CV


Mojtaba Hajiabadi

Mojtaba Hajiabadi

Assistant Professor

Faculty: Electrical and Computer Engineering

Department: Electronic

Degree: Ph.D

CV
Mojtaba Hajiabadi

Assistant Professor Mojtaba Hajiabadi

Faculty: Electrical and Computer Engineering - Department: Electronic Degree: Ph.D |

Dr. Mojtaba Hajiabadi, a graduate of Electrical Engineering with a focus on Telecommunication Systems, earned his Bachelor's degree in 2012 from the University of Birjand, his Master's degree in 2014, and his Ph.D. in 2018 from Ferdowsi University of Mashhad. He was an outstanding student, holding third rank in his Bachelor's, first in his Master's, and first in his Ph.D. In 2018, he completed a doctoral research opportunity at KU Leuven University in Belgium under the supervision of Professor Marc Moonen, a distinguished IEEE Fellow.

During his Ph.D., Dr. Hajiabadi received several awards from the National Elites Foundation, including research grants, teaching assistantships, and an international research opportunity grant. After completing his studies, he worked for five years in Iran's telecommunications industry, contributing to satellite communication transceivers in the aerospace sector and optical telecommunication systems at the Infrastructure Communications Company. Since 2022, he has been a full-time faculty member in the Communication Engineering Department, Faculty of Electrical and Computer Engineering, at the University of Birjand. His research interests include adaptive filters, machine learning, and AI in wireless communication systems.

If you are interested in collaborating on research in his field of expertise, you may contact him via the following email address:

Email: mhajiabadi@birjand.ac.ir

نمایش بیشتر

Transient analysis of multitask learning over adaptive networks with wireless links

AuthorsMojtaba Hajiabadi
JournalInternational Journal of Adaptive Control and Signal Processing
Page number1-18
Serial number38
Volume number1
IF1.708
Paper TypeFull Paper
Published At2023
Journal GradeISI
Journal TypeTypographic
Journal CountryIran, Islamic Republic Of
Journal IndexJCR،Scopus

Abstract

Distributed multitask learning over adaptive networks with non-ideal links is studied in this paper. The performance of an adaptive multitask network with wireless communication links suffering from flat fading and additive white Gaussian noise is derived through simulation and theoretical analysis. The effect of the wireless link on the learning performance of a multitask network is analyzed. It is shown that this destroying effect is reduced by using local equalizers at each agent along with the intelligent cooperation policy based on the correntropy criterion. Stability condition, steady-state and transient performances are studied theoretically. Finally, the theoretical results are validated by numerical simulations and computer experiments.

Paper URL