AI: Graduate Seminar

University of Illinois

4-Credit Students Only: Research Seminar

Students taking the course for 4cr are required to attend a weekly research seminar. This will probably be Mondays 1-2pm, beginning in the second week of the course. Seminar grades are based on:

  1. Presentations. Every student will give a three-slide presentation, every week. Presentations should follow distributed templates, but will cover research papers of your own choosing. If you miss attendance at one seminar during the semester, it won't count against you; if you need to miss two or more, please contact the professor to discuss.
  2. Slides. Each of you will submit your slides (PDF) on Gradescope. It's strongly recommended that you use Beamer.
    • Note: Slides will be shared on a google drive with all members of the grad section, unless your title slide includes the words ``not for coursework.''
  3. Session Summaries. Every week, each of you will enter, into Gradescope, a very short summary of your breakout session. This will include the names of the other students (you can copy this from their zoom window), and a two or three sentence summary of their presentation topic.

Detailed Schedule

Presentation topics for each week are listed below. You will be choosing, on your own, two papers from the research literature that you want to read. You will also be required to read the papers chosen by three other students in your small group. You will have the chance to present your own research during the third part of the course: you may present your thesis research, your project from another course, or you may present a third paper from the research literature.

Week Topic Required Slides
2/1 How to use LaTeX (a) quad chart
(week02_template.zip) (b) equations
(c) citations
2/8 Paper 1 Overview (a) Objective and relationship to AI
(week03_template.zip) (b) Most relevant previous solutions or partial solutions
(c) Technical approach
2/15 Paper 1 Algorithm Derivation (a) Block diagram/schematic of the algorithm
(week04_template.zip) (b) Algorithm equation, and definition of its variables
(c) Algorithm derivation: one key step
2/22 Paper 1 Experimental Test (a) Data used in testing: definition and stats
(week05_template.zip) (b) Test metric: equation, and definition of its variables
(c) Test results table or chart
3/1 Quad charts (d) Quad chart of the paper one of your fellow students presented
(week06_template.zip) (b) Quad chart of the paper another student presented
(c) Quad chart of the paper a third student presented
3/8 Paper 2 Overview (a) Objective and relationship to AI
(week07_template.zip) (b) Most relevant previous solutions or partial solutions
(c) Technical approach
3/15 Paper 2 Algorithm Derivation (a) Block diagram/schematic of the algorithm
(week08_template.zip) (b) Algorithm equation, and definition of its variables
(c) Algorithm derivation: one key step
3/22 Paper 2 Experimental Test (a) Data used in testing: definition and stats
(week09_template.zip) (b) Test metric: equation, and definition of its variables
(c) Test results table or chart
3/29 Quad charts (a) Quad chart of the paper one of your fellow students presented
(week10_template.zip) (b) Quad chart of the paper another student presented
(c) Quad chart of the paper a third student presented
4/5 Paper 3 Overview (a) Objective and relationship to AI
(week11_template.zip) (b) Most relevant previous solutions or partial solutions
(c) Technical approach
4/12 Paper 3 Derivation (a) Block diagram/schematic of the algorithm
(week12_template.zip) (b) Algorithm equation, and definition of its variables
(c) Algorithm derivation: one key step
4/19 Paper 3 Experimental Test (a) Data used in testing: definition and stats
(week13_template.zip) (b) Test metric: equation, and definition of its variables
(c) Test results table or chart
4/26 Quad charts (a) Quad chart of the papers three of your fellow students presented
(week14_template.zip) (b) Quad chart of the paper another student presented
(c) Quad chart of the paper a third student presented
5/3 No seminar

Major conferences

Here is a list of major conferences and journals that you can browse to find interesting papers.

Core AI
AAAI, IJCAI
IEEE Transactions on Artificial Intelligence
Computer vision
CVPR, ICCV, ECCV
IEEE Transactions on Computer Vision
International Journal of Computer Vision
Natural language
ACL, NAACL, EACL, EMNLP, COLING (All available at the ACL anthology web site.)
Computational Linguistics
Speech
ICASSP, Interspeech
IEEE Transactions on Audio, Speech and Language
ACM Transactions on Asian and Under-Resourced Languages
Speech Communication
Computer Speech and Language
Machine Learning
NeurIPS, ICML, ICLR
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks and Learning Systems
Pattern Recognition
Robotics
ICRA, IROS
IEEE Transactions on Robotics
Robotics