Publications by Ehsan Kazemi | EPFL Graph Search

MPGM: Scalable and Accurate Multiple Network Alignment

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

IEEE COMPUTER SOC2020

PROPER: global protein interaction network alignment through percolation matching

Matthias Grossglauser, Seyed Hamed Hassani, Ehsan Kazemi, Hasan Pezeshgi Modarres

Background The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological know ...

2016

Network Alignment: Theory, Algorithms, and Applications

Ehsan Kazemi

Networks are central in the modeling and analysis of many large-scale human and technical systems, and they have applications in diverse fields such as computer science, biology, social sciences, and economics. Recently, network mining has been an active a ...

EPFL2016

Growing a Graph Matching from a Handful of Seeds

Matthias Grossglauser, Seyed Hamed Hassani, Ehsan Kazemi

In many graph–mining problems, two networks from different domains have to be matched. In the absence of reliable node attributes, graph matching has to rely on only the link structures of the two networks, which amounts to a generalization of the classic ...

Assoc Computing Machinery2015

When Can Two Unlabeled Networks Be Aligned Under Partial Overlap?

Matthias Grossglauser, Ehsan Kazemi, Lyudmila Yartseva

Network alignment refers to the problem of matching the vertex sets of two unlabeled graphs, which can be viewed as a generalization of the classic graph isomorphism problem. Network alignment has applications in several fields, including social network an ...

2015

Hiding in the Mobile Crowd: Location Privacy through Collaboration

Jean-Pierre Hubaux, Panagiotis Papadimitratos, Reza Shokri, Ehsan Kazemi, Georgios Theodorakopoulos

Location-aware smartphones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to track users. We address this probl ...

Ieee Computer Soc2014

Where to go from here? Mobility prediction from instantaneous information

Patrick Thiran, Matthias Grossglauser, Ehsan Kazemi, Mohamed Kafsi, Vincent Etter

We present the work that allowed us to win the Next-Place Prediction task of the Nokia Mobile Data Challenge. Using data collected from the smartphones of 80 users, we explore the characteristics of their mobility traces. We then develop three families of ...

Elsevier Science Bv2013

Mitigating Epidemics through Mobile Micro-measures

Patrick Thiran, Matthias Grossglauser, Lucas Maystre, Ehsan Kazemi, Mohamed Kafsi, Lyudmila Yartseva

2013

Been There, Done That: What Your Mobility Traces Reveal about Your Behavior

Ehsan Kazemi, Vincent Etter, Mohamed Kafsi

Mobility is a central aspect of our life; the locations we visit reflect our tastes and lifestyle and shape our social relationships. The ability to foresee the places a user will visit is therefore beneficial to numerous applications, ranging from forecas ...

2012