Overview
Course description: This course introduces PhD students in SCI to the program and prepares them for their journey. In introduces students to the milestones of the program. It overviews the scientific enterprise, including tips on collaborations, funding, and the conference/journal review process. It discusses creativity and generating well-grounded, novel ideas. It reviews the scientific method, including hypothesis testing and statistical significance. It provides advice and practice on writing, reviewing, revising, and presenting one’s work. It explores using AI effectively and ethically. It describes strategies for teaching and career planning. It includes presentations from the students, including literature reviews, comparing/contrasting successful/unsuccessful paper versions, idea pitches, and full project presentations. It also features guest speakers (senior students and/or faculty).Prerequisites: None, but note course only counts for the PhD program.
Canvas: We will use it for one assignment turn-in, tracking grades, and sending announcements.
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Policies
Grading
Grading will be based on the following components:- Participation in discussions, questions asked, offering feedback: 20%
- Literature review team presentation: 15%
- Paper pair (successful/unsuccessful version) presentation: 10%
- Idea pitch and revision thereof: 25%
- Paper section drafts, responding to feedback, revising: 15%
- Project presentation: 15%
Collaboration Policy and Academic Honesty
You will do your work individually, unless otherwise stated. You will may use AI to help with writing, but must document your use, including showing your draft/notes that prompted the AI model with. You may use AI to help with finding relevant papers for your research (i.e. using AI as a search engine). You will always cite your sources and tools/materials you used. When in doubt about what you can or cannot use, ask the instructor. A first offense will cause you to get 0% credit on the assignment. A report will be filed with the school. A second offense will cause you to fail the class and receive disciplinary penalty. Please consult SCI's Academic Integrity Policy. Also make sure you are familiar with the concept of plagiarism.Note on Disabilities
If you have a disability for which you are or may be requesting an accommodation, you are encouraged to contact both your instructor and Disability Resources and Services (DRS), 140 William Pitt Union, (412) 648-7890, drsrecep@pitt.edu, (412) 228-5347 for P3 ASL users, as early as possible in the term. DRS will verify your disability and determine reasonable accommodations for this course.Note on Medical Conditions
If you have a medical condition which will prevent you from doing a certain assignment, you must inform the instructor of this before the deadline. You must then submit documentation of your condition within a week of the assignment deadline.Statement on Classroom Recording
To ensure the free and open discussion of ideas, students may not record classroom lectures, discussion and/or activities without the advance written permission of the instructor, and any such recording properly approved in advance can be used solely for the student's own private use.[top]
Schedule
| Week of | Topics | In-class work and homework | |
| Aug 25 | Intro, course structure, PhD at Pitt, integrity | lecture (slides) | |
| Sept 1 | Scientific enterprise, collaborations, funding, conference/journal review process | lecture (slides) | |
| Sept 8 | Generating research ideas | lecture (slides) | |
| Sept 15 | Scientific method, hypothesis testing | lecture (slides) | |
| Sept 22 | Publishing: writing, reviewing, rebuttals, presenting your work | lecture (slides) | |
| Sept 29 | Literature review team presentations, discussion of future ideas | presentations | |
| Oct 6 | Paper pair (accepted/rejected version: focus on framing) presentations | presentations | |
| Oct 13 | Idea pitch – v1 | presentations | |
| Oct 20 | Senior grad student mini talks and panel | guest speakers | |
| Oct 27 | Using AI effectively and responsibly | lecture (slides) | |
| Nov 3 | Idea pitch – v2 | presentations | |
| Nov 10 | Teaching, mentoring, being mentee, career planning | lecture (slides) | |
| Nov 17 | Related work, method and experiment setup writeup: review, feedback, revisions | writeup (hw); reviews | |
| Nov 24 | No class (Thanksgiving) | ||
| Dec 1 | Project presentations, feedback | presentations | |
| Dec 8 | tbd | ||
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Readings
Integrity:- On Being a Scientist: Responsible Conduct in Research
- Guidelines for Responsible Conduct of Research (Pitt)
- Guide to CS PhD students at Pitt
- Keshav, How to Read a Paper, ACM SIGCOMM Computer Communication Review 37(3): 83-84, July 2007.
- Hanson and McNamee, Efficient Reading of Papers in Science and Technology
- Fong, How to Read a CS Research Paper, July 2004.
- Griswold, How to Read an Engineering Research Paper
- Griswold's paper comprehension template
- Hill and McKinley, Notes on Constructive and Positive Reviewing, May 2005.
- Smith, The Task of the Referee, IEEE Computer 23(4), April 1990.
- Roscoe, Writing reviews for systems conferences, March 2007.
- Belongie, Paper gestalt
- Huang, Deep paper gestalt
- Gao et al., Does my Rebuttal Matter?
- Su and Crandall, The Affective Growth of Computer Vision
- Real ML reviews: 1, 2, 3, 4
- Raskar, How to Invent
- Strunk and White, The Elements of Style
- Jones, How to write a great research paper
- Knuth, Mathematical Writing
- Freeman, How to write a good research paper
- Hertzman, Writing Research Papers
- Parikh et al., How we write rebuttals
- Ernst, Giving a technical presentation
- Shewchuk, Giving an Academic Talk
- Van Loan, The Short Talk