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Ali Saraa is a Visiting Lecturer and Postgraduate Student at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science, Institute of Artificial Intelligence and Digital Sciences, and the Research and Educational Laboratory of Big Data Analysis Methods. She began her work at HSE in 2021 and is currently in her 3rd year of postgraduate studies. Her educational background includes a Master's degree in Mechatronics and Robotics from Moscow State Technological University "Stankin" (2021) and a Bachelor's degree in Electromechanical Engineering from Tishreen University (2018). Dr. Saraa's research focuses on machine learning , deep learning , and generative adversarial networks , with applications spanning physics instrumentation, electrical engineering, safety monitoring, and educational technology. Her work on personalized adaptive learning systems involves developing methods and algorithms for building personal learning trajectories, from Bayesian Knowledge Tracing (BKT) up to modern machine learning approaches. She conducts detailed analysis of current implementations of methods and algorithms in various Personalized Adaptive Learning Systems (PALSs), examining statements, input data, results, ideas, solutions, software implementation details, efficiency, and adoption. Her recent publications demonstrate a strong trend toward applying deep learning techniques to solve practical problems across multiple scientific and engineering domains. She has made significant contributions in fault detection for electrical systems, calorimeter response correction in particle physics, safety monitoring through PPE detection, and video stream processing for robotic systems. Letter of gratitude from the Senior Director for Research and Development at HSE (August 2024) As a Postgraduate Student, Ali Saraa is working on her dissertation titled "Efficient parameterizations for training and retraining generative adversarial networks in the image and audio domain" under the supervision of Denis Aleksandrovich Derkach. She has co-authored multiple publications, contributed to research projects at the Institute for Information Transmission Problems (IITP RAS), and holds two patents related to AI applications in industrial settings. Dr. Saraa is affiliated with the Research and Educational Laboratory of Big Data Analysis Methods within the Institute of Artificial Intelligence and Digital Sciences at HSE. Her work bridges theoretical machine learning research with practical applications in physics, electrical engineering, robotics, and educational technology, demonstrating the interdisciplinary nature of modern AI research.

• Machine Learning
• Deep Learning
• Generative Adversarial Networks
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Chaouki Boulahouache is an Instructional Associate Professor and Director of Physics Labs in the Foundational Sciences unit at the College of Marine Sciences & Maritime Studies, Texas A&M University at Galveston. He holds a PhD and MS in Physics from Syracuse University (2002) and a BS in Theoretical High Energy Physics from Constantine University (1995). Research Focus: His work spans experimental and theoretical high-energy physics, specializing in particle detectors, collider experiments (CMS, ATLAS, CLEO), and fundamental particle interactions. Key areas include: Particle detector design and calibration (muon systems, calorimeters) Beyond-Standard-Model phenomena (LRSM, leptoquarks) Precision measurements in B-meson decays and Higgs boson searches Publication Trends: Recent articles emphasize LHC detector performance and data analysis (CMS muon systems, ATLAS trigger calibration), while earlier works explore theoretical frameworks (D-branes, heavy quark expansion) and specialized detector technologies (Cherenkov radiators, RICH systems). Leadership: As Director of Physics Labs, he oversees experimental facilities supporting foundational physics education and research at Texas A&M Galveston.

• Particle Physics
• High Energy Physics
• Experimental Physics
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