Ammar Khaleel is a PhD student in Computer Science at Széchenyi István Egyetem, specializing in intelligent and autonomous transportation systems. His research focuses on reinforcement learning–based decision making for autonomous vehicles, with particular emphasis on autonomous driving and lane-changing strategies. He has strong expertise in deep reinforcement learning methods such as DDPG and PPO, as well as Model Predictive Control. Ammar actively works with traffic simulation environments using SUMO and the TraCI Python API to model and evaluate complex traffic scenarios. His technical skills include Python and C/C++, along with experience in Git, LaTeX, and scientific software tools.

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Professor Mohammadali Ebrahimzadeh Mousavi is a leading expert in food science, biotechnology, and food engineering, affiliated with the University of Tehran. His work integrates advanced food processing, packaging technologies, rheology, mass and heat transfer modeling, and functional food development. He has made significant contributions to plant-based products, bioactive compounds, food hydrocolloids, encapsulation systems, and sustainable food technologies. Alongside extensive teaching at undergraduate, master’s, and doctoral levels, he has held numerous senior academic, policy-making, and industrial advisory roles. His research output, high citation impact, and technology transfer activities demonstrate strong influence in both academia and industry.

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