Course projects are carried out in groups. You are encouraged to select a project from the list of given projects (check Canvas).
You may also choose a project with focus on implementation or original research. This option requires early discussion with the instructor and getting approval.
Potential topics:
MatchU.ai: contribute to the MatchU.ai project by developing a known matching algorithm and visualizing the process step-by-step. For potential projects, please look into solutions available on MatchU.ai and contact the instructor with your ideas.
Empirical: Implementation and quantitative analysis of algorithms presented in class using simulation (synthetic) or real data.
Theoretical/algorithmic: Develop new models for a problem, prove new observations about algorithms and/or design new algorithms for a problem.
Milestone 1: Oct. 30
Milestone 2: Nov. 21
Final report (due Dec. 12): Up to 5 pages (excluding references)