Hi, my name is Mengjie Chen.
I'm an assistant professor in the Department of Biostatistics and Genetics at UNC-Chapel Hill.
I graduated from the interdisciplinary program of Computational Biology and Bioinformatics at Yale University in 2014. I was co-advised by Professor Hongyu Zhao in Department of Biostatistics and Professor Haifan Lin, who is a stem cell biologist. Before that, I did my undergraduate majoring in Biotechnology from Huazhong University of Science and Technology in China (09').
High-throughput technologies have been increasingly applied in a broad range of scientific research. These technologies present researchers with the task of extracting meaningful information from high-dimensional data spaces, where hundreds or thousands measurements concurrently obtained from a relative small number of samples. My primary research is driven by the need for powerful statistical methods to address the challenges those technologies have posed for data analysis and interpretation, particularly for data emerging from biological and biomedical studies, such as epigenetic and cancer genomics related research.
I hope my future methodology research will contribute to the integration of genomic feature into the prediction of clinical outcomes, which will potentially shed new lights on personalized disease diagnosis and treatment.
The following is a word cloud made from my research statement.
I'm an assistant professor in the Department of Biostatistics and Genetics at UNC-Chapel Hill.
I graduated from the interdisciplinary program of Computational Biology and Bioinformatics at Yale University in 2014. I was co-advised by Professor Hongyu Zhao in Department of Biostatistics and Professor Haifan Lin, who is a stem cell biologist. Before that, I did my undergraduate majoring in Biotechnology from Huazhong University of Science and Technology in China (09').
High-throughput technologies have been increasingly applied in a broad range of scientific research. These technologies present researchers with the task of extracting meaningful information from high-dimensional data spaces, where hundreds or thousands measurements concurrently obtained from a relative small number of samples. My primary research is driven by the need for powerful statistical methods to address the challenges those technologies have posed for data analysis and interpretation, particularly for data emerging from biological and biomedical studies, such as epigenetic and cancer genomics related research.
I hope my future methodology research will contribute to the integration of genomic feature into the prediction of clinical outcomes, which will potentially shed new lights on personalized disease diagnosis and treatment.
The following is a word cloud made from my research statement.
