Navigating research through interfaces: brain imaging, computational and systems biology, and deep learning
Interesting and rewarding research happens at the interfaces between established fields. In this talk, he will share his experiences as a computational scientist and lessons he learned by working at the interfaces between computer science, biology, and medicine. he began his research during heydays of early neural networks when backpropagation was invented. His graduate research focused on building neural network models to solve computer vision applications. That earned him research positions in the analysis of brain imaging for investigations of brain function and disease. With the sequencing of the human genome, he moved to computational and systems biology to understand the molecular basis of diseases and find novel biomarkers and therapeutics. He now investigates how to harness the power of deep learning to unravel knowledge embedded in life sciences and medical imaging data.
His journey starts from engineering to basic research to industry sponsored research. He will take snapshots of his research works to illustrate opportunities in brain imaging, computational and systems biology, and deep learning; and will share leant lessons useful for early researchers. To survive and thrive in today’s research, one needs to embrace latest technologies and makes use of open-source codes and public-domain databases. Multidisciplinary research requires openness for collaborations between scientists working in vastly different areas.