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Gervais THENETView profile

Professor

• Management Control
• Services
• Performance Measurement
• +5 more

Gervais THENET is a Full Professor at University of Rennes 1 (IGR-IAE Rennes). He serves as Director of Studies for performance management programs and Program Director for accounting/management tracks. Specializes in Management Control and Performance Measurement in service sectors Key methodologies: Data Envelopment Analysis (DEA) Research Focus examines value creation in service companies, emphasizing sector-specific management control systems. His work spans banking, healthcare, and higher education sectors, addressing resource allocation, cost distribution, and efficiency measurement. Recent Publications (2016-2025) demonstrate DEA methodology applications in Vietnamese universities (2015), microfinance institutions (2007-2016), and food retail cost distribution (2016). His 2025 study analyzes African commercial banks' profitability and risk factors. Supervision Experience includes 7 PhD students across topics like intangible capital measurement (2019), medical-social institution management (2013), and Burkinabé cross-cultural control systems (2010). Administrative Roles include IGR-IAE Rennes Board member (since 2005) and leadership in recruitment committees for academic positions.

• Statistics
• Bioinformatics
• Biostatistics
• +7 more

Marepalli B. Rao is a Professor in the Department of Environmental Health at the University of Cincinnati's College of Medicine. He holds an Emeritus Professor title at North Dakota State University (NDSU), where he served from 1987–2003. His academic journey includes roles as Visiting Professor at the University of Pittsburgh and Lecturer at the University of Sheffield. Rao earned his B.S. and M.S. in Statistics from Madras University and a Ph.D. in Statistics from the Indian Statistical Institute. His research focuses on statistical methodologies with applications in bioinformatics, biostatistics, epidemiology, and genetic studies. Notable areas include damage models, survival analysis, and statistical genetics. Rao has contributed to over 200 peer-reviewed publications and serves on several editorial boards. His work often intersects with clinical and public health challenges, such as asthma epidemiology and environmental exposure analysis. Rao has led or collaborated on numerous grants, including NIH-funded studies on statistical genomics, tissue engineering, and pediatric allergy research. He has held leadership roles in academic committees and has mentored numerous Ph.D. students. His expertise in statistical design and analysis is applied across disciplines, from biomedical engineering to environmental health.

Takakuni SuzukiView profile

Assistant Professor

• Clinical Psychology
• Transdiagnostic dimensional psychopathology
• Personality disorders
• +7 more

Takakuni Suzuki is an Assistant Professor of Clinical Psychology in the Department of Psychology at The University of Tulsa’s Kendall College of Arts & Sciences. He holds a Ph.D. from Purdue University, with postdoctoral training at the University of Michigan. His research focuses on transdiagnostic approaches to psychopathology, integrating neurophysiological methods such as EEG and ecological momentary assessment with advanced statistical techniques like factor analysis and structural equation modeling. Education: B.S. in Psychology/Physiology (Michigan State University), M.S. in Psychology (Villanova University), Ph.D. in Clinical Psychology (Purdue University). Completed clinical internship at University of Mississippi Medical Center and postdoctoral fellowship at University of Michigan, Michigan Medicine. Research interests include personality disorders, psychosis spectrum disorders, and bipolar disorder. He investigates neural mechanisms using theta-band oscillations, event-related potentials (ERPs), and cross-frequency coupling. His work emphasizes dimensional models of psychopathology and the role of affective cognitive control. Recent articles explore theta-band activity in schizophrenia and bipolar disorder, differential item functioning in personality disorder criteria, and neurophysiological markers of response monitoring in youth. His studies utilize both experimental paradigms (e.g., flanker tasks) and community-based longitudinal designs. Labs/Teams: Leads the Inspire Lab focused on transdiagnostic psychopathology research. Collaborates with multidisciplinary teams in clinical neuroscience and measurement development.

