Soheila Sadeghi

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• PhD Student at University of the Incarnate Word

This study proposes a novel Robust, Resilient, and Risk‐Based approach in Machine Learning (3RML) that emphasizes the application of project scheduling for the first time. A robust stochastic LASSO regression model is proposed to predict project duration. This model seeks to enhance a traditional LASSO regression by minimizing the expected value an...

As today’s job seekers pursue their need for upskilling, human resource development (HRD) areas must design innovative training. Instruction must consider the affective use of AI in delivering workforce education. Keywords: Artificial Intelligence, Human Resource Development, Spiral Dynamic Theory, Workforce Development, Upskilling

Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast pro...

The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment, performance evaluation, and employee engagement. While AI offers numerous advantages, such as improved efficiency, reduced bias, and hyper-personalization, it raises significant concerns about employe...

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial...

Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast pro...

The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment, performance evaluation, and employee engagement. While AI offers numerous advantages-such as improved efficiency, reduced bias, and hyper-personalization-it raises significant concerns about employee...

—In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucia...

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial...

Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast pro...

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates...

There is a growing need for a more diverse teacher workforce in the United States to close the racial and ethnic gap between students and teachers. Due to the significant gap in the literature and the practical relevance of the topic, we propose a conceptual framework to apply artificial intelligence (AI) to address inequities in recruiting, hiring...

This study investigates the impact of capital increases on market reactions, focusing specifically on pharmaceutical companies listed on the Tehran Stock Exchange (TSE). We analyze stock returns over a six-month window: three months preceding and three months following the announcement of capital increases. Employing the market model, we assess inv...

Adult online learning can be a very complex and volatile process, often leading to different expected and/or unexpected outcomes attributed to both learner-specific and non-learner-specific motivational factors. Despite the growing research literature recently, most studies examine online adult online learning motivation only from one perspective a...

In an increasingly complex financial market, selecting the optimal stock portfolio has become a subject of intense debate. This study aims to develop a model for optimal stock portfolio selection. We apply Markowitz's mean-semivariance approach to determine the downside risk of portfolios, which reflects investors' intuitive perception of risk. In...