Xiaodong Zhou | High energy physics | Research Excellence Award

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Prof. Xiaodong Zhou | High energy physics | Research Excellence Award 

East China University of Science and Technology | China 

Prof. Xiaodong Zhou is a Professor at the Chemical Engineering School, East China University of Science and Technology (ECUST), Shanghai, where he has been a core faculty member for more than two decades. He received his doctoral degree from Nanjing University of Science and Technology and has built a distinguished academic career focused on advanced composite materials, functional interfaces, and high-performance materials for extreme environments. His research integrates fundamental colloid and interface chemistry with applied materials engineering, addressing both scientific challenges and industrial needs. Prof. Zhou’s primary research interests encompass composite materials, biodegradable and bio-based materials, graphene and related nanomaterials, antistatic materials, and composite material interface engineering. A significant part of his work is dedicated to high-energy laser protection materials, including fibrous felt-reinforced aerogels, ceramic-based composites, and polymer matrix composites designed to withstand ultra-high laser power densities. Through innovative structural design and interfacial regulation, his group has achieved materials exhibiting high reflectivity, low absorptivity, and excellent ablation resistance under continuous-wave laser irradiation. In parallel, Prof. Zhou has made notable contributions to sustainable materials and biodegradable composites. His research on starch-, cellulose-, and lignin-based composites, as well as polylactic acid and poly(vinyl alcohol) systems, has advanced the understanding of interfacial modification, processing–structure–property relationships, and mechanical and thermal performance optimization. These studies provide valuable pathways for developing environmentally friendly materials with enhanced functionality. Prof. Zhou is also actively engaged in graphene and nanostructured material research, including high-yield liquid-phase production of high-quality graphene and the design of graphene-based aerogels and composites for energy, environmental, and protection applications. His work emphasizes scalable processing methods and the translation of nanomaterial advantages into macroscopic performance.

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Michael Koutsilieris | Experimental methods | Best Academic Researcher Award

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Prof. Michael Koutsilieris | Experimental methods | Best Academic Researcher Award

Prof. Michael Koutsilieris, MD, PhD, is an internationally recognized endocrinologist, physiologist, and academic leader whose research has made seminal contributions to molecular endocrinology, endocrine oncology, and translational medicine. His scientific career bridges fundamental molecular physiology with clinical application, particularly in hormone-dependent diseases, bone metabolism, and cancer progression. With formal training at the National and Kapodistrian University of Athens and McGill University, Prof. Koutsilieris developed an early and sustained focus on the molecular mechanisms underlying prostate cancer metastasis, especially osteoblastic bone involvement, a theme that has remained central to his research trajectory. A defining contribution of his work is the elucidation of endocrine and paracrine signaling pathways that regulate bone remodeling and tumor–bone interactions in prostate cancer. His pioneering studies on prostate-derived mitogenic factors and their selective activity on osteoblasts provided foundational insights into the pathophysiology of skeletal metastases. These discoveries have influenced both experimental research and clinical strategies aimed at targeting metastatic disease. Beyond oncology, his research has expanded to include molecular mechanisms of endometriosis, reproductive endocrinology, metabolic disorders, and the systemic effects of exercise as medicine, emphasizing prevention, functional health, and quality of life. Prof. Koutsilieris has published extensively, with more than 375 peer-reviewed publications indexed in PubMed, over 17,700 citations, and an h-index of 71, reflecting sustained international impact. His work integrates molecular biology, physiology, and clinical endocrinology, advancing understanding of hormone signaling, cellular microenvironments, and disease progression. In parallel, he has been deeply engaged in medical education, curriculum development, and the promotion of physiology as a core discipline in modern medical training.