• Parkinson's disease
• Lewy body dementia
• Movement disorders
• +6 more

Professor David Burn is a leading researcher at Newcastle University specializing in Parkinson's disease and Lewy body dementia, with active publications through 2025. His work focuses on neuropsychiatric symptoms, delirium mechanisms, brain connectivity, and therapeutic interventions in neurodegenerative disorders. His primary research interests include: Parkinson's disease pathophysiology and progression Lewy body dementia prodromal stages Delirium diagnosis and outcomes in neurological disorders Brain network connectivity using advanced imaging Metabolic and genetic biomarkers Therapeutic development for movement disorders Analysis of his 15 most recent publications (2022-2025) reveals three dominant research trajectories: (1) Delirium as a critical predictor of adverse outcomes in Parkinson's disease, with emphasis on diagnostic tool validation; (2) Biological frameworks for Parkinson's disease staging through genetic, metabolic, and imaging biomarkers; (3) Neuropsychiatric symptom progression in Lewy body spectrum disorders using longitudinal cohort designs. His work consistently employs multi-center collaborative approaches with strong clinical translation focus. Scientific awards: No awards documented in provided text Advising and grants: While specific students and grants aren't listed, his leadership in major studies (SKY/EMBARK trials, Movement Disorders Society frameworks) indicates substantial grant funding and likely PhD/MSc supervision. Collaborative patterns suggest mentorship of early-career researchers in neurology and geriatrics. Labs and teams: Professor Burn operates within Newcastle's interdisciplinary neuroscience ecosystem, collaborating extensively with Professor John-Paul Taylor (dementia research), Professor Alison Yarnall (movement disorders), and Dr. Laura Wright (neuropsychiatry). His work bridges clinical neurology, neuroimaging, and geriatric medicine through multi-institutional consortia.

Andrew G AlleyneView profile

Professor

• Control Theory
• Thermal Systems
• Manufacturing Automation
• +4 more

Andrew G Alleyne is the Ralph & Catherine Fisher Professor in Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC). He holds joint appointments in the Coordinated Science Laboratory and the Information Trust Institute. His academic roles include Director of the NSF Engineering Research Center (POETS) from 2015-2022, and he has served in leadership positions such as Associate Dean for Research (2008-2012) and Associate Head for Undergraduate Programs (2014-2015). Education: Ph.D. and M.S.E. in Mechanical Engineering from UC Berkeley (1994, 1992), B.S.E. in Mechanical and Aerospace Engineering from Princeton University (1989). Research focuses on control systems, thermal management, and mechatronics. Key areas include iterative learning control (ILC) for precision motion, transient thermal modeling for HVAC and power electronics, and additive manufacturing innovations. Applications span automotive, aerospace, and biomedical sectors. Publications highlight advancements in control theory, thermal systems, and interdisciplinary applications. Recent work emphasizes electrified mobility, hierarchical control frameworks, and nanoscale thermal devices. Over 200 peer-reviewed articles demonstrate contributions to both theoretical and applied engineering. Awards: ASME Henry Paynter Award (2014), IEEE Fellow (2017), Air Force Exemplary Civilian Service Award (2012) Grants and collaborations include leadership of the POETS ERC ($50M NSF-funded initiative). Mentoring over 50 graduate students and postdocs, with active roles in curriculum development and diversity initiatives. Serves on national committees for the NSF, ASME, and IEEE. Labs include the Alleyne Research Group focusing on mechatronics and control systems. Current projects address power density in electrified vehicles and advanced thermal management solutions.

