in Medical Imaging, and the guest chief editor of the Journal Computerized Medical Imaging and Graphics. Prof. Fang’s Smart Medical Informatics Learning and Evaluation (SMILE) Lab aims to explore intelligent approaches to bridge the data and medical informatics in the era of big medical data. More information at about SMILE lab: