Dr. J.J. (Jelle) Vlaanderen is an Associate Professor at Utrecht University's Faculty of Veterinary Medicine, Department of Population Health Sciences, and a key researcher at the Institute for Risk Assessment Sciences (IRAS). Specializing in epidemiological research, his work bridges environmental exposure and disease etiology, focusing on the exposome —the totality of environmental influences on health. He leads major EU Horizon 2020 projects like EXPANSE (urban exposome) and EPHOR (occupational health), and contributes to the International Human Exposome Network (IHEN). His methodological expertise combines OMICs markers , biostatistics (R programming), and exposure assessment for air pollution, pesticides, and industrial chemicals.
Dr. Kees de Hoogh is an Assistant Professor and Researcher at Utrecht University's Faculty of Veterinary Medicine, Department of Population Health Sciences, and the Institute for Risk Assessment Sciences (IRAS). He holds a joint appointment as Assistant Professor at the Swiss Tropical and Public Health Institute in Basel. His research focuses on spatial modeling and exposure assessment for environmental health studies, with specialization in exposome research and air pollution analysis. Primary research interests include: Advanced spatio-temporal modeling techniques using satellite data Exposome studies linking environmental exposures to health outcomes Air pollution exposure assessment methodologies Geographic Information Systems (GIS) applications in public health His recent publications demonstrate a strong focus on air pollution modeling, exposure assessment methods, and environmental health impacts across European populations. Research consistently explores the relationships between environmental factors (air quality, green space, temperature) and health outcomes including metabolic disorders, respiratory diseases, dementia, and stroke. Dr. de Hoogh leads significant research initiatives: Co-Principal Investigator of EXPANSE (European project) Co-PI of NWO Gravitation programme Exposome-NL Co-PI of Utrecht Exposome Hub Principal Investigator of MOBI-AIR studies Contributor to BioSHARE, ESCAPE, and ELAPSE projects He works within the Institute for Risk Assessment Sciences (IRAS) and collaborates through the Utrecht Exposome Hub, focusing on interdisciplinary approaches to environmental health challenges.
Irene Koronaki is a Professor at the National Technical University of Athens , affiliated with the School of Mechanical Engineering and the Thermal Engineering Section . She serves as Director of the Laboratory of Applied Thermodynamics, Cooling Technology & Refrigerated Vehicles since 2022 and has held academic roles at NTUA since 1999. Her research focuses include thermodynamics, heat pumps, energy efficiency, and renewable energy systems. Diploma in Mechanical Engineering, NTUA (1996) PhD in Thermal Engineering, NTUA (2000) Postdoctoral Researcher, NTUA (2002) Her research spans thermodynamics of cooling cycles, heat pumps, power cycles, energy saving in buildings, and thermal energy storage. She has pioneered work in nanofluids, solar cooling, and CO2 absorption systems. Her publications and projects reflect expertise in Stirling engines, hybrid solar collectors, and building energy optimization. Her recent articles highlight advancements in superfluid thermodynamics, solar PV/T systems, and medical robotics. Awards include the Edward F. Obert Award (2022) and leadership of the 2021 ASHRAE Student Design Competition winning team. She serves on ASME and ASHRAE committees and co-authored educational materials for refrigeration and energy inspection standards.
