This is a simple page to provide basic information about the 2014 Doctoral Consortium at AAAI 2014.
This program is preliminary and is likely to be updated several times before the DC. Please check back to ensure you have the latest version. (Current version uploaded: Sunday July 27, 2014)
The names shown are in order of Student Participant / Mentor.
Location: Room 206b (on the Second Level of the Quebec Convention Center)
SUNDAY 27 JULY 2014
0900 - 0940: Introduction
0940 - 1020: Tim Brys: Reinforcement Learning on Multiple Correlated Signals / Sonia Chernova
1050 - 1130: Anup Kalia: The Semantic Interpretation of Trust in Multiagent Interactions / Eric Eaton
1130 - 1210: Thomas Allen: Making CP-nets (More) Useful / Sven Koenig
1340 - 1420: Ran Taig: Compilation Based Approaches to Probabilistic Planning - DC application / Daniele Magazzeni
1420 - 1500: Elizabeth Jensen: Robot Team Exploration with Communication Restrictions / Ayanna Howard
1520 - 1600: Khang Lam: Automatically creating bilingual lexical resources / Cynthia Matuszek
1600 - 1640: Adrian Boteanu: Solving Semantic Problems Using Contexts Extracted from Knowledge Graphs / Hana Chockler
1645 - 1800: Panel Discussion: Launching and Managing Your Career
Panelists: Eric Eaton, Hana Chockler, Sven Koenig
1830: DC Dinner: SaviniLocation:
680 Rue Grande Allée Est
Quebec City, QC G1R 2K5
Map (~5 minute walk from conferenece venue)
Reservation made under "Dr. Matthew Taylor"
MONDAY 28 JULY 2014
0900 - 0940: Lawson Wong: Living and Searching in the World: Object-based State Estimation for Mobile Robots / Maria Gini
0940 - 1020: Ofra Amir: Information Sharing for Care Coordination / Milind Tambe
1050 - 1130: Maria Chang: Analogy Tutor: a Tutoring System for Promoting Conceptual Learning via Comparison / Yolanda Gill
1130 - 1210: Xiaojian Wu: Optimizing and Learning Diffusion Behaviors in Complex Network / Pradeep Varakanthan
1340 - 1420: Taraneh Khazaei : Modeling Argumentation and Explanation in the Social Web / Matt Taylor
1420 - 1500: Pineda Luis: Probabilistic Planning with Reduced Models / Toby Walsh
1520 - 1600: Matthew Spradling: Roles and Teams Hedonic Games / Noa Agmon
1600 - 1640: John Doucette: Imputation, Social Choice, and Partial Preferences / Bo An
1640 - 1720: Jason M Bindewald: The Effect of Similarity Between Human and Machine Action Choices on Adaptive Automation Performance / Todd Neller
1730: Close of 2014 DC
- Each participating student will be assigned a time to give a talk (see the preliminary schedule above). Your talk should be about 25 minutes long. Afterwards, there will be 15 minutes allocated for questions and discussion. The room will be equipped with a data projector, so plan to bring slides (PDF format recommended) on a USB flash drive or a laptop.
- Note that 25 minutes is not a long time. If you have not given many talks before, then we recommend that you practice your talk before coming to the conference.
- Please keep your audience in mind: while we all have a background in AI, there are participants from a wide variety of subareas, so setting the context is critical. Be sure to cover background and motivation before getting into the technical details of your approach. Make sure that the high-level issues in your research are understandable to the audience in general. Having a running example is often a good idea.
- Here is a list of the kinds of questions/comments that past students have received after their talks, which you might want to try and address in your presentation:
- What is your primary contribution?
- How do you know when you'll be done with your thesis? What are the "exit criteria?"
- How do all of the pieces of your thesis fit together?
- Do you have a simple example showing how it works?
- Have you looked at work in subfield X that addresses similar problems?
- Wasn't this already done by person Y?
- How do you expect to address problem Z in your future work?
- How will you evaluate the approach?
- Is your evaluation plan sufficient? Why not look at other/more problem domains?
- Do you expect similar results for other problem domains?
- Is there a real world problem that could benefit from using your work?
- Here is a possible outline for a presentation:
- Problem statement (what problem are you addressing?)
- Motivation (why should we care about this?)
- Your contribution and approach
- Related work (Have others addressed the problem, or how is your problem related to those addressed by others? How is your approach different, and why do you think it might be better?)
- Results so far
- Future work (what else do you expect to do in order to complete your thesis?)
- Summary, Conclusion
- Acknowledgments (list your advisor, any funding sources, and any peers you work with on your project)
- Backup material (see below: material/details that you didn't have time to include but could be useful to help answer questions)
- Below are some more general recommendations for preparing talks:
- If giving talks is a completely new experience for you, then write down an entire script for the talk, broken into sections for each slide. You won't read this script at the talk, but the exercise will help you figure out what you want to say on each slide. If you read the script through using a slow and clear voice, then you can time your delivery and see how well you fall within the prescribed length. People usually get nervous during talks, especially if they are new at it, and that usually means that they talk faster. So keep that in mind when completing this exercise.
