CSE 290B: Seminar on Advanced Data Science

Seminar Overview and Goals

Data science is an emerging interdisciplinary area, whose foundations lie in the massive intersection of the fields of data management, data mining, machine learning, machine perception, statistics, optimization, visualization, and human-computer interaction. Data science is transforming the way researchers and practitioners work in the sciences, humanities, and engineering, the way companies obtain business insights, and even the way government and society itself function, given the explosion in the amount and diversity of data being captured and exploited (aka "Big Data").

The goal of this seminar is to give students a better understanding of the state of the art in this emerging area, especially in terms of high-profile applications of data science and "Big Data" analytics, but also the techniques and tools used in data science. Students will also acquire the skills of reading papers in this area and presenting them to a technical audience.

NB: In contrast to CSE 291G from Winter 2017, the papers in this seminar's reading list will be less systems-focused and more focused on cutting-edge applications and techniques of data science.


Seminar Meetings: Wed 3:30-4:50pm; CSE 2154

Organizer: Arun Kumar; Office: CSE 3218

Seminar Content and Format

  • There is a weekly reading list of papers and articles on both the applications and foundations of data science.

  • Students are expected to read all papers in the reading list. Each student has to present one paper from the reading list in class and steer a discussion about the paper. Students will be randomly assigned to papers by the organizer.

  • Each seminar will have 2 presentations.

  • Students are free to chose how they want to present: slidedeck or whiteboard. The content should be well-organized, readable, and well-presented.


Courses on databases, data mining, machine learning, statistics, visualization, and HCI (not necessarily all of them, but at least some of them), or consent of the organizer. Students should also learn the basics of new application domains on their own.


Enrollment is capped at 27 students (PhD and MS). Please add yourself to the wait list. If no more than 27 students get wait listed, all will be enrolled; otherwise, a questionnaire will be released to help the organizer make enrollment decisions.


This is a 1-credit pass-fail seminar. The requirement for a pass grade is to present one of the papers/articles and also attend most of the other presentations.