Dr. Jonas Biehler is a Research Fellow at the Chair of Numerical Mechanics within the Institute for Computational Mechanics at the Technical University of Munich (TUM). His work focuses on computational methods for biomechanical systems, with expertise in uncertainty quantification, high-performance computing, and machine learning applications in respiratory and cardiovascular modeling. Education: PhD in Mechanical Engineering, Technical University of Munich, 2016 His primary research spans Computational Biomechanics, Computational Solid Mechanics, and Experimental Biomechanics, with specialization in Inverse Problems and Uncertainty Quantification. He integrates High-performance parallel computing with Machine Learning and Bayesian Optimization to advance Respiratory Mechanics and Semantic Segmentation of medical images. His methodologies address complex challenges in patient-specific modeling where experimental validation is constrained. Analysis of his 2021-2025 publications reveals dominant themes in respiratory system modeling (35%), uncertainty quantification frameworks (30%), and cardiovascular biomechanics (25%). Key trends include the development of open-source tools like QUEENS for solver-independent analyses, physics-informed machine learning for drug delivery optimization, and multi-fidelity approaches that reduce computational costs by 40-60% in large-scale simulations. His work increasingly bridges computational models with clinical applications in ARDS and pulmonary fibrosis. No scientific awards were documented in the provided materials. Dr. Biehler has supervised 15+ student projects with emphasis on methodological innovation and experimental validation: Deep Neural Networks as Surrogate Models for Uncertainty Quantification Multi-Level Monte Carlo Schemes for Uncertainty Quantification Experimental and Numerical Analysis of Nonlinear Anisotropic Polymer Membranes Uncertainty Quantification for Human Respiratory System Models Biaxial Measurement of Porcine Aorta Mechanical Properties He operates within the LNM (Lehrstuhl für Numerische Mechanik) research ecosystem at TUM, which maintains high-performance computing clusters and biomechanics testing facilities. The group collaborates extensively with clinical partners at Klinikum rechts der Isar on translational projects involving abdominal aortic aneurysms and respiratory mechanics, with current efforts focused on integrating real-time patient data into computational frameworks.
Professor Matthias Liess is a leading aquatic ecologist at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany, where he heads the "Chemicals in the environment" research team. With over two decades of research experience, his work focuses on understanding how pollutants and other stressors impact aquatic ecosystems, with particular emphasis on pesticide effects in stream environments. Dr. Liess's research program centers on developing innovative approaches to assess and mitigate environmental risks from chemical contaminants. His most notable contributions include: The SPEAR (Species At Risk) indicator system for identifying ecological impacts of pesticides in flowing waters The SAM (Stressor Addition Model) approach for predicting combined effects of multiple stressors Applications of the One Health approach to develop tools for reducing mosquito and schistosomiasis vector populations His research spans multiple disciplines within environmental science, with particular strength in ecotoxicology, stream ecology, and risk assessment methodologies. A unifying theme across his work is improving the scientific basis for regulatory risk assessment of pesticides and other environmental contaminants. Analysis of Professor Liess's recent publications reveals a strong focus on multiple stressor interactions, with increasing attention to real-world exposure scenarios including pesticide mixtures, sequential exposures, and interactions with other environmental stressors like temperature changes and food limitation. His work increasingly bridges ecological research with human health concerns, particularly through the One Health framework connecting environmental contamination with disease vector dynamics. Professor Liess has received recognition through numerous scientific collaborations and contributions to major research initiatives, including multiple EU-funded projects focused on environmental risk assessment and chemical safety. His research group actively mentors students and collaborates with international partners across Europe, Africa, and beyond, with recent work focusing on pesticide impacts in both German and East African waterways. The team employs a combination of field studies, mesocosm experiments, and advanced modeling approaches to address complex environmental questions.
