Mohammad Ghaith Altarabichi is a postdoctoral researcher at the School of Information Technology , Halmstad University. His research focuses on leveraging Evolutionary Computation (EC) to optimize Deep Learning (DL) models, covering feature selection, hyperparameter tuning, and architectural decisions like loss and activation functions. He has published in top-tier venues such as Expert Systems With Applications , Information Sciences , and conferences like GECCO and IEEE CEC . His work intersects Artificial Intelligence , Battery Technology , and Transportation Systems , particularly in optimizing DL for battery state-of-health estimation and fault detection in evolving environments. Recent publications explore Randomness Techniques in DNNs and Kolmogorov-Arnold Networks (KANs) for regularization and performance enhancement. Scientific Awards: 2nd place in ESREL 2020 AI competition Global Swede 2017 award He has contributed to advancing Evolutionary Deep Learning frameworks, with applications spanning Health Informatics , Computational Neuroscience , and Energy Systems . His research also includes Accessible Technology , such as a vision-based indoor navigation system for visually impaired individuals.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۶-۲۰ از ۲۰ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Edmund Burke is a Professor and Vice Chancellor at Bangor University. His research focuses on operations research, combinatorial optimization, and algorithm development, with notable contributions to scheduling, hyper-heuristics, and airport ground movement optimization. He has published extensively on topics such as constraint propagation, routing algorithms, and multi-objective optimization. Research interests include algorithmic approaches for real-world problems, such as airport slot allocation, maintenance crew scheduling, and timetabling. His work often integrates heuristics and metaheuristics to tackle complex optimization challenges. Recent publications explore cutting-edge techniques like memetic algorithms for ground movement and hyper-heuristics for nurse rostering. Burke has contributed to interdisciplinary projects, including collaborations with Danish railways and airport logistics systems. He actively participates in university administration, organizing alumni events and engaging in outreach activities such as exhibitions and community days. His academic leadership roles underscore his commitment to both research excellence and institutional governance.
Raimundo Saonaمشاهده پروفایل
پژوهشگر ارشد
Raimundo Saona is a Research Fellow in the Department of Mathematics at the London School of Economics and Political Science (LSE), where he joined in 2025. His work bridges theoretical mathematics with practical applications in computer science and decision theory. His research focuses on Game Theory, Probability Theory, Algorithmic Game Theory, Stochastic Analysis, Optimal Control, and Imprecise Probability Theory. He develops mathematical tools to provide new insights on situations involving uncertainty, working with both continuous and discrete models, proving theoretical existence theorems, coding efficient algorithms, and analyzing both dynamic online and static offline settings. His publication record shows a strong focus on stochastic games, Markov decision processes, and prophet inequalities. His recent work (2022-2024) has centered on ergodic unobservable MDPs, marginal values in stochastic games, and zero-sum random games on directed graphs, demonstrating his continued contribution to advancing theoretical frameworks in game theory and decision processes. His earlier work established foundational results in POMDPs and prophet inequalities.
Adrien Saumardمشاهده پروفایل
دانشیار
Adrien Saumard is a tenured Associate Professor at ENSAI, Bruz, France, and a permanent member of the CREST (Center for Research in Economics and Statistics) laboratory. His academic roles include heading the Department of Statistics since September 2022 and co-organizing the Statistical Seminar in Rennes since 2015. He also held leadership positions in the "groupe stat math" (2016-2022) and managed the "Data Science et Génie Statistique" program (2021-2022). His research spans statistical learning theory , robust learning (MOM principle), empirical process theory , and functional/concentration inequalities . Notably, he integrates Stein's method into his work and explores hyper-parameter tuning and learning with differential privacy . Adrien earned his HDR (Habilitation à Diriger des Recherches) in 2020, France's highest academic qualification enabling him to supervise PhD students. His doctoral advisees include Amandine Dubois (focusing on high-dimensional statistics under confidentiality constraints ) and Edouard Genetay (specializing in robust clustering in large dimensions via the CIFRE program with LumenAI). His career includes postdoctoral positions in Paris, Seattle (Jon A. Wellner's team), and Valparaiso before joining ENSAI in 2015.
Recep Firat Cekinel is a Turkish NLP researcher who recently obtained his Ph.D. in Computer Engineering from Middle East Technical University (METU). He spent 13 months as a visiting predoctoral researcher at the University of Tübingen and is currently a researcher on the EU-funded EXA4MIND project, where he develops NLP pipelines that convert natural language into database queries using large language models. His research focuses on responsible, scalable AI systems and bridges foundational NLP work with real-world applications. Education: Ph.D. in Computer Engineering, Middle East Technical University (METU), Türkiye Visiting Predoctoral Researcher, University of Tübingen, Germany (13 months) Research Interests: Dr. Cekinel’s work spans natural language processing , multimodal fact-checking , explainable AI , and large language models . He is particularly interested in building responsible and scalable AI systems that integrate foundational research with practical deployments, such as natural-language interfaces for high-performance computing environments. Recent Publication Trends: His 2025 publications reveal a concentrated effort on multilingual and multimodal fact-checking , satire-style debiasing , and NL-to-database-query generation . Earlier work explores graph-based event extraction , Turkish irony detection , and cultural-heritage text mining , demonstrating a trajectory from low-resource Turkish NLP toward globally applicable, responsible-AI systems. Contact & Code: Email: rfcekinel@ceng.metu.edu.tr Office: METU Computer Eng. Dept. A-206, 06800 Ankara, Turkey Phone: +90-(312)-210-5593 GitHub: firatcekinel Google Scholar: profile available