My name is Laith. I am a a PhD candidate at Vrije University Amsterdam where I am delving into the fascinating realm of AI applications in supply chain management, with an emphasis on Pon’s supply chain. My initial exposure to supply chain management occurred during my Bachelor’s degree in Industrial Engineering at the American University of Sharjah, UAE. There, I gained insights into other relevant paradigms, such as operations research, logistics modeling, and Six Sigma methodologies.

Following the completion of my Bachelors, I gained experience as an omni-channel analyst at a multinational FMCG. Despite the valuable insights I acquired, I felt an urge to deepen my expertise, leading me to pursue a Master’s in Supply Chain Management from Aston University, UK. My research endeavours have centered around the development of advanced machine learning models to address pressing environmental concerns within supply chain systems. One notable project involved optimizing supplier selection in a large construction supply chain to minimize carbon footprint. Additionally, I have explored environmentally conscious solutions to the vehicle routing problem, culminating in a publication in Transportation Research Part D. Meta-heuristics, a crucial component of these solutions, is an area I am particularly passionate about.

As a PhD candidate, my primary objective is to expand the boundaries of AI and how the solutions can be translated to existing supply chains to solve and drive valuable insight. I am driven to develop innovative machine learning models with a great emphasis on reinforcement learning that are capable of revolutionizing supply chain practices and contribute to a sustainable future. Beyond my academic pursuits, I find joy in playing the piano, socializing with friends, and staying updated on AI advancements, as I ardently believe AI will play a pivotal role in shaping our future world.

At the AI Lab, I am actively engaged in various projects that align with my passion for sustainability and AI optimization within supply chain management. One of the primary projects I will be working on involves the implementation of reinforcement learning models to improve forecasting of raw components in production processes. By leveraging these models, I aim to enhance production efficiency and ultimately strengthen supply chain resilience. Additionally, I am in the early stages of exploring another project related to sustainability and emissions assessment within supply chains. Although the scope is still being defined, the goal is to investigate advanced deep learning networks’ potential in capturing and predicting emissions data for different distribution and supplier strategies. The insights gleaned from this work will be instrumental in informing supplier selection decisions and their impact on Pon’s overall corporate social responsibility (CSR) strategy.

By working on these cutting-edge projects at the AI Lab, I strive to contribute to the development of AI-driven solutions that bolster the paradigms that exists in supply chain management and sustainability, while also advancing our understanding of how AI can be harnessed to create a more resilient and eco-friendly future.