Paper Presentations

After each lecture three to four students will actively participate in teaching the course about additional material relevant to the class topic. The purpose of the exercise is to offer a venue to practice giving scientific presentations in English and to answer questions about paper contents. Each student will be assigned one paper (see list below) and has to prepare a presentation on the paper topic. This presentation has to include the material of the paper and can additionally include other material that the student finds relevant.

Each paper presentation will be a maximum of 12 minutes long (time-limit will be enforced) plus 3 minutes of questions from other students.

Paper Assignment

The papers will be assigned to students based on their reported preferences. On 25/11/2015 after the first lecture, we will briefly explain the process. Then students will have to pair for their paper presentation and complete the following google doc (here). Put a 1 for your favorite paper, 2 for the second favorite... and give at least 3 papers that you would like to present. A couple of days later, students will be informed which paper they have been assigned and when they will present it. Emails should be sent on the evening of the first class.

Student-paper assignments will be done using the Hungarian method. A student getting her first choice will be assigned a cost of -5, the second choice is -4, etc. Getting an unlisted paper yields the highest cost of 0. This situation cannot be avoided altogether but the risk of it happening lowers with the number of papers listed (up to 5).

Students who send their preferences too late (e.g., absent) will have to choose among the remaining papers.

Presentation instructions

  • Start with a short introduction of the goal and contribution (1-2 slides)
  • Then, show the system, either a video, a demo or slides (in order of preference). Keep it under time control.
  • Then, give more "important" details. One per slide with illustration.
  • Finish in the conclusion with a take-away message and a personal statement.

It's highly recommended you practice your talk at least once (either alone or with a friend) to make sure you will not go over 12 minutes.


02/12/2015 Perception and Color (T. Isenberg)

  1. Arnaud | German: The Effect of Colour and Transparency on the Perception of Overlaid Grids
  2. Deng | Hirvonen: Choosing Effective Colours for Data Visualization
  3. Guo | Xie: Selecting Semantically-Resonant Colors for Data Visualization (EuroVis '13 best paper award winner)
  4. Lasne | Zheng: How Capacity Limits of Attention Influence Information Visualization Effectiveness (InfoVis '12 best paper award winner)
  5. Unassigned: An Empirical Model of Slope Ratio Comparisons
  6. Unassigned: Color Naming Models for Color Selection, Image Editing and Palette Design

09/12/2015 Multidimensional Data (Boukhelifa)

  1. Chai | Ursashi: LineUp: Visual Analysis of Multi-Attribute Rankings (InfoVis '13 best paper award winner)
  2. Lipcanu: Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases
  3. Devaikin | Coimbatore: Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation (InfoVis '08 best paper award winner)
  4. Unassigned: VisDB: a system for visualizing large databases
  5. Unassigned: Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization

16/12/2015 Interactive Visualization (Dragicevic)

  1. Xia | Karlen: Toolglass and magic lenses: the see-through interface
  2. Giang | Vitale: Evaluating the Efficiency of Physical Visualizations
  3. Yang | Lu: Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions
  4. Unassigned: Dust & Magnet: Multivariate Information Visualization using a Magnet Metaphor

06/01/2016 Time and animation (Dragicevic)

  1. TranĀ | Fallaha: Interactive Horizon Graphs: Improving the Compact Visualization of Multiple Time Series
  2. Binisti | Sifre: Exploring Video Streams Using Slit-Tear Visualizations
  3. Gbakatchetche | Hanif: Effectiveness of Animation in Trend Visualization
  4. Xu | Du: RankExplorer: Visualization of Ranking Changes in Large Time Series Data

13/01/2016 Graphs (Fekete)

  1. Unassigned: A Comparison of the Readability of Graphs Using Node-Link and Matrix-Based Representations
  2. Unassigned: Topology-Aware Navigation in Large Networks
  3. Perez | Mullafetah: Exploring the Design Space of Interactive Link Curvature in Network Diagrams
  4. Alali | Cabridens: Visualizing Network Data
  5. Phan Thai | Rukubayihunga: Search, Show Context, Expand on Demand: Supporting Large Graph Exploration with Degree-of-Interest


You can reuse this content for your class if you acknowledge us (Petra Isenberg, Jean-Daniel Fekete, Pierre Dragicevic and Wesley Willett). For student slides, please acknowledge the student.