Integration of heterogeneous data sources in smart grid based on summary schema model. - Foroogh Sedighi; Mahshid Helali Moghadam (IIT, 2016)

A Multi-Objective Optimization Model for Data-Intensive Workflow Scheduling in Data Grids. - Mahshid Helali Moghadam; Seyed Morteza Babamir; Meghdad Mirabi (LCN Workshops, 2016)

Adaptive Service Performance Control using Cooperative Fuzzy Reinforcement Learning in Virtualized Environments. - Olumuyiwa Ibidunmoye; Mahshid Helali Moghadam; Ewnetu Bayuh Lakew; Erik Elmroth (UCC, 2017)

Adaptive runtime response time control in PLC-based real-time systems using reinforcement learning. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (SEAMS@ICSE, 2018)

Learning-based response time analysis in real-time embedded systems: a simulation-based approach. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (SQUADE@ICSE, 2018)

Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (ICST Workshops, 2018)

Makespan reduction for dynamic workloads in cluster-based data grids using reinforcement-learning based scheduling. - Mahshid Helali Moghadam; Seyed Morteza Babamir (J. Comput. Sci., 2018)

Machine Learning to Guide Performance Testing: An Autonomous Test Framework. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (ICST Workshops, 2019)

Machine learning-assisted performance testing. - Mahshid Helali Moghadam (ESEC/SIGSOFT FSE, 2019)

Poster: Performance Testing Driven by Reinforcement Learning. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (ICST, 2020)

From Requirements to Verifiable Executable Models Using Rebeca. - Marjan Sirjani; Luciana Provenzano; Sara Abbaspour Asadollah; Mahshid Helali Moghadam (SEFM, 2020)

Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL. - Hamid Ebadi; Mahshid Helali Moghadam; Markus Borg; Gregory Gay 002; Afonso Fontes; Kasper Socha (AITest, 2021)

Automated Performance Testing Based on Active Deep Learning. - Ali Sedaghatbaf; Mahshid Helali Moghadam; Mehrdad Saadatmand (AST@ICSE, 2021)

Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent. - Mahshid Helali Moghadam; Golrokh Hamidi; Markus Borg; Mehrdad Saadatmand; Markus Bohlin; Björn Lisper; Pasqualina Potena (CEC, 2021)

A population-based automatic clustering algorithm for image segmentation. - Seyed Jalaleddin Mousavirad; Gerald Schaefer; Mahshid Helali Moghadam; Mehrdad Saadatmand; Mahdi Pedram (GECCO Companion, 2021)

An LSTM-Based Plagiarism Detection via Attention Mechanism and a Population-Based Approach for Pre-training Parameters with Imbalanced Classes. - Seyed Vahid Moravvej; Seyed Jalaleddin Mousavirad; Mahshid Helali Moghadam; Mehrdad Saadatmand (ICONIP (3), 2021)

Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search. - Mahshid Helali Moghadam; Markus Borg; Seyed Jalaleddin Mousavirad (SBST@ICSE, 2021)

An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator. - Seyed Jalaleddin Mousavirad; Gerald Schaefer; Iakov Korovin; Mahshid Helali Moghadam; Mehrdad Saadatmand; Mahdi Pedram (SMC, 2021)

HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space. - Seyed Jalaleddin Mousavirad; Gerald Schaefer; Iakov Korovin; Diego Oliva; Mahshid Helali Moghadam; Mehrdad Saadatmand (SSCI, 2021)

Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL. - Hamid Ebabi; Mahshid Helali Moghadam; Markus Borg; Gregory Gay 002; Afonso Fontes; Kasper Socha (CoRR, 2021)

Towards a Verification-Driven Iterative Development of Software for Safety-Critical Cyber-Physical Systems. - Marjan Sirjani; Luciana Provenzano; Sara Abbaspour Asadollah; Mahshid Helali Moghadam; Mehrdad Saadatmand (J. Internet Serv. Appl., 2021)