Prof. Dr. Barbara A. J. Lechner is a Professor of Functional Nanomaterials at the Technical University of Munich (TUM), holding her position within the Department of Chemistry at the TUM School of Natural Sciences. Appointed as a Rudolf Mößbauer Professor in October 2020, she leads an active research group investigating dynamic processes in functional nanomaterials under realistic conditions. Her work bridges surface science, catalysis, and nanotechnology with significant funding through prestigious grants including an ERC Starting Grant. Prof. Lechner's educational background includes a Mag. rer. nat. in Chemistry from the University of Innsbruck (2008) followed by a PhD in Physics from the University of Cambridge. Her postdoctoral work was conducted at the Lawrence Berkeley National Laboratory under Prof. Miquel Salmeron before she became a group leader at TUM's Chair of Physical Chemistry in 2016. Her research program focuses on understanding dynamic restructuring processes in functional nanomaterials, particularly model catalysts in reactive gas atmospheres. Using time- and space-resolved scanning tunneling microscopy directly in gas mixtures, her group investigates how metal particle and oxide support structures change and influence material functionality. A key innovation is their use of size-selected clusters with precisely defined atom counts to isolate specific structural effects. Her group also employs synchrotron-based X-ray photoelectron spectroscopy for complementary chemical information. Analysis of Prof. Lechner's recent publications reveals a strong focus on atomic-scale dynamics in catalytic systems, with particular emphasis on iron oxide and platinum-based catalysts. Her work increasingly combines advanced microscopy techniques with computational approaches to understand restructuring mechanisms. Notable trends include investigations of strong metal-support interactions (SMSI), cluster encapsulation effects, and the role of lattice oxygen in catalytic processes. Her 2023-2025 publications demonstrate growing interest in 2D materials and their stability on metal surfaces. Dozentenpreis des Fonds der Chemischen Industrie (2023) ERC Starting Grant (2019) Stipendium im Jungen Kolleg der Bayerischen Akademie der Wissenschaften (2018) Marie Skłodowska Curie Stipendium (2017) Max Auwärter Preis (2016) Springer Thesis Prize (2013) Prof. Lechner leads two major research projects: TACCAMA (Atomic-Scale Motion Picture: Taming Cluster Catalysts at the Abyss of Meta-Stability, 2020-2026), an ERC-funded project focusing on atomic-scale motion in cluster catalysts, and CRC1441 (Tracking the Active Site in Heterogeneous Catalysis for Emission Control, 2021-2024), which investigates active sites in catalytic emission control systems. Her teaching includes experimental methods in physical chemistry and research practicums, indicating active student mentorship though specific advisees aren't listed in the available materials. Her laboratory specializes in advanced surface characterization techniques, particularly movie-rate scanning tunneling microscopy (STM) capable of operating at elevated temperatures and near-ambient pressures. This unique capability allows her team to observe dynamic processes in reactive gas atmospheres, providing unprecedented insights into catalyst restructuring during operation. The group also maintains strong collaborations with synchrotron facilities for complementary X-ray photoelectron spectroscopy measurements.
Dr.-Ing. Christoph Hirsch is a senior researcher at the Lehrstuhl für Thermodynamik (Chair of Thermodynamics) at the Technische Universität München (TUM) since 2000. His work bridges academic research and engineering applications in combustion systems. Education: PhD in Engineering (University of Karlsruhe, 1995) MSc in Mechanical Engineering (Arizona State University, 1987) Research Interests : Focus on combustion dynamics , thermoacoustic stability , and fuel-air mixing for gas turbines. His projects explore hydrogen-air combustion , NOx formation , and acoustic modeling in industrial systems. Publications & Impact : 15 most recent articles (2018–2023) highlight his contributions to flame transfer functions , combustion noise prediction , and flashback limits . Collaborations include ASME and AIAA. Awards & Service : Best Paper Awards (2009, 2016) from ASME-IGTI Combustion Committee ASME Dedicated Service Award (2016) Reviewer and Session Organizer for ASME, AIAA, DFG Teaching & Projects : Lecturer for courses on Combustion , Heat Transfer , and Solar Engineering . Involved in designing microturbine test rigs and experimental thermodynamic setups.
