Research scope

We are an active multidisciplinary group at the computer engineering department of University of Kurdistan at the beautiful city of Sanandaj at the west of Iran. Lab members are from different majors. Our focus is on network analysis research in various fields. Furthermore, we do practical analysis of social and biological networks for nationwide and international customers. Level of the network analysis can vary from micro level, living organism genes, to macro level, relation between people or groups or companies of peoples.

 

Active projects

Bipartite network analysis

Bipartite graphs are especial type of graphs that relations is only permitted between the nodes of different parts. In other word, here, the connections between parts are important, not connections within each part. Some examples include: gene-disease, student-course, country-product, drug-gene, etc. Modeling and general calculations on such network needs different equations and considerations. We are currently working on two different aspects of bipartite networks: theory and applications. For theory, we are concentrating on improving popular network analysis tasks such as bipartite link prediction, bipartite community detection, converting related time series to bipartite graphs for more analysis, ..., and for applications we have several researches running like better drug-target interaction modeling, educational processes improvement, global trade connection predictions for various fields, ....

Network based time series analysis

A large part of data gathered from biological, medical, economical, and etc. are in the form of time series. Examples include EEG signals, price time series, climate statistics, ... Besides, various computational tasks has been performed to do prediction or enhancement on such data that majority of them are based on traditional machine learning techniques. However, network and relational view to these time series data may open new horizons to analyze and mine. Therefore we are currently focused on visibility graph analysis topics, and progressively extend its application to new areas.