• Tuberculosis
• Immunology
• Host defense mechanisms
• +3 more

Hardy Kornfeld, MD is a Professor at the University of Massachusetts Chan Medical School, affiliated with the T.H. Chan School of Medicine's Department of Medicine. He also holds positions in the Morningside Graduate School of Biomedical Sciences across multiple programs, including Immunology and Microbiology, Interdisciplinary Graduate Program, and MD/PhD Program. Education: BA in Liberal Arts from Bennington College (VT), MD from Boston University School of Medicine (1978). Clinical training includes medical residency at University Hospital (Boston), St. Luke's Hospital (NY), and specialized fellowships in Infectious Disease, Pulmonary Medicine, and Molecular Virology at institutions including Harvard School of Public Health. Research focuses on tuberculosis (TB) pathogenesis, host immune responses, and the impact of metabolic disorders like diabetes on TB outcomes. Key interests include macrophage apoptosis in TB defense, diabetes-TB comorbidity mechanisms, IL-16's role in immunity, and heterologous immunity between viruses and mycobacteria. Publications emphasize clinical and translational research, with recent work on post-TB lung disease, metformin's therapeutic potential in TB-diabetes comorbidity, and biomarkers predicting TB treatment outcomes. Collaborative studies involve multinational cohorts in India and Georgia. Notable contributions include defining diabetes as a risk factor for adverse TB outcomes and exploring host metabolic pathways influencing TB susceptibility. Research has implications for global TB control strategies and comorbidity management.

Georgios MichalareasView profile

Research Fellow

• Neuroscience
• Cognitive Neuroscience
• Brain Oscillations
• +3 more

Dr. Georgios Michalareas is a Senior Research Fellow in the Department of Neuroscience at the Max Planck Institute for Empirical Aesthetics, Germany, since 2015. His research focuses on functional interactions between brain areas using neuroimaging (MEG/EEG) and electrophysiology (ECOG/sEEG), with an emphasis on brain oscillations and communication mechanisms. He holds a PhD in Mathematical Modelling (University of Southampton, 2003), MSc in Telecommunications (University of Surrey, 1999), and MEng in Electrical Engineering (University of Liverpool, 1998). His career includes roles as a Research Fellow at the Ernst Strüngmann Institute (2011–2015) and University of Glasgow (2008–2011). Notable awards include the Kavli Fellowship (2017) and a Human Connectome Project research scholarship (2011–2015). His work explores how brain oscillations mediate inter- and intra-network communication, with applications to speech processing, verbal memory, and social interactions. Research Themes: Brain oscillations, functional connectivity, temporal anticipation, EEG/MEG analysis Key Projects: Human Connectome dynamics, classroom brain synchrony, crowd dynamics Recent articles highlight his contributions to understanding neural mechanisms underlying temporal expectancy and group interactions. Ongoing work integrates MEG and EEG data to map dynamic brain networks in real-world contexts.

• Artificial Intelligence
• Robotics
• Educational Technology
• +3 more

Kai Guo is an academic affiliated with the School of Computer Science and Information Engineering at Hefei University of Technology, China. His research spans interdisciplinary areas including artificial intelligence, robotics, and educational technology. He has collaborated with institutions globally on projects involving AI applications in education, industrial process optimization, and computer vision. Key research interests include AI-driven educational tools, robotics systems, and data-driven industrial analysis. Notable contributions include developing prediction models for blast furnace operations, AI-enhanced language learning platforms, and visual perception techniques in virtual reality. His work often bridges theoretical computer science with practical applications in manufacturing, education, and healthcare. Publications from 2025 focus on advanced machine learning techniques such as graph-based retrieval systems, diffusion models for anomaly detection, and VR visualization methods. Collaborations with Samuel Kai-Wah Chu and David James Woo highlight his engagement in educational technology innovation. Guo has no listed scientific awards but maintains an active research agenda with over 185 publications. His work emphasizes cross-disciplinary approaches to solving complex technical and pedagogical challenges.