- If you are not brand new at giving talks, then create a short outline and write down 1-2 phrases for each slide indicating the main thing(s) you want to convey on each slide. This outline should fit on one page, so you could print it out and have it with you when you present, as a quick reference. It's also helpful to have in case you are nervous and/or distracted during your presentation, because it serves as a quick reminder of what you wanted to say on each slide.
- Read about How to Give a Bad Talk, e.g., Here, here, or here!
- Proofread your slides for typos!!!
- Put page numbers on your slides. This will be especially helpful for the mentor who is leading the discussion, because they can easily refer back to particular slides.
- A good rule of thumb is to have one slide per 2-3 minutes allocated for a talk, e.g., about 8-12 slides in this case. This includes a title page at the beginning and an acknowledgments page at the end.
- It is good to have backup slides that may help you quickly answer questions and allow more time to get feedback. For example, if you have detailed mathematical formulae or software architecture drawings, put these *after* your acknowledgments slide and have them ready to support your answers to questions at a detailed level. Often, having too much technical detail in a presentation can detract from the main point you are trying to get across, so it is better not to include them in the main flow of your talk.
- Beware of cascading bullets in MS Powerpoint (i.e., which require you to hit "next" multiple times on the same slide). This is a matter of stylistic preference, but be aware of the drawbacks (below) if you decide to use this "feature" of your presentation software package. First, as a presenter, you will be distracted from what you are saying by the continual need to interact with the laptop (even via remote control) in order to activate the next cascading bullet. Second, as audience members, we will have to keep returning our attention to the projected slides, away from you and away from what you are saying, in order to read the new bullet. Third, as a presenter, if you need to speed up or go back to a slide during the question/discussion period, it is much easier to do this without the cascading bullets.
- Finally, DON'T STRESS! You are not supposed to have all the answers. If we thought you did, then your application probably would have been rejected. Sometimes "I don't know" is the right answer!
The AAAI-14 Poster Session will include Doctoral Consortium posters, EAAI posters, Poker Competition posters, Student Abstracts, and a light reception on Tuesday, July 29 from 5:30 - 7:00 PM. Also, the "games night" activities will follow the reception, starting at 7pm in Room 206.
Here are the guidelines for the session:
- AAAI will provide fabric-covered boards and mounting supplies (push pins). The dimensions of the poster boards are 4 feet x 6 feet and will be set in landscape orientation. You are responsible for mounting your material on the board for presentation. This task should be completed NO LATER THAN 5:30 PM.
- A good poster allows someone to grasp quickly what your research is all about, and allows you to explain your ideas to them in more detail in case they are interested.
- A representative from the author team should remain by the poster board during the entire session to answer questions and clarify statements. The session should be used as an opportunity to probe deeper into your work, and give attendees an opportunity to ask questions, so your presence is essential. If you would like to keep your poster material, please be sure to retrieve it promptly at 7:30 PM on Tuesday evening. Otherwise, it will be discarded.
- Please do not hesitate to contact us if you have any questions about your poster presentation.
Here are some suggestions from DC students in previous years:
- "Start early and practice your presentation multiple times with a group of critical peers and faculty. My presentation was far better thanks to multiple iterations that incorporated feedback from (helpfully) critical lab mates."
- "Focus more on motivation and broad impact of your work. Provide a clear contribution of your work and discuss how it will push the state of the art in AI."
- "Be proactive in interacting with people you don't already know."
- "Embrace the challenge of marketing your work to an unspecialized audience - discuss intuitions, not equations!"
- "Keep the slides simple, talk more about background and intuitions."
We are most grateful to assistance from the Program Committee for reviewing submissions.
- Stephanie August, Loyola Marymount University
- Philip Chan, Florida Institute of Technology
- Adam Cannon, Columbia University, USA
- Sonia Chernova, Worcester Polytechnic Institute, USA
- Brad Clement, NASA Jet Propulsion Laboratory, USA
- Mark Core, USC Institute for Creative Technologies, USA
- Jeremy Frank, NASA, USA
- Maria Gini, University of Minnesota, USA
- Amy Greenwald, Brown University, USA
- Benjamin Hirsch, EBTIC, Abu Dhabi UAE
- Gal Kaminka, Bar Ilan University, Israel
- Sven Koenig, University of Southern California, USA
- Peter McBurney, King's College London, UK
- Timothy Miller, University of Melbourne, Australia
- Katarzyna Musial-Gabrys, King's College London, UK
- Andrea Omicini, University of Bologna, Italy
- David Roberts, North Carolina State University, USA
- William Smart, Oregon State University, USA
- Brian Smith, Drexel University, USA
- Robert St. Amant, North Carolina State University, USA
- Sebastian Stein, University of Southampton, UK
- Botond Virginas, British Telecom, UK
- Toby Walsh, NICTA, University of New South Wales, Australia