Open to doctoral candidates and to qualified M.S. candidates with instructor's permission. Recent experimental and theoretical developments in various areas of photonics research. Examples of topics that may be treated include squeezed-light generation, quantum optics, photon detection, nonlinear optical effects, and ultrafast optics.
This course is designed to provide the student with the knowledge and skills necessary to serve as a member and lead interdisciplinary groups in organizational assessment to identify systems issues and facilitate organization-wide changes in practice delivery utilizing quality improvement strategies. Course content focusses on understanding systems concepts and thinking to achieve results in complex health care delivery systems. Frameworks, approaches, and tools that foster critical thinking are examined as mechanisms to formulate vital questions, gather and assess relevant information, develop well-reasoned conclusions, test conclusions against relevant standards, compare conclusions with alternative systems of thought, and communicate effectively throughout the process.
This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search
This course will introduce students to the theoretical and practical aspects of applying a “causal roadmap” to research questions in epidemiology using both single timepoint and longitudinal data. A causal roadmap approach to empirical investigation is intended to strengthen transparency and clarity in the research process and typically consists of several steps including: 1) formulating a research question, 2) translating it into a causal quantity, 3) listing the assumptions required to identify this causal quantity from the data, 4) choosing an estimation approach, and 5) doing the analysis. We will learn single timepoint and longitudinal g-computation/ standardization, inverse-probability-of-treatment weighting (IPTW), and doubly robust estimation approaches (e.g., targeted minimum loss-based estimation (TMLE)). The final class will include integrating machine learning into the estimation approach. Each module will include hands-on exercises in R in which we will apply the estimation approaches to data. Data for each analysis exercise will be provided by the instructor. For the final project, students can choose to use data provided by the instructor or data for which they already have access.
Students in the Biological Science PhD program only. Independent research in approved thesis sponsor laboratories.
Doctoral candidates are required to make an original investigation of a problem in biomedical engineering, the results of which are presented in the dissertation.
Prerequisites: The qualifying examinations for the doctorate. Open only to certified candidates for the Ph.D. and Eng.Sc.D. degrees. Doctoral candidates in chemical engineering are required to make an original investigation of a problem in chemical engineering or applied chemistry, the results of which are presented in their dissertations. No more than 15 points of credit toward the degree may be granted when the dissertation is accepted by the department.
All doctoral students are required to attend the department seminar as long as they are in residence. No degree credit is granted.
This is a course during which the mid-career executives who are enrolled as students in the Executive MPA program exhibit and share professional work they have managed or directly created during their first year in the program. Materials are presented to the faculty and students for criticism, analysis, and potential improvement.
All doctoral students are required to complete successfully four semesters of the mechanical engineering seminar MECE E9500.