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:

Poster: Performance Testing Driven by Reinforcement Learning (Oct 2020)
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg , Markus Bohlin, Björn Lisper
IEEE 13th International Conference on Software Testing, Validation and Verification (ICST2020)

Machine Learning-Assisted Performance Assurance (Jun 2020)
Mahshid Helali Moghadam

From Requirements to Verifiable ExecutableModels using Rebeca (Nov 2019)
Marjan Sirjani, Luciana Provenzano, Sara Abbaspour Asadollah, Mahshid Helali Moghadam
International Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE 2019)

Machine Learning-Assisted Performance Testing (Aug 2019)
Mahshid Helali Moghadam
ESEC/FSE ACM Student Research Competition (ESEC/FSE SRC'19)

Machine Learning to Guide Performance Testing: An Autonomous Test Framework (Apr 2019)
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'19)

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)