Machine Learning for Graphs

Apply

Project Description

We have numerous projects where we work networks or graphs of various kinds, biological ones in particular. Networks can be undirected, directed with or without signs, discrete or continuous.

For publications see google scholar (https://scholar.google.com/citations hl=sv&user=_DUppAgAAAAJ&view_op=list_works&sortby=pubdate).

Challenges and sub-projects include:-         

How to compare 2 and several networks,review,benchmark current methods, invent new efficient algorithms for network comparison

-Analyze networks embedded in hyperbolicspace

-Review, benchmark current methods for embedding networks into anML framework

-Generative modeling of networks constrained by correlational information from data-sets

-Partially overlapping networks,analyzetheirputativealignment,constructionof multi-layer networks from several partially overlappinggraphs.

-Search and propagation in multi-layernetworks

-Alignment of several but different real protein interaction networks​

Program - Computer Science
Division - Computer, Electrical and Mathematical Sciences and Engineering
Field of Study - ​Computer Science, Applied Mathematics

About the
Researcher

Jesper Tegner

Jesper Tegner
jesper.tegner@kaust.edu.sa

Desired Project Deliverables

​Individual projects will be tailored and narrowly designed from the above palette according to interest of the student, technical proficiency, and level of study. We expect you (a) to bring enthusiasm, creativity, and hard work, (b) give lab seminars on your work, and (c) produce a final written report.In returnthis facilitates your critical thinking, presentations skills, and scientific writing.Yourresearch, in collaboration and with support of team members, may lead to scientific publications. You will also get a good hands-on perspective at the frontier of machine intelligence and its applications in an interdisciplinary research group andenvironment.​