Radu Jianu (email@example.com), project supervision
About me: I am a lecturer in the giCentre at City.
My research interests are in Data Visualization, Visual Analytics, and Human Computer
Interaction. In particular, I look to understand how people interpret and 'read'
data visualizations and figure out what makes visual content 'good'. To this end
I often run user studies and leverage eye-trackers to record where people look while
using visual interfaces. I'm also interested in using eye-trackers more broadly,
for instance to understand how people learn from visual content or how they use
particular applications. Finally, I enjoy mining interesting data using visual methods
and creating public facing websites that show data in engaging ways.
I'm happy to supervise projects having to do with the topics above. Projects can involve programming,
but students can conduct user experimentation, run eye-tracking studies, or collect and analyze data.
A few project ideas, some more specific than other, are listed below. However, if you have some other project idea
that you feel aligns with my interests, contact me!
Crowdsourced/collaborative eye tracking annotation
Description: Eye-tracking can tell us where on a computer screen a person is looking
when viewing a video. Any eye-tracking analysis will involve mapping 2D gaze
coordinates (where on the screen a viewer is looking) to what was shown in the video
(the objects, people, etc.).
To be able to do this efficiently we need to know the positions and shapes of
things shown in the video at each moment in time. Going through the video and
drawing shapes around objects one frame at a time is very laborious. It would be
great if we could 'crowdsource' this effort - have many people do a little bit of
work and combine their results. This project involves building an online video
annotation tool and would require coding.
Analyzing and/or visualizing fraudulent reviewing behavior in the google app store
Category: Research, data analysis; coding is a plus but may not be required
Description: When choosing to buy and install an app from the Google App Store, users rely on reviews and scores.
However, a significant proportion of reviews are fake, aimed at raising or lowering an apps standing. This project is
about mining available review data to come up with metrics and visualizations that can help researchers and users
separate fake reviews from genuine reviews.
Eye-tracking analysis of learning from visual content
Category: Research, minimal coding necessary
Description: Eye-tracking can tell us where on a computer screen a person is looking.
In the context of learning supported by digital learning environments, it can tell us what type of
learning content students focus most on (e.g., definitions? examples? text? imagery? hints? etc.)
Correlating such data with learning effectiveness (for example performance in tests) may help us
understand how people learn and what type of digital content is most effective. This project is fairly
open-ended (what type of learning you wish to explore, the kind of experiment you wish to design, etc.) but
would involve collecting eye-tracking data from people using visual learning materials and interpreting
A public facing visualizaton of IMDB (movie) data (or other data)
Description: IMDB data can be downloaded and visualized to reveal interesting connections
between actors, movies, directors, genres, etc. This project is about creating a public facing, online
such visualization. The same project can apply to other kinds of data (e.g., Google App store data, or any data the student
might be interested in).
User studies of data visualization
Category: Designing and conducting a user study
Description: Often there are multiple ways in which the same data can be shown visually and
we need to choose the most effective representation. User studies help us do that. They involve asking
many people (potentially online) to look at and use the alternative representations and answer questions
about the data they display. Representations are good if people can make sense of the data they show
quickly and accurately. This project is about conducting such a user study for a particular class
of data visualizations.
A data analysis of music playlists
Category: Research project, data analysis; coding is not required
Description: The music that DJs play is influenced by the DJ's audience, the time
(within the event, within a day, or season), by cultural and regional preferences, and trends.
Given a large set of DJ playlists you are to conduct a data analysis to expose trends, patterns, and correlations.
This would be a research-type project, and may require limited coding.
An online environment for shareable and extensible user studies
Category: Research and interface design; coding optional
Descripton: Data visualizations (interactive ones too) are evaluated via user studies.
Increasingly these evaluations are done online: web-users are asked to use a web-visualization to solve some tasks
and their performance (e.g., time required, accuracy) is recorded in a database and then analyzed. It would be great
if experimenters (scientists, UX designers) could create user studies in standardized format, store them in an online repository,
and share them with others interested in extending them (e.g., add extra tasks, try other visualizations).
Think of it as a github for user studies. This project would involve designing (optionally, partly implementing)
such an online environment.
How do people learn how to program (or choose your own domain): a system 1 vs. system 2,
and situated cognition perspective
Description: When teaching programming, lectures most often emphasize problem solving and higher level cognition
(system 2 cognition). They describe abstract high level concepts first, then expect students to instantiate them in
concrete problems. However, what if we consider programming to be a skill - such as tennis or dancing? In this case,
learning by doing or from example might be more effective. Is programming a system 1 or system 2 activity? Are there
learning tools that support this type of learning and how would we design one that would? This project aims to explore
such topics but is fairly open ended.