The Biomedical Data Driven Discovery (BD3) Training Program at Northwestern University (NU) is a collaborative proposal that brings together Big Data educators and researchers from the Feinberg School of Medicine (FSM), the McCormick School of Engineering and Applied Science (MEAS), the Weinberg College of Arts and Sciences (WCAS) and the School of Communication. The goal of BD3 is to train Big Data scientists for both academic and industry research positions, who will develop the next generation of methodologies and tools. BD3 will to create a truly multidisciplinary data science training environment. In doing so, BD3 will encompass multiple departments and degree-programs, leveraging three existing data-intensive doctoral programs-- the well-established and nationally recognized program in Data Analytics in MEAS, led by Diego Klabjan, PhD, and two innovative and growing programs led by Justin Starren, MD, PhD: the Informatics track of the Driskill Graduate Program, focusing on Bioinformatics, and the Informatics track of the Health Sciences Integrated Program, focusing on clinical and population informatics. Together, Drs. Klabjan and Starren have expertise that spans three critical areas: computer science/informatics, statistics/mathematics, and biomedical domain knowledge. BD3 brings together the biomedical Big Data and domain expertise across multiple departments of FSM with methodological expertise in computation, informatics, statistics, and mathematics. The program will recruit three candidates per year and support each trainee for two years. Success in data science requires mastery of three distinct skill sets: 1) an understanding of the target domain, 2) an understanding of the nature and structure of the data within that domain, and 3) a mastery of the computational and statistical techniques for manipulating and analyzing the data. This translates into a number of more specific competencies, including: deep Domain Knowledge in the target domain, Statistical Methods, Computer Programming, Ontologies, Databases, Text Analytics, Predictive Analytics, Data Mining, Analytics for Big Data, and Responsible Conduct of Research. BD3 will utilize a co-mentoring model, with each student having a domain mentor and a methodological mentor. Each student's program will be based on an Individual Development Plan (IDP). Students will have many opportunities for both laboratory and industrial rotations leveraging well-established programs at MEAS. Additional educational activities include: an annual retreat, monthly trainee meetings, departmental seminars and speakers, journal clubs, teaching training and experience, and writing and presentation training. Trainees benefit from extensive institutional support for this program, such as: tuition supplements, stipend supplements, administrative support, the Writing Workshop for Graduate Students, the Searle Center for Advancing Learning and Teaching, the Management for Scientists and Engineers, nationally recognized mentor and mentee training programs, and formal training in Team Science.
The Biomedical Data Driven Discovery (BD3) Training Program at Northwestern University brings together Big Data educators and researchers from the Feinberg School of Medicine, the McCormick School of Engineering and Applied Science, the Weinberg College of Arts and Sciences and the School of Communication to create a truly multi-disciplinary data science training environment. The proposal leverages three existing data-intensive doctoral programs-- the well-established and nationally recognized program in Data Analytics in McCormick, led by Diego Klabjan, and two innovative and growing programs at Feinberg led by Justin Starren: the Informatics track of the Driskill Graduate Program, focusing on Bioinformatics and the Informatics track of the Health Sciences Integrated Program (HSIP), focusing on clinical and population informatics. The aim of BD3 is to train future scientists for both academia and industry who will develop novel Big Data methods to advance science and improve health.
| Zimmerman, Lindsay P; Goel, Satyender; Sathar, Shazia et al. (2018) A Novel Patient Recruitment Strategy: Patient Selection Directly from the Community through Linkage to Clinical Data. Appl Clin Inform 9:114-121 |
| Benjamin, Ari S; Fernandes, Hugo L; Tomlinson, Tucker et al. (2018) Modern Machine Learning as a Benchmark for Fitting Neural Responses. Front Comput Neurosci 12:56 |
| Suresh, Aneesha K; Winberry, Jeremy E; Versteeg, Christopher et al. (2017) Methodological considerations for a chronic neural interface with the cuneate nucleus of macaques. J Neurophysiol 118:3271-3281 |
