This course is a semester-long series of seminars presented by graduate students, complemented by occasional presentations by invited faculty and external visitors. The course is designed for graduate students enrolled in the Graduate Certificate Program in Statistics and Machine Learning, but is also open to others with permission of the instructor.
The course is designed so that graduate students can be exposed to, benefit from, and actively contribute to the scholarly research of their peers. It will provide the opportunity for students to organize their thoughts on a research topic in a way suitable for a public presentation, to give opportunities for practice in the preparation and delivery of a research presentation, and to receive valuable feedback from their peers. It is also intended to foster the growth of a supportive community of young scholars with shared research interests in modern statistics and machine learning.
Each workshop will feature a presentation by a graduate student. A second student will introduce the speaker and give some brief background to the work, and a third student will moderate the post-presentation discussion. Every student is expected to read the circulated material prior to the workshop and to come prepared to engage in conversation with the presenter, other students and attending faculty during the discussion period.
Each participant is required to select and discuss their topic with the instructor no later than two weeks prior to their presentation, and to make relevant supporting materials available to all enrolled students one week prior to the presentation. Second and third- year students can elect to present a recent research paper of sufficiently broad interest. More senior students are expected to present their own research, preferably documented as a draft conference, journal paper or draft thesis chapter. The course is not open to first-year students.
The order of presentations and assignment of student roles will be decided in an organizational meeting at the beginning of the semester. Each semester, the seminar may also include several presentations from external speakers, faculty members or post-doctoral fellows. These visitors will be selected with the goal of exposing the students to recent results of sufficiently broad interest in the areas of statistics and machine learning.
Students will be assessed based on their attendance, and their roles as presenters, introductory commentators, discussion moderators and engaged discussion participants.
Enrollment to the Course
For enrollment, please use this form: SML 510 Enrollment Form