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Jin-Song Von Storch | Theoretical Advances | Research Excellence Award

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Prof. Jin-Song Von Storch | Theoretical Advances | Research Excellence Award 

Max-Planck Institute for Meteorology | Germany

Prof. Jin-Song von Storch is a senior climate scientist whose research focuses on the fundamental dynamics, variability, and predictability of the climate system, with particular emphasis on ocean–atmosphere interactions, climate energetics, and the role of stochastic processes in climate dynamics. Her work bridges theory, numerical modeling, and diagnostics of high-resolution Earth system simulations, contributing substantially to the physical understanding of climate variability across temporal and spatial scales. A central theme of her research is the energetics of the ocean and climate system, including the Lorenz Energy Cycle, energy pathways from large-scale circulation to internal waves, and the role of mesoscale and submesoscale processes. She has made pioneering contributions to quantifying how wind forcing, tides, and internal waves transfer energy within the ocean and influence large-scale circulations such as the Atlantic Meridional Overturning Circulation (AMOC). Her work has clarified how resolving ocean eddies and tides alters the climate system’s response to external forcing, including greenhouse gas increases. Another major strand of her research addresses air–sea interactions and climate variability, particularly the dependence of coupling processes on temporal and spatial scales. She has contributed key insights into how vertical mixing, surface flux fluctuations, and coupling frequency shape climate sensitivity, predictability, and variability. Her studies on equilibrium fluctuations and integral forcing provide a theoretical framework for interpreting variability in complex climate models and linking stochastic forcing to low-frequency climate behavior. Jin-Song von Storch has played a leading role in the development and application of high-resolution and eddy-rich Earth system models, including ICON-O, MPI-ESM, and EC-Earth. She has been deeply involved in international modeling efforts such as HighResMIP, PRIMAVERA, TRR181, and the Horizon Europe project EERIE, contributing to advances in kilometer-scale global simulations and their use for understanding climate processes and extremes. Her research has also addressed internal tides, near-inertial waves, and their implications for deep-ocean mixing and overturning circulation.

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Germain Hubert BEN-BOLIE | High energy physics | Research Excellence Award

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Prof. Germain Hubert BEN-BOLIE | High energy physics | Research Excellence Award 

University of Yaounde I Cameroon

Professor Germain Hubert Ben-Bolie is a distinguished Cameroonian nuclear physicist, radiation protection expert, and academic leader at the University of Yaoundé I, where he has served for over two decades in teaching, research, and scientific governance. Currently a Professor of Nuclear Physics in the Department of Physics, Faculty of Science, he is also the Director of the Nuclear Physics Laboratory and Head of the Nuclear Physics, Dosimetry, and Radioprotection postgraduate program. His career reflects a sustained commitment to advancing nuclear science, environmental radiological protection, and applied theoretical physics in Africa and beyond. Professor Ben-Bolie’s research spans a broad yet coherent range of fields, including nuclear physics, radioecology, radiation protection and dosimetry, soil–plant transfer of radionuclides, natural radioactivity assessment, and radionuclide migration in environmental systems. He has made significant contributions to understanding radiological risks associated with natural and anthropogenic sources, particularly in high background radiation areas of Central Africa. His work has informed radiation safety practices, environmental monitoring strategies, and public health assessments in Cameroon and neighboring regions. In parallel, he has produced influential theoretical research in nonlinear physics, Bose–Einstein condensate dynamics, charge and energy transport in DNA, and fractional quantum models, demonstrating a rare ability to bridge applied nuclear science with fundamental physics. As a recognized expert in radiation protection and radioecology, Professor Ben-Bolie has played a strategic national role as an expert monitoring the implementation of the Additional Protocol to the Agreement between the Republic of Cameroon and the International Atomic Energy Agency (IAEA). He is also President of the Cameroonian Radiation Protection Society and an active member of international scientific bodies, including the International Union of Radioecology. His leadership has been instrumental in strengthening national capacity in radiological safety, regulatory compliance, and scientific training.

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Tuniyazi Abudoureheman | Advanced Computing | Research Excellence Award

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Dr. Tuniyazi Abudoureheman | Advanced Computing | Research Excellence Award