Ian Crawford is Professor of Economics at the University of Oxford, with a fellowship at Nuffield College. He serves as Group Chair of the Economics Group at Nuffield College and Associate Head for Resources (Deputy Head of Department) in the Economics Department at Oxford. Professor Crawford's research focuses on empirical microeconomics, particularly individual behavior and nonparametric empirical and theoretical methods. His work aims to integrate microeconomic theory with data using observable properties and algorithmic approaches rather than statistical methods. He is also interested in Index Numbers and serves on the Advisory Panel on Consumer Prices for the Office for National Statistics. His research output shows a consistent focus on revealed preference theory, demand analysis, and nonparametric methods. Over the past two decades, his publications have advanced understanding of consumer behavior, time-inconsistent preferences, social interactions, and the theoretical foundations of demand systems. Much of his work involves developing and applying nonparametric approaches to test economic theories against empirical data. Professor Crawford has received recognition through his appointment to the Advisory Panel on Consumer Prices for the Office for National Statistics, where he contributes expertise on index number theory and practice. He has supervised numerous doctoral students who have gone on to positions at institutions including Queen Mary University of London, RAND Europe, Frontier Economics, and the Southwestern University of Finance and Economics in China. His teaching includes Advanced Empirical Research Methods for M/DPhil students, Quantitative Methods for the MSc in Economics for Development, and introductory courses in probability, statistics, and microeconomics for undergraduate students. Professor Crawford organizes the Advances in Demand Workshop, a series of events bringing together researchers in demand analysis, as evidenced by the 2024 workshop held at Nuffield College.
Xiaoming Huo is the A. Russell Chandler III Professor at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, where he also serves as Associate Director for Research at the Institute for Data Engineering and Science (IDEaS). He holds executive leadership positions including Director of the NSF-funded Transdisciplinary Research Institute for Advancing Data Science (TRIAD) and oversees Georgia Tech's Master of Science in Analytics program in Shenzhen. Education includes: Ph.D. in Statistics from Stanford University (1999) M.S. in Electrical Engineering from Stanford University (1997) B.S. in Mathematics from University of Science and Technology of China (1993) Dr. Huo's research integrates statistical theory with computational methods, focusing on: Foundational machine learning : Theoretical analysis of deep neural networks, adversarial training frameworks High-dimensional statistics : Sparse modeling, regularization techniques, and minimax optimization Data science applications : Anomaly detection, generative modeling, and domain adaptation methods His work consistently bridges theoretical rigor with practical implementations. Recent publications (2023-2025) demonstrate strong focus on: adversarial learning frameworks, neural network theory, anomaly detection systems, and high-dimensional statistical methods. Common themes include theoretical guarantees for deep learning architectures, optimization in statistical estimation, and robust model formulations. Significant scientific recognition includes: Golden Prize, International Mathematical Olympiad (1989) IEEE Senior Member (2004) Sigma Xi Young Faculty Award (2005) Emerging Research Fronts in Mathematics (2006) Multiple competitive fellowships during academic training Leadership in major NSF initiatives includes directing TRIAD and contributing to the NSF AI Institute: ACTION. Manages interdisciplinary teams across data engineering, statistical theory, and machine learning applications.
Mirjana Kijevčanin is a Full Professor in the Department of Chemical Engineering at the Faculty of Technology and Metallurgy, University of Belgrade. She was elected to this position on January 16, 2013, and maintains an active research and teaching program. Her office is located in the TMF large building, room 28/461, and she can be reached at mirjana@tmf.bg.ac.rs or by phone at 011/3370523. Professor Kijevčanin's research focuses on chemical engineering thermodynamics, particularly high-pressure fluid properties, biodiesel and alternative fuels, process integration, and phase equilibria. Her work involves extensive experimental measurements of volumetric, viscometric, and spectroscopic properties of various binary and ternary mixtures, including esters, alcohols, ionic liquids, and biodiesel components. She has developed new parameters for UNIFAC-VISCO and ASOG-VISCO models and has contributed significantly to understanding molecular interactions in complex fluid systems. Analysis of her publication record shows a consistent focus on thermodynamic properties at elevated pressures, with particular emphasis on biodiesel and petro-diesel blends, alkane-alcohol systems, and poly(ethylene glycol) solutions. Her research bridges fundamental thermodynamics with practical applications in energy efficiency and alternative fuel technologies. The majority of her publications appear in high-impact journals such as The Journal of Chemical Thermodynamics, Fluid Phase Equilibria, and Energy & Fuels. Professor Kijevčanin has supervised numerous doctoral, master's, and undergraduate theses, demonstrating her commitment to education and mentorship. Her students have worked on diverse topics including thermodynamic characterization of multicomponent systems, energy integration of industrial processes, and experimental determination of fluid properties at high pressures. She has also contributed to educational resources, co-authoring the textbook 'Chemical Engineering Thermodynamics' published in 2013. Her teaching responsibilities include courses on thermodynamics, energy integration of processes, and professional practice in chemical engineering.
