Secondary Appointments in Computer Science, Neuroscience and Physics at Georgia State University, with additional appointments at Georgia Institute of Technology (Electrical and Computer Engineering, Biomedical Engineering) and Emory University (Neurology, Radiology, Psychiatry, Biomedical Engineering).
Signal processing, medical image analysis, brain imaging, data fusion, machine learning, deep learning, neuroinformatics, data science, magnetic resonance imaging
Dr. Calhoun is the founding director of the tri-institutional Center for Translational Research in Neuroimaging and Data Science, which is focused on improving our understanding of the human brain using advanced analytic approaches with an emphasis on translational research such as the development of predictive biomarkers for mental and neurological disorders. The use of big data approaches and neuroinformatics tools to capture, manage, analyze, and share data is also a major emphasis.
Dr. Calhoun develops techniques for making sense of brain imaging data. The use of flexible/data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However, such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. Because each imaging modality has limitations, the integration of these data is needed to understand the healthy and especially the disordered human brain. He has created algorithms which map dynamic networks of brain function, structure, and genomics and how these are impacted while being stimulated by various tasks or in individuals with mental illness such as schizophrenia. He has released multiple software tools as well as advanced neuroinformatics tools for data management and sharing.
Dr. Calhoun is the author of more than 650 peer-reviewed journal articles and over 750 technical reports, abstracts and conference proceedings. Much of his career has been spent on the development of data driven approaches for the analysis of brain imaging data. He has won over $100 million in NSF and NIH grants on various topics including the incorporation of prior information into independent component analysis (ICA) for functional magnetic resonance imaging, data fusion of multimodal imaging and genetics data, and the identification of biomarkers for disease.
Dr. Calhoun is a fellow of the Institute of Electrical and Electronic Engineers, The Association for the Advancement of Science, The American Institute of Biomedical and Medical Engineers, the International Society of Magnetic Resonance in Medicine, and the American College of Neuropsychopharmacology (ACNP). He is also a member and regularly attends the Organization for Human Brain Mapping, the International Society for Magnetic Resonance in Medicine, the International Congress on Schizophrenia Research, and the ACNP. He is also a regular grant reviewer for NIH and NSF. He has organized workshops and special sessions at multiple conferences. He is currently chair of the IEEE Machine Learning for Signal Processing (MLSP) technical committee. He is a reviewer for many journals and is on the editorial board of the Brain Connectivity and Neuroimage journals and serves as Associate Editor for Journal of Neuroscience Methods and several other journals.