The goal of this project is for you to develop your skills in conducting and communicating original research. Interested students will be supported (and encouraged) by the instructor to submit this semester-long project for publication or as part of your application to find an exciting job opportunity in industry.
For your project, you will design and investigate a novel idea involving machine learning. It will be a self-designed project in consultation with the instructor. The only requirement is it includes a machine learning component with analysis. This is an opportunity for you to enhance your expertise on a topic you feel passionate about.
Your final project will constitute 40% of your total class grade. Your project grade will be calculated as follows:
Your group: you are strongly encouraged to work with a partner (but with instructor approval can work alone)
Research ideas: submit one PDF per group that includes members' names and five ideas for your final project
After submitting your ideas, you will need to choose a 10 minute time slot that works for all group members to meet with the instructor to discuss the ideas. Available time slots will be posted.
When choosing your topic, general guidelines are to:
Choose a problem you have an idea for how to solve
Choose a problem someone else cares about
Choose a problem that is not yet solved (know current literature!)
Choose a problem that you can objectively evaluate by tying it to a task
Revisit advice on how to read a research paper to evaluate your own ideas (e.g,. from the first week of assigned readings)
Project Proposal
The project proposal should:
Establish the research problem and novel idea your group will tackle for your course project.
Identify relevant related work.
You will need to submit one PDF per group that is 1-2 pages long (excluding references). The paper should include each of the following:
Title
[Section 1] Introduction
Paragraph 1: Explain the motivation for your work; e.g., Why anyone should care? What are the desired benefits?
Paragraph 2: Explain why existing solutions are inadequate for the motivated problem; e.g., Is there a gap in the literature? Is there a weakness in existing approaches?
Paragraph 3: Explain what you are proposing, what is novel/new about your idea, and why you believe this solution will be better than previous solutions; e.g., Are you asking a new question, offering a greater understanding of a research problem, establishing a new methodology to solve a problem, building a new software tool, or offering greater understanding about existing methods/tools?
[Section 2] Related Work
Identify 3-5 related topics. Then, for each topic, cite 3-6 related papers (must include the bibliography). Finally, for each cluster of related works, give a 1-2 sentence explanation describing the key difference(s) of your proposed idea to the cluster of prior works. One way to format each topic is as follows:
Topic:
Reference 1
Reference 2
Reference 3
Reference 4
Reference 5
Our work is different from these works because...
Bibliography: this must be formatted correctly.
Please note that your proposed project is not a binding contract. You will continue to update and improve it as you learn more from your readings and/or feedback.
Project Outline Submission
The project outline should map out the entire project. You will be expected to:
Submit a detailed project outline that is 3-4 pages long (excluding references).
Demo your proposed machine learning system; you should have a complete working prototype that you will use for your experiments.
You will need to choose a 10 minute time slot that works for all group members to meet with the instructor to demo the system and receive feedback on the paper. Available time slots will be posted before the due date.
For the project outline, you should submit one PDF per group. The paper should include each of the following:
Title
[Section 1] Introduction (improve upon the material from your proposal)
[Section 2] Related Work (update the material from your proposal so this section includes a paragraph per topic instead of a bullet list per topic)
[Section 3] Methods - describe the implementation of your proposed idea (e.g., features, algorithm(s), training overview.) so that:
A reader could reproduce your set-up
A reader understand why you made your design decisions
It includes a figure illustrating your proposed idea; e.g., a flowchart illustrating the steps in your machine learning system(s)
[Section 4] Experimental Design - describe 2-3 experiments you plan to conduct and indicate the following for each experiment:
Main purpose: 1-3 sentence high level explanation
Dataset(s): 1-3 sentence description of the dataset and how it was collected
Baseline(s): describe status quo method(s) that you will use for comparison
Evaluation Metrics(s): which ones will you use and why?
[Section 5] Experimental Results - for each experiment:
Main finding(s): report your expected results and what you might conclude
Include at least one placeholder figure and/or table for communicating your experimental findings
Include one paragraph to explain what questions are not fully answered by your experiments as well as natural next steps for this direction of research
[Section 6] Conclusions - summarize in one paragraph what you expect will be the take-away point from your work
[Section 7] Bibliography
Final Project Presentation
The final project presentation will involve:
Presenting a 5 minute recorded video about your project.
Taking 5 minutes to answer questions from the audience.
Your video should be no longer than 5 minutes and should do the following:
Motivate the problem your work is designed to solve.
(Very) briefly explain what other solutions are available and why they are not suitable.
Demo your idea, approach, and key design decisions.
Highlight key findings from your experiments and offer insights into what your work has taught us. Focus on finding 1-3 punchlines that explain why your work is exciting/valuable.
Please design your video for an audience who has not taken the class. In other words, your mom, dad, friend, or a potential employer should be able to watch it and understand what you did and why what you did is valuable.
You must submit a URL (either public or unlisted) that links to your video in your Canvas submission. This link will be shared with your peers for the peer evaluation phase.
A best project award will be announced. The best project will be determined by popular vote from the members of the class.
Peer Evaluation
You will evaluate the presentation from every group at the link shared by the instructor. The evaluations will not take time outside of class. The evaluations that you do for other students' projects will not affect your own grade, except that you will be penalized if you do not complete an evaluation (following the requirements) for every group (excluding your own).
Final Project Submission
For the final project submission, you should submit a zip file which contains the following content:
A PDF per group that is a complete research paper.
Your final video presentation, either in .mp4 format or a URL link for its location on the web.
All code for your project.
The paper should be 5-7 pages (excluding references) and include each of the following:
Title
Abstract - one paragraph summary of your paper describing the motivation, problem, conducted experiments, and experimental findings
[Section 1] Introduction (improve upon the material from your project outline)
[Section 2] Related Work (improve upon the material from your project outline; if you have not already, you should remove the bulleted structure you used in the initial proposal and instead have a paragraph form)
[Section 3] Methods (improve upon the material from your project outline)
[Section 4] Experimental Design (improve upon the material from your project outline)
[Section 5] Experimental Results (improve upon the material from your project outline)
[Section 6] Conclusions (improve upon the material from your project outline)