Graduate School of Advanced Science and Engineering | Japan

Dr. Tuniyazi Abudoureheman is a doctoral researcher in the Smart Robotics Laboratory, Graduate School of Advanced Science and Engineering, Hiroshima University, Japan, where he is pursuing advanced research at the intersection of image processing, intelligent systems, and high-frame-rate (HFR) video analysis. His academic trajectory reflects a strong foundation in signal processing and computational intelligence, combined with a growing focus on real-world engineering applications involving visual data and dynamic system monitoring. He completed his Master’s studies at the Graduate School of Science and Technology, Tokushima University (2017–2019), where he developed a solid background in digital signal processing and computational methods. During this period, he gained hands-on experience in analyzing complex data signals and applying algorithmic techniques to engineering problems. This training laid the groundwork for his later research in image and video-based measurement systems, where precision, robustness, and computational efficiency are critical. Currently, as a Ph.D. student at Hiroshima University (2022–Present), Tuniyazi’s research is centered on advanced image processing and intelligent systems, with particular emphasis on high-frame-rate video processing. His work explores how HFR video data can be effectively leveraged to capture fast, subtle, and transient phenomena that are often missed by conventional imaging systems. By integrating intelligent algorithms with high-speed visual sensing, his research aims to enhance the accuracy and reliability of motion analysis, vibration monitoring, and dynamic system evaluation.

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Christian Schmidt | Computational QCD | Research Excellence Award

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Dr. Christian Schmidt | Computational QCD | Research Excellence Award 

Bielefeld University | Germany

Dr. Christian Schmidt is a senior researcher at the Faculty of Physics, Bielefeld University, Germany, and an internationally recognized expert in theoretical and computational high-energy physics, with a primary focus on Quantum Chromodynamics (QCD) under extreme conditions. He obtained his Diploma in Physics and Ph.D. (Dr. rer. nat.) from Bielefeld University, and completed his habilitation (PD) in Physics in 2017. His academic career spans more than two decades, with research appointments at leading institutions including Brookhaven National Laboratory (USA), the University of Wuppertal, and the Frankfurt Institute for Advanced Studies. Dr. Schmidt’s research addresses fundamental questions on the phase structure of strongly interacting matter at finite temperature and baryon density. A central theme of his work is the exploration of the QCD phase diagram, including the nature of the chiral phase transition and the possible existence and location of the QCD critical end point. He has made pioneering contributions to universal scaling analyses, analytic continuation methods, Lee–Yang and Langer edge singularities, and resummation techniques such as Padé approximants and density-of-states methods, significantly advancing lattice QCD studies at finite chemical potential. He plays a leading role in major international collaborations, including the HotQCD, Bielefeld–Parma, and BNL–Bielefeld–CCNU collaborations, contributing to landmark results on the QCD equation of state, conserved charge fluctuations, and freeze-out conditions in heavy-ion collisions. His work has direct relevance to experimental programs at RHIC, the LHC, and future facilities such as FAIR. In addition, Dr. Schmidt has contributed to the development of high-performance lattice QCD software, including multi-GPU frameworks that enable large-scale numerical simulations.

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Jian Du | Machine Learning in Physics | Best Scholar Award

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Dr. Jian Du | Machine Learning in Physics | Best Scholar Award 

Politecnico di Milano | Italy

Mr. Jian Du is a fourth-year Ph.D. candidate in Petroleum and Natural Gas Engineering at China University of Petroleum–Beijing, and a visiting Ph.D. researcher at the Department of Energy, Politecnico di Milano, Italy. His research focuses on the integration of physics-based knowledge and advanced machine learning techniques to address complex industrial challenges in liquid and multi-product pipeline systems. His core interests include explainable machine learning for pipeline process monitoring, physics-informed neural networks (PINNs) for efficient simulation of complex fluid dynamics, and knowledge-embedded data science frameworks for intelligent pipeline management. Through these efforts, he aims to bridge the gap between traditional physical modeling and data-driven approaches, improving reliability, interpretability, and real-time applicability in energy transportation systems. Jian Du has made significant research contributions in the areas of contamination tracking, hydraulic transient simulation, batch tracking, corrosion prediction, and energy system forecasting. He has authored or co-authored more than 30 peer-reviewed publications, with over 17 papers as first or second author, published in leading journals such as Energy, Engineering Applications of Artificial Intelligence, Journal of Industrial Information Integration, Renewable and Sustainable Energy Reviews, and Chemical Engineering Research and Design. His cumulative journal impact factor exceeds 95, and his work includes an ESI Hot Paper and Highly Cited Paper ranked in the top 1% of the engineering field. A recurring theme in his research is the development of the “DeepPipe” framework—a series of theory-guided, physics-enhanced, and multi-modal neural networks tailored for real-time pipeline monitoring and decision support.

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