RWS-L-SHADE: An Effective L-SHADE Algorithm Incorporation Roulette Wheel Selection Strategy for Numerical Optimisation. - Seyed Jalaleddin Mousavirad; Mahshid Helali Moghadam; Mehrdad Saadatmand; Ripon K. Chakrabortty; Gerald Schaefer; Diego Oliva (EvoApplications, 2022)

An autonomous performance testing framework using self-adaptive fuzzy reinforcement learning. - Mahshid Helali Moghadam; Mehrdad Saadatmand; Markus Borg; Markus Bohlin; Björn Lisper (Softw. Qual. J., 2022)

Intelligence-Driven Software Performance Assurance. - Mahshid Helali Moghadam (2022)

Anomaly Detection Dataset for Industrial Control Systems. - Alireza Dehlaghi-Ghadim; Mahshid Helali Moghadam; Ali Balador; Hans Hansson (IEEE Access, 2023)

Making Sense of Failure Logs in an Industrial DevOps Environment. - Muhammad Abbas 002; Ali Hamayouni; Mahshid Helali Moghadam; Mehrdad Saadatmand; Per Erik Strandberg (CoRR, 2023)

How effective are current population-based metaheuristic algorithms for variance-based multi-level image thresholding? - Seyed Jalaleddin Mousavirad; Gerald Schaefer; Huiyu Zhou 001; Mahshid Helali Moghadam (Knowl. Based Syst., 2023)

ICSSIM - A framework for building industrial control systems security testbeds. - Alireza Dehlaghi-Ghadim; Ali Balador; Mahshid Helali Moghadam; Hans Hansson; Mauro Conti (Comput. Ind., 2023)

Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system. - Markus Borg; Jens Henriksson; Kasper Socha; Olof Lennartsson; Elias Sonnsjö Lönegren; Thanh Bui; Piotr Tomaszewski; Sankar Raman Sathyamoorthy; Sebastian Brink; Mahshid Helali Moghadam (Softw. Qual. J., 2023)

Using Decision Support to Fortify Industrial Control System Against Cyberattacks. - Alireza Dehlaghi-Ghadim; Niclas Ericsson; Lars-Göran Magnusson; Mats Eriksson; Mahshid Helali Moghadam; Ali Balador; Hans Hansson (ETFA, 2024)

Lithium-Ion Battery SOH Forecasting: From Deep Learning Augmented by Explainability to Lightweight Machine Learning Models. - Arman Sheikhani; Ervin Agic; Mahshid Helali Moghadam; Juan Carlos Andresen; Anders Vesterberg (ETFA, 2024)

A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks. - Seyed Jalaleddin Mousavirad; Diego Oliva; Gerald Schaefer; Mahshid Helali Moghadam; Mohammed El-Abd (EvoApplications@EvoStar, 2024)

Enabling Smart Retrofitting and Performance Anomaly Detection for a Sensorized Vessel: A Maritime Industry Experience. - Mahshid Helali Moghadam; Mateusz Rzymowski; Lukasz Kulas (CoRR, 2024)

Machine learning testing in an ADAS case study using simulation-integrated bio-inspired search-based testing. - Mahshid Helali Moghadam; Markus Borg; Mehrdad Saadatmand; Seyed Jalaleddin Mousavirad; Markus Bohlin; Björn Lisper (J. Softw. Evol. Process., 2024)

Machine Learning-Driven Intrusion Detection and Identification in Industrial Control Systems. - Alireza Dehlaghi-Ghadim; Mona Moslemzade; Nima Pattiyampully Dharmapal; Niclas Ericsson; Mahshid Helali Moghadam; Ali Balador; Hans Hansson (PDP, 2025)

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems. - Khashayar Etemadi; Marjan Sirjani; Mahshid Helali Moghadam; Per Erik Strandberg; Paul Pettersson (CoRR, 2025)

Alleviating Attack Data Scarcity: SCANIA's Experience Towards Enhancing In-Vehicle Cyber Security Measures. - Frida Sundfeldt; Bianca Widstam; Mahshid Helali Moghadam; Kuo-Yun Liang; Anders Vesterberg (CoRR, 2025)