Hi. I'm Goran Murić

I am a Postdoctoral Research Associate at the University of Southern California‘s Information Sciences Institute. I got a PhD in Engineering at TU Dresden at the Faculty of Electrical and Computer Engineering. I like analyzing data. I like networks: communication networks, complex networks, social networks... name it. I like simulating things. I like programming (MATLAB, Python, R, PhP, SQL...) and I enjoy learning new programming languages.

My research is oriented toward the resilience of communication networks against failures. I deal with modeling epidemics within the networks. I have an experience working with the game theory modeling, data analysis and clustering algorithms. I am also interested in social networks and particularly in optimizing team's performance.

I was a scholarship holder of a Leibniz Institute of Urban and Regional development within the DLGS programme.

Some of the stuff I do.

Spreading phenomena

I deal with the modeling of spreading failures within the networks and mitigating the risk. Details

Social networks

Team optimization. Based on the friendship network, teams could be optimized to perform better. Details

Cascading failures

I model cascading failures within the network. I optimize the network so it becomes more robust. Details

Some videos I've made recently

Network resilience

I focus on network resilience against spreading failures. Spreading failures can propagate through the network and cause substantial damage or even the network breakdown. I model various spreading processes and try to identify the most influential spreaders within the network. Besides, I research cascading failures which are the phenomena prevailing in the networks loaded with traffic. Also, I try to implement the methods from the systems theory in the network analysis. You can find my paper on this topic here.

I use my findings to develop strategies to protect the network against the spreading failures. However, in some cases we want to do the opposite. For example, if we want to spread the news to the large audience of customers, we want to "infect" the social network on right places to do it most efficiently.

Teams optimization

The team will perform better if people in the team like each other. That is the main premise behind this project. We use the underlying network of social interactions within the large group to divide the group in optimal teams. Our algorithm solves this extremely complex optimization problem very efficiantly and timely. The researh part of the project is ongoing.

The solution could be used in education or in the companies where the team work is necessary.

Cascading failures

How much capacity is too much? Many networks are characterized by the capacity of its elements (nodes and links). A single failure could cause the traffic rerouting and further congestion and therefore more failures. Failures come in a form of a cascade.

Any system which can be modeled using an interdependence graph with limited capacity of either nodes or edges will be prone to cascading failure phenomena. I try to answer a big question: How to make networks more resilient against cascading failures?

You can ask me anything. Or just say Hi!

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