• Geostatistics
• Compositional Data Analysis
• Mineral Processing
• +5 more

Prof. Dr. Karl Gerald van den Boogaart is Head of the Modelling and Evaluation department at the Helmholtz Institute Freiberg for Resource Technology (HZDR). His work focuses on advancing geostatistical methods, compositional data analysis, and their applications in resource technology, mineral processing, and environmental geochemistry. He holds a leadership role in developing stochastic models for geological systems and has contributed significantly to the field of geometallurgy through interdisciplinary research. His research integrates advanced statistical techniques, such as multivariate analysis and Bayesian methods, with practical applications in mineral exploration, ore separation processes, and environmental assessment. Key areas of interest include the development of compositional data-driven tools for decision-making in resource management and the application of machine learning to materials science challenges. Prof. van den Boogaart has published extensively on topics ranging from geostatistical simulation and particle dynamics to organizational culture modeling. His work emphasizes bridging theoretical statistical advancements with real-world industrial and environmental challenges. Notable contributions include the Georges Matheron Lecturer of the Year 2014 award, recognizing his impactful research in mathematical geosciences. His current projects involve optimizing mineral processing techniques, enhancing ionospheric tomography via geostatistical inversion, and advancing compositional data analysis frameworks. He actively collaborates with academic and industrial partners to translate research into practical solutions for sustainable resource utilization and environmental stewardship.

Lianhua ChiView profile

Lecturer

• Big Data Analytics
• Artificial Intelligence in Healthcare
• Machine Learning
• +7 more

Lianhua Chi is a Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia, since February 2018. He holds a dual PhD in Machine Learning and Data Mining from the University of Technology Sydney (Australia) and Huazhong University of Science and Technology (China). Before joining academia, he worked as a Postdoctoral Researcher at IBM Research Australia on Watson Education and Health, and as a Data Specialist at the University of New South Wales (UNSW). His research focuses on big data analytics, particularly in healthcare applications, AI-driven Autism Screening, and hashing techniques for real-time data processing. Chi has received notable awards including the 'Young Global Changer' title from G20/T20 Germany, 'Top 200 Young Researchers Globally' by the Heidelberg Laureate Forum, and the IBM External Honors award. Education: PhD in Machine Learning and Data Mining (2015), University of Technology Sydney & Huazhong University of Science and Technology Previous roles: Postdoc at IBM Research Australia, Visiting Researcher at UTS Research Interests: Chi’s work emphasizes adaptive hashing algorithms, graph stream classification, geolocation prediction in social media, and time series analysis. He applies these techniques to healthcare challenges such as AI-based Autism Screening and medical imaging diagnostics. His methodologies prioritize scalability and real-time adaptability. Awards & Grants: Best Paper Award (PAKDD13) Romberg Grant (Heidelberg Laureate Forum, 2016) Innovation Connection Grant (NostraData, 2022–2023) Advising & Collaborations: Chi has collaborated with Harvard Medical School’s Gehlenborg Lab and led projects on healthcare AI and cybersecurity. His work integrates advanced hashing techniques with clinical data to improve diagnostic accuracy and patient care efficiency. Labs/Teams: Active in interdisciplinary teams focusing on AI ethics, healthcare analytics, and big data security at La Trobe University.

• Statistical Process Control
• Probability Theory
• Quality Control
• +3 more

Laila El Ghandour is an Assistant Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University. Her research focuses on statistical process control, probability theory, and quality control methodologies. She contributes to UN Sustainable Development Goals through innovative applications of control charts and statistical modeling. Her work includes analysis of SPRT charts, gamma processes, and Weibull distributions. She has received two Certificate of Best Paper Awards in 2023 and 2024 for collaborative research on control chart performance and parameter estimation. Her recent publications explore advanced control systems, statistical monitoring techniques, and optimization of quality assurance processes. Collaborations include international conferences on robotics, signal processing, and computational science.

EMRAH AKDAMARView profile

Associate Professor

• Maritime Economics
• Logistics Performance Analysis
• Multivariate Statistical Techniques
• +4 more

Emrah Akdamar is an Associate Professor at the Department of Maritime Business Administration within the Maritime Faculty at Bandırma Onyedi Eylül University, where he also serves as the Head of the Department of Maritime Economics and Policies. His academic career includes roles as Doctor Lecturer (2019-2024) and current Associate Professorship. He specializes in maritime economics, logistics performance analysis, multivariate statistical techniques, and sustainable development strategies. His research focuses on port performance metrics, maritime trade dynamics, and statistical methodologies applied to maritime industries. He has authored/co-authored multiple books including R İle Veri Analizi 1 (2022) and contributed to international journals in logistics and maritime economics. Notable awards include the 2018 Best PhD Thesis Award from Uludağ University's Institute of Social Sciences. He teaches courses such as Operations Research and Maritime Applications, Logistics Performance Analysis, and Data Analytics. His administrative roles include Department Head and Academic Committee positions at his university. His work spans over 23 articles, 14 conference papers, and 6 books/book chapters, reflecting his commitment to advancing maritime business administration and logistics research.

