About

Daniel Chen is a highly skilled PhD candidate in Genetics, Bioinformatics, and Computational Biology at Virginia Tech. He is currently working at the Social and Decision Analytics Laboratory in the Biocomplexity Institute at Virginia Tech where he is developing a Python package that implements a cognitive psychology framework of attitudes using Artificial Neural Networks within social networks. His research interests include understanding how attitudes change and spread within social networks as well as performing analytics for precision medicine. Daniel's educational background includes a Master of Public Health (MPH) in Epidemiology from Columbia University and a Bachelor of Arts in Psychology - Behavioral Neuroscience with minors in Biology and Computer Science from the Macaulay Honors College at CUNY Hunter College. He has also completed a Doctor of Philosophy (PhD) in Genetics, Bioinformatics, and Computational Biology from Virginia Tech. In addition to his academic achievements, Daniel is also a talented instructor and volunteer. He enjoys teaching and has volunteered his time to Software Carpentry by teaching, serving on the Mentoring subcommittee, and chairing the Assessment subcommittee. He has also worked as a Volunteer Instructor at Software Carpentry where he helped maintain, edit, and contribute to lesson material and taught novice learners Bash, Python, R, Git, and SQL. He has also worked as a Data Scientist at Lander Analytics where he wrote lesson material for Python programming and data analysis and taught and assisted workshops on R and Python. Daniel's technical skills include Research Scientist, Python, Data Scientist, Spark, SQL, Neural Networks, and infra. He has 3.95 years of relevant experience and is a valuable asset to any team he works with.