Hakmook Kang

Dr. Hakmook Kang is devoted to exploring challenges in the field of biostatistics, with a particular emphasis on functional neuroimaging analysis and the likelihood paradigm. As an Associate Professor at Vanderbilt University School of Medicine, he brings a wealth of knowledge and expertise to his research endeavors. Dr. Kang earned his Ph.D. in Biostatistics from Brown University, where he developed a strong foundation in statistical methodologies and their applications to complex biomedical data. His research interests are centered around the development and application of advanced statistical methods for analyzing imaging data, particularly through the use of multi-modal MRI. Dr. Kang is particularly interested in spatio-temporal modeling, which allows for the examination of dynamic processes over time and space within the brain. This approach is crucial for understanding the intricate workings of the human brain and for advancing the field of neuroimaging. Dr. Kang's work also addresses multiple testing problems, a significant challenge in the analysis of large-scale imaging data. By developing innovative solutions to these problems, he aims to enhance the accuracy and reliability of neuroimaging studies. His contributions to the field are not only theoretical but also practical, as they have the potential to improve diagnostic and therapeutic strategies in clinical settings. Through his research, Dr. Kang continues to push the boundaries of biostatistics and its applications in medicine.