Dimirovski GeorgiView profile

Professor

• Control Systems
• Neural Networks
• Cyber-Physical Systems
• +7 more

Dimirovski Georgi is a Professor at the Department of Control and Systems Engineering, Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University of Skopje. His research focuses on advanced control systems, neural networks, cyber-physical systems, and computational cybernetics. He has extensively contributed to theoretical and applied aspects of switched systems, nonlinear control, fault-tolerant mechanisms, and networked control systems. His work integrates methodologies such as Lyapunov theory, adaptive control, and reinforcement learning to address complex challenges in robotics, aerospace, and industrial automation. Recent studies emphasize resilient control under adversarial attacks, optimal resource allocation, and synchronization of dynamic systems. Key research trends include: (1) developing robust control strategies for systems with time-delays and uncertainties, (2) enhancing cybersecurity in cyber-physical systems through deception attack detection and mitigation, and (3) advancing machine learning techniques for real-time system estimation and prediction. Dimirovski has published over 200 peer-reviewed articles, with recent contributions appearing in top journals and conferences. His work frequently explores intersections between control theory and artificial intelligence, particularly in applications requiring safety-critical performance guarantees.

Kristina ÅkessonView profile

Professor

• Osteoporosis Research
• Bone Biology
• Fracture Risk Assessment
• +3 more

Kristina Åkesson is a Professor in Orthopedics and a member of the EpiHealth: Epidemiology for Health research group at Lund University's Department of Clinical Sciences, Malmö. She leads research focusing on bone biology, osteoporosis, fracture risk, and aging-related musculoskeletal integrity. Her work integrates clinical biomarkers, genetic studies, and advanced imaging to understand bone health across lifespans. Prof. Åkesson is currently leading three active research projects: investigating inflammation and osteoporosis in systemic sclerosis and elderly women, studying musculoskeletal integrity in aging, and evaluating risk factors for bone health. She manages key infrastructure including a Bone Densitometer and Peripheral CT-scanner. Her recent work has been widely recognized, appearing in high-impact journals like Osteoporosis International and EClinicalMedicine. Her research contributes to UN Sustainable Development Goals, particularly addressing health and well-being through advancements in bone disease prevention and management. She has supervised 14 academic works and actively participates in conferences such as the 2017 Forskningens Dag.

Gamal WehebaView profile

Professor

• Additive Manufacturing
• Quality Management
• Industry 4.0 in Construction
• +5 more

Dr. Gamal Weheba is a Professor in the Department of Industrial, Systems, and Manufacturing Engineering at Wichita State University’s College of Engineering. His research focuses on additive manufacturing, quality management, and statistical process control. He holds the honor of being an ASQ Fellow. Education: Ph.D. in Industrial Engineering, University of Central Florida M.Sc. in Production Engineering, Menoufia University, Egypt B.Sc. in Production Engineering & Mechanical Design, Menoufia University, Egypt Research Interests: Applications of 3D printing in construction and historical preservation Software quality measurement and ISO standards compliance E-learning quality management during crises Statistical process control methodologies Virtual reality in manufacturing and education Article Trends: Recent work emphasizes additive manufacturing’s role in construction (e.g., Portland cement 3D printing) and quality management innovations. Over 25 years of publications reflect sustained contributions to manufacturing processes, metrology, and educational technology. Awards: ASQ Fellow Advising & Grants: No explicit student advisees listed, though extensive professional experience in quality systems suggests mentorship roles. Grants and service details are not detailed in the text. Labs/Teams: Not explicitly mentioned. Research collaborations likely tied to additive manufacturing and quality initiatives.