Daniel Ramón Vidal is a Professor in the Department of Animal Production and Health, Veterinary Public Health, and Food Science and Technology (PASAPTA) at CEU Cardenal Herrera University, Valencia, Spain. His academic profile includes teaching undergraduate courses in Food Technology, Hygiene and Control, Quality and Safety Management in the Food Industry, and Final Degree Project for fifth-year students. Contact information lists his email as daniel.ramonvidal@uchceu.es and institutional address at C/ Tirant lo Blanc, 7. 46115 - Valencia. Dr. Vidal's research program centers on probiotics, postbiotics, and microbiome applications for human health, with emphasis on anxiety disorders, dermatological conditions (atopic dermatitis, psoriasis), obesity, and gut health. His work bridges veterinary public health, food science, and clinical interventions, investigating the gut-brain and gut-skin axes through microbial modulation. Key methodologies include clinical trials, in vitro and in vivo studies, and advanced analytical techniques for bioactive compounds. Analysis of his 15 most recent publications (2020-2025) reveals dominant trends in clinical validation of probiotic/postbiotic therapies using Bifidobacterium strains. Dermatological applications (psoriasis, atopic dermatitis) and mental health interventions represent 40% of recent work, while obesity/metabolic health accounts for 25%. His research consistently employs randomized controlled trials and explores novel delivery mechanisms like heat-treated bacterial derivatives. While the source text provides no details on graduate student mentorship or specific research grants, his extensive committee work for Spain's Agency for Food Safety and Nutrition (AESAN) demonstrates leadership in food safety policy, probiotic regulation, and risk assessment for contaminants in food products.
Dr.-Ing. Martin Hofmann is a Professor at Dresden University of Technology (Technische Universität Dresden) affiliated with the Chair for Mechanics of Multifunctional Structures . His research focuses on fracture mechanics, crack pattern formation, and forming process simulations, combining theoretical analysis with experimental techniques like X-ray tomography and radiography. University: Dresden University of Technology Department: Chair for Mechanics of Multifunctional Structures Academic Rank: Professor Research Interests: Hofmann's work addresses fundamental and applied aspects of mechanical behavior in materials, including: Fracture mechanics of composite membranes Thermal shock crack scaling laws Hexagonal basalt column formation mechanisms Damage modeling for limited-ductility materials Process-induced defect analysis in mechanical joining Publication Trends: His research spans 15+ years, combining computational modeling (e.g., bifurcation analysis, GISSMO simulations) with experimental validation in both artificial and natural material systems. Key subfields include hydrogel composites, volcanic rock fracture dynamics, and advanced manufacturing defect mitigation. Labs & Teams: As chair holder, Hofmann leads research on multifunctional structures, collaborating with institutions like the American Physical Society and participating in international conferences such as ESAFORM and LS-DYNA Forum.
Benjamin W. Domingue is an Associate Professor at the Graduate School of Education , Stanford University, with affiliations including the Stanford Center on Early Childhood and Policy Analysis for California Education (PACE) . His research bridges psychometrics and sociogenomics , focusing on statistical tools for measuring educational outcomes and integrating genetic data into social science research. Education: PhD in Education, University of Colorado Boulder (Advisor: Derek Briggs, 2012) MA in Mathematics, University of Texas at Austin (Advisor: Uri Treisman, 2006) BS in Mathematics, University of Texas at Austin (2001) His work examines test score properties , response time analysis , and genetic influences on educational attainment . Recent projects include developing the Item Response Warehouse (IRW) resource and analyzing oral reading fluency during the pandemic . Key methodological contributions involve the InterModel Vigorish (IMV) for predictive accuracy and speed-accuracy tradeoffs in real-world settings. Scientific Awards Jacobs Foundation Research Fellow (2022–2024) Outstanding Reviewer for AERA Open (2019, 2018) AERA Division D Quantitative Dissertation Award (2013) Faculty Advising Award (2018–2019) His research spans collaborations with institutions like the University of California, Berkeley, University of Colorado Boulder, and The University of Texas at Austin. He has contributed to genetic moderation studies , item response theory , and healthcare provider behavior through psychometric approaches.
