General information

Course Logistics

Theme

This is a capstone course. Every student will work on an indiviudal research project. We don't recommend group projects.

Prerequisites and Grading

Prerequisites: Students entering the class should be comfortable with programming and should have a pre-existing working knowledge of linear algebra (MATH 308), vector calculus (MATH 126), probability and statistics (CSE 312/STAT390), and algorithms. For a brief refresher, we recommend that you consult the linear algebra and statistics/probability reference materials on the Textbooks page.

Grading: Your grade will be based on course project (80%), participation in classes (10%), participation in Research Showcase (10%).

Course project: Every student needs to work on an individual project (not as a team, but we will have lots of discussion in the class). Every student might need to briefly update the project progress in every class. Milestone: mid-term presentation, final presentation, final project report.

Research Showcase: 45-minute invited presentation about ongoing computational biology research by Allen School PhD students and the instructor. The instructor will then lead the discussion about the limitation, potential improvement and future directions.

Tentative Schedule

Date Topic Content Discussion
3/28 Welcome/overview. Introduction to CSE428. (Sheng) Sheng will give a brief overview and discuss research projects with each student. Identify 3 papers for further consideration
4/4 Project topic presentation (students) Every student will present the paper they want to study. Why is this problem significant?
4/11 Project updates (discuss briefly, slides are not required) Goal: reproduce the paper. Understand the dataset, task, evaluation setting and metrics. Is the evaluation rigorous?
4/18 Project updates (discuss briefly, slides are not required) Goal: reproduce the paper. Figure out the limitation of the current method. Is the limitation easy to address? Can the limitation be addressed by existing resources (e.g., dataset, GPUs)?
4/25 Project idea presentation (students) How are you going to improve this paper given the limitation you identified in previous weeks? Is your idea sound and doable? What is the potential pitfall?
5/2 Project updates (discuss briefly, slides are not required) Do you have enough resources to implement this idea?
5/9 Working time + research showcase Students can schedule Zoom meeting with Sheng to debug your projects. Mon, Wed, Fri night 8-10pm PST time.
5/16 Working time + research showcase Students can schedule Zoom meeting with Sheng to debug your projects. Mon, Wed, Fri night 8-10pm PST time.
5/23 Most of the work are done. what other analysis can you perform? Corner case?
5/30 Final project presentation (students)