If you are interested in doing a semester project in data visualisation in the domain of education, you can apply for one of the projects bellow. Your primary supervisors will be Francisco Pinto and Patrick Jermann, from the Center for Digital Education (CEDE).
List of Projects
This is only a selected list of the types of projects we supervise. If you have your own ideas about new apps that address the daily needs of students, and that you would like to deploy of top of GraphSearch, do not hesitate to share.
- 3D/VR knowledge graph navigation app [Bachelor or Master level]
- Knowledge map of all concepts taught at EPFL [Bachelor or Master level]
- Course similarity app [Bachelor or Master level]
- Video-lectures mind map generation app [Bachelor or Master level]
- Research collaborations network app [Master level]
Level: Bachelor or Master.
Subject area(s): Graph theory, data visualisation.
Description:
Navigating a large knowledge graph visually is a challenging task, because of the large amount of nodes and edges and the “hairball” nature of the graph. One approach to improve the visualisation is to add a third dimension to the graph, and allow the user to “fly and look around” and navigate it as if it were a video game.
This project builds on a previous one that included information only about EPFL courses and concepts. The goal is to build a navigation app that allows users to search the entire academic graph that is used to power EPFL’s GraphSearch engine, and add additional functionalities like filters, jump-to, colour code, and potentially a VR/stereo mode.
Graph Apps are a new functionality of the GraphSearch platform, that allows students to build their own custom-made apps on top of it, as well as to credit their name on the app, and make it useful to the rest of the students community.
Note that building and deploying the app on GraphSearch is a required outcome of this project.
Pre-requisites: JavaScript programming, basic understanding of graph theory.
Useful tools: React.js, Three.js.
Contact: [email protected]
Please attach the grade transcripts from both your Bachelor and Master studies.
Knowledge map of all concepts taught at EPFL
Level: Bachelor or Master.
Subject area(s): Graph theory, data visualisation.
Description:
The online teaching efforts of EPFL during the covid pandemic resulted in the recording of 40’000 video lectures by our professors, representing 60k+ hours of teaching material. We took advantage of the opportunity to map out and index the semantic content of these lectures, in order to allow students to quickly find the timestamps in videos where specific concepts were taught. See demo here [requires Gaspar login].
This projects aims at leveraging this massive semantic dataset we’ve built for EPFL’s GraphSearch engine, to map out the entire knowledge map of EPFL courses. The goal is to have an interactive app that allows students to visualise, navigate, search, and filter out the different “knowledge paths” they can follow throughout their studies at EPFL. It should also have functionalities to analyse the knowledge map from a graph theoretical perspective, to allow professors and section deputies to better understand what is taught at EPFL as a whole.
Graph Apps are a new functionality of the GraphSearch platform, that allows students to build their own custom-made apps on top of it, as well as to credit their name on the app, and make it useful to the rest of the students community.
Note that building and deploying the app on GraphSearch is a required outcome of this project.
Pre-requisites: JavaScript programming, basic understanding of graph theory.
Useful tools: React.js, Cytoscape.js.
Contact: [email protected]
Please attach the grade transcripts from both your Bachelor and Master studies.
Course similarity app
Level: Bachelor or Master.
Subject area(s): Graph theory, data visualisation.
Description:
The online teaching efforts of EPFL during the covid pandemic resulted in the recording of 40’000 video lectures by our professors, representing 60k+ hours of teaching material. We took advantage of the opportunity to map out and index the semantic content of these lectures, in order to allow students to quickly find the timestamps in videos where specific concepts were taught. See demo here [requires Gaspar login].
This projects aims at leveraging this massive semantic dataset we’ve built for EPFL’s GraphSearch engine, to visualise how courses overlap with each other and how clusters of courses relate to each other. This type of app would help EPFL’s academic service and professors better organise the course curriculum, so that it optimally meets the objectives of each study plan.
Graph Apps are a new functionality of the GraphSearch platform, that allows students to build their own custom-made apps on top of it, as well as to credit their name on the app, and make it useful to the rest of the students community.
Note that building and deploying the app on GraphSearch is a required outcome of this project.
Pre-requisites: JavaScript programming, basic understanding of graph theory.
Useful tools: React.js, Cytoscape.js.
Contact: [email protected]
Please attach the grade transcripts from both your Bachelor and Master studies.
Video-lectures mind map generation app
Level: Bachelor or Master.
Subject area(s): Data visualisation.
Description:
The online teaching efforts of EPFL during the covid pandemic resulted in the recording of 40’000 video lectures by our professors, representing 60k+ hours of teaching material. We took advantage of the opportunity to map out and index the semantic content of these lectures, in order to allow students to quickly find the timestamps in videos where specific concepts were taught. See demo here [requires Gaspar login].
This projects aims at leveraging this massive semantic dataset we’ve built for EPFL’s GraphSearch engine, to facilitate the revision of video lectures through the use of mind maps and other revision techniques like flash cards. This app will be of great value to students during the exams period.
Graph Apps are a new functionality of the GraphSearch platform, that allows students to build their own custom-made apps on top of it, as well as to credit their name on the app, and make it useful to the rest of the students community.
Note that building and deploying the app on GraphSearch is a required outcome of this project.
Pre-requisites: JavaScript programming, basic SQL.
Useful tools: React.js, Joint.js.
Contact: [email protected]
Please attach the grade transcripts from both your Bachelor and Master studies.
Research collaborations network app
Level: Master.
Subject area(s): Machine learning, graph theory, data visualisation.
Description:
The EPFL knowledge graph (graphsearch.epfl.ch) contains a historical network of publication co-authorships dating back 15+ years. This co-authorship graph can be used to visualise, locate, and predict future collaborations within EPFL.
The goal of this project is to provide doctoral students and postdocs with the means to explore potential avenues for research collaborations. The resulting app should allow, for example, users to search and locate on the EPFL map different areas of research they might be interested in.
Graph Apps are a new functionality of the GraphSearch platform, that allows students to build their own custom-made apps on top of it, as well as to credit their name on the app, and make it useful to the rest of the students community.
Note that building and deploying the app on GraphSearch is a required outcome of this project.
Pre-requisites: JavaScript programming, experience with machine learning algorithms, mathematical knowledge of graph theory.
Useful tools: Node.js, React.js, Cytoscape.js, Pyodide, Danfo.js.
Contact: [email protected]
Please attach the grade transcripts from both your Bachelor and Master studies.