Graph Theory and its Applications LAB

(In Persian) آزمایشگاه نظریه گراف و کاربردهای آن

GTA-Lab-logo.png

Faculty of Mathematical Sciences

Ferdowsi Univ. of Mashhad

Mashhad, IRAN

About

The Graph Theory and its Applications Laboratory at the Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, is dedicated to conducting research in graph theory, graph algorithms, and their applications. By leveraging innovative approaches and advanced analytical methods, our laboratory addresses various challenges in diverse graph domains, including graph structure learning, graph neural networks, and temporal graphs.

Our laboratory fosters interdisciplinary collaborations with experts from various fields to develop innovative graph applications in different domains, expand knowledge, and specialize in graph theory and graph algorithms within the faculty.

The laboratory’s areas of activity include designing and analyzing graph algorithms, graph neural networks, modeling and analyzing complex networks, graph structure learning, graph compression, large-scale graph processing, and graph applications in various sciences, including biological and medical sciences.

news

Nov 20, 2024 GNN workshop at Faculty of Mathematical Sciences, FUM
Oct 09, 2024 13th Graph Theory and Algebraic Combinatorics Conference will be held in Shahid Rajaee Teacher Training University, Tehran, Iran on 28-29 May 2025.
Oct 01, 2024 Dr. Ghafarian is added to our GTA-Lab.
Sep 10, 2024 GNN workshop at Faculty of Mathematical Sciences, FUM
Aug 08, 2024 Distill's GNN Guides Now Available on GTA-lab

latest posts

selected publications

  1. Amintoosi2023GFS-COAM.jpg
    Graph Feature Selection for Anti-Cancer Plant Recommendation
    Mahmood Amintoosi, and Eisa Kohan-Baghkheirati
    Control and Optimization in Applied Mathematics, 2023
  2. GCN-JAC2021.jpg
    Overlapping Clusters in Cluster Graph Convolutional Networks
    Mahmood Amintoosi
    Journal of Algorithms and Computation, 2021
  3. localization.png
    Localization of mobile targets in a wireless sensor network using Diffusion Least Mean Square algorithm based on Huber loss function (in Persian)
    Soheila Ashkezari-Toussi, Mohammad-Naeem Teimoori, and Vahid-Reza Sabzevari
    Soft Computing Journal, 2023