Research Fellow at Harvard Medical School and Massachusetts General Hospital
Shaun’s research is focused on understanding how neurons encode and process information to produce complex cognition and behavior. Shaun plans to apply the tools and skills learned in the bootcamp to rapidly prototype and deploy predictive analytics to distill complex patterns of neurophysiological activity into meaningful measures that can be used to strengthen our understanding of cognition and improve therapies to treat neurodegenerative and psychiatric illness.
PhD in Environmental Engineering and Water Resources at Princeton University
(Joyce) Wang’s research focuses on impacts of climate change and remote sensing of hydrologic systems. She wants to use the skills developed at the bootcamp to improve the estimation of hydrological and meteorological variables using data analytics and machine learning techniques.
PhD in Pathobiology at the University of Washington
Emilia’s research in Dr. Tim Rose’s lab at Seattle Children’s Research Institute involves managing and analyzing large sets of high throughput sequencing data. She plans to use the tools she learned at Data Science Dojo to help her team understand the changes produced in both viral and host cell gene expression when cells are infected with Kaposi’s Sarcoma-associated Herpes virus, the virus associated with the most common form of cancer affecting HIV+ patients.
Technology Program Manager – Data Science & Products
Michael manages and analyzes large, diverse and unstructured sustainability datasets for trends that support the greater disclosure of sustainability information for the public. He plans to use the knowledge and skills learned from the bootcamp to scale SASB’s machine learning pilot program, develop prediction models, and leverage big data cloud storage and compute resources.
PhD in Applied Math at Illinois Institute of Technology
Ting’s research focuses on generating efficient algorithms for computing complex nonlinear systems and devising new techniques for uncertainty quantification on non-Gaussian data. She hopes to use what she learns in this workshop to do magic with big data: to gain more information hidden behind data during her future data analysis work.
PhD Candidate in Decision Analysis at Stanford University
Noah’s research project revolves around helping individuals, institutions and governments make better decisions by subjecting the field of decision analysis to philosophical scrutiny. His hope is to make decision analysis clearer and better connected with the humanities and to produce empirically testable theories that ground decision analysis in reality.
Assistant Policy Analyst at RAND Corporation
Christina works on population health and health services research, trying to understand health risk behaviors and identify levers for positive behavior change. With the tools learned in the bootcamp, she hopes to use big data to serve the public through policy research that informs social and health policy decision-making.