Mahshid Helali Moghadam, Industrial Doctoral Student


Mahshid Helali Moghadam received her B.Sc. degree in software engineering and her M.Sc. degree in computer engineering with focus on artificial intelligence from Iran University of Science and Technology (IUST), Tehran, Iran in 2008 and 2011 respectively. She has worked as a researcher at ICT department of Niroo Research Institute (NRI) in Tehran for six years. She has been also as a research visitor at Distributed Systems group of Umeå University for five months. Currently, she is an industrial PhD student at the School of Innovation, Design, and Engineering at Mälardalen University and working as a member of software testing research group at RISE SICS Västerås. Her research interests include software testing, machine learning and cloud computing.

Research Interests:

  • Performance Analysis
  • Real-time Embedded Systems
  • Machine Learning
  • Cloud Computing

 

Current Projects:

ITS ESS-H Industrial Graduate School in Reliable Embedded Sensor Systems

TESTOMAT Project - The Next Level of Test Automation

[Show all publications]

Latest publications:

Adaptive Runtime Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning (May 2018)
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg , Markus Bohlin, Björn Lisper
13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 18)

Learning-based Response Time Analysis in Real-Time Embedded Systems: A Simulation-based Approach (May 2018)
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg , Markus Bohlin, Björn Lisper
1st International Workshop on Software Qualities and their Dependencies, located at the International Conference of Software Engineering (ICSE) 2018 (SQUADE'18)

Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System (Apr 2018)
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg , Markus Bohlin, Björn Lisper
ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems (ITEQS'18)

Adaptive Service Performance Control using Cooperative Fuzzy Reinforcement Learning in Virtualized Environments (Dec 2017)
Olumuyiwa Ibidunmoye , Mahshid Helali Moghadam, Ewnetu Bayuh Lakew , Erik Elmroth
10th IEEE/ACM International Conference on Utility and Cloud Computing (UCC'17)

Makespan reduction for dynamic workloads in cluster-based data grids using reinforcement-learning based scheduling (Oct 2017)
Mahshid Helali Moghadam, Seyed Morteza Babamir
Journal of Computational Science (J COMPUT SCI)

A Multi-Objective Optimization Model for Data-Intensive Workflow Scheduling in Data Grids (Nov 2016)
Mahshid Helali Moghadam, Seyed Morteza Babamir , Meghdad Mirabi
IEEE International LCN Workshop on Cloud-based Networks and Applications (IEEE CloudNA'16)