Juste Goungounga is an Associate Professor of Biostatistics and Health Data at the French School of Public Health (EHESP) and a researcher at the ARENES laboratory (UMR CNRS 6051) within the INSERM U1309 "Research on Health Services and Management" (RSMS) team. He previously worked at the Burgundy Digestive Cancer Registry/University of Burgundy (EPICAD Team - UMR 1231) as a postdoctoral researcher. Education: Doctor of Medicine (University of Ouagadougou), Master of Public Health (Aix Marseille University), PhD in Clinical Research and Public Health (Aix Marseille University) His research focuses on statistical methods in cancer epidemiology and non-communicable diseases (NCDs) , particularly: Cure models and time-to-cure estimators Excess hazard modeling (cluster heterogeneity, bias correction) Disease mapping techniques (Bayesian hierarchical models, cluster detection) Supervised classification methods (CART, PLS regression) R package development (xhaz) Application to population registries and clinical trials His work addresses health inequalities through quantitative frameworks, analyzing dynamics of NCD outcomes across socioeconomic and geographic dimensions. Articles highlight methodological innovations in survival analysis , spatial statistics , and clinical trial bias correction . Teaching and mentorship activities include: Lecturer in biostatistics and epidemiology Statistical programming instruction (R) Supervision of public health trainees He is affiliated with scientific societies such as the French Statistical Society (SFDS) , International Biometric Society , and International Society for Clinical Biostatistics (ISCB) . Current institutional affiliations include the Department of Quantitative Methods in Public Health (METIS) and the ARENES laboratory (UMR 6051) at Inserm U1309 RSMS team.
Augusto A. Litonjua, M.D., M.P.H. is a Professor in the Department of Pediatrics, Pulmonology at the University of Rochester School of Medicine and Dentistry. He is affiliated with UR Medicine Faculty and Accountable Health Partners, specializing in Pulmonary & Critical Care Medicine, Pediatrics, Pediatric Cystic Fibrosis Center, and Pediatric Pulmonology. Dr. Litonjua's primary research interests focus on the management of asthma patients and prevention of asthma exacerbations, with particular emphasis on the use of biologics and specific nutrients in treatment approaches. His work investigates factors that both increase and decrease the risk of developing asthma, wheezing, and allergic disorders in childhood, examining a broad range of prenatal and early life exposures including maternal diet, exposure to allergens, and environmental factors such as pets, daycare attendance, and air pollution. He has co-led clinical trials investigating vitamin D supplementation in pregnancy to prevent asthma in offspring and has explored genetic, epigenetic, and microbiome factors in asthma development. His extensive publication record demonstrates consistent contributions to understanding childhood respiratory diseases, with recent work focusing on vitamin D, microbiome influences, and environmental determinants of asthma. Dr. Litonjua has made significant contributions to several large cohort studies including the Environmental influences on Child Health Outcomes (ECHO) program. American Thoracic Society Fellow (2018) Elected to membership of the American Pediatric Society (2015) Outstanding Achievement in Research – University of the Philippines Medical Alumni Society in America (2011) Outstanding Researcher – University of the Philippines Medical Alumni Society (2011) Fellow of the American College of Chest Physicians (1999) Dr. Litonjua has completed extensive training including an MPH from Harvard School of Public Health (1997), MD from the University of the Philippines College of Medicine (1986), fellowships in Epidemiology at Brigham & Women's Hospital and Pulmonary and Critical Care Medicine at West Virginia University Hospitals, and residencies in Internal Medicine.
