جست‌وجوی استاد و پژوهشگر

Michel Audiffrenمشاهده پروفایل

مدرس

• Cognitive Neuroscience
• Executive Functions
• Mental Effort
• +۷ مورد دیگر

Michel Audiffren is a Lecturer at the University of Poitiers, affiliated with the Cognition and Learning Research Center (CeRCA) and Maison des Sciences de l’Homme et de la Société (MSHS). His research focuses on the bidirectional relationship between physical activity and cognitive processes, spanning cognitive neuroscience, executive functions, mental fatigue, and self-control. He employs neuroimaging (NIRS) and psychophysiological methods to study aging, cognitive performance, and exercise-induced adaptations. Role: Lecturer, University of Poitiers Research Affiliation: CeRCA/MSHS Key Collaborations: University of Geneva, University of Queensland, University of Bordeaux Michel Audiffren’s research demonstrates how chronic exercise modulates cognitive aging via neuroplasticity, while acute exercise enhances executive functions. His recent work explores mental fatigue’s impact on athletic performance, brain endurance training, and psychophysiological markers of effort engagement. Collaborative studies address genetic polymorphisms (BDNF, COMT) and physical activity’s role in depression and inhibitory control among older adults. His publications from 2022-2025 emphasize mental fatigue dynamics, cognitive load assessment, and neuroergonomics. Collaborators include Nathalie André, Cédric Albinet, and international institutions. Audiffren investigates the interplay of motor processes, decision-making, and cognitive resource allocation using behavioral and neuroimaging approaches. PhD Supervision: Anne Canivet (2012-2016), Nounagnon Frutueux Agbangla (2013-2016), Thomas Mangin (2017-2020), Marine Grousset (2019-2023) Research Tools: Near-infrared spectroscopy, dual-task paradigms, CRUNCH model

Julien Vrydaghمشاهده پروفایل

پژوهشگر ارشد

• Deliberative democracy
• Citizen participation
• Democracy theory
• +۳ مورد دیگر

Julien Vrydagh is a Research Fellow at the Institute of Social Sciences, Department of Political Theory and Empirical Democracy Research, focusing on deliberative democracy and citizen participation. He is affiliated with Vrije Universiteit Brussel . Education Bachelor of Political Sciences, Université Libre de Bruxelles (2010–2013) Master of European Studies, Ghent University (2013–2015) Master of International Relations, Ghent University (2015–2016) PhD, Vrije Universiteit Brussel & UCLouvain (2017–2023) Research Focus Deliberative minipublics Citizens' assemblies Policy impact of democratic innovations Collaborative governance Youth political engagement Citizens' meeting legitimacy Recent Publications (2023–2025) His work spans democratic innovations, analyzing the integration of deliberative minipublics into mainstream politics, their policy impacts using frameworks like the Sequential Impact Matrix, and challenges in linking minipublics to broader governance systems. Key themes include citizen participation, climate change governance, and institutional ethics. Projects Postdoctoral Researcher, "Designing Democracy on Mars and Earth" (2023–2024) Teaching Assistant, Vrije Universiteit Brussel (2017–2023)

Jeffrey W. Ohlmannمشاهده پروفایل

دانشیار

• Operations Research
• Logistics
• Sports Analytics
• +۳ مورد دیگر

Jeffrey W. Ohlmann is an Associate Professor and Director of Graduate Studies in Business Analytics at the Tippie College of Business, University of Iowa. He holds a PhD in Industrial and Operations Engineering from the University of Michigan and a BS in Mathematics from the University of Nebraska-Lincoln. Research focuses on sequential decision making under uncertainty, logistics optimization, and sports analytics 2022 Master of Business Analytics Instructor of the Year recipient 2010 Strategic Innovation Faculty of the Year award winner His recent publications address stochastic vehicle routing, crowdshipping dynamics, and social media applications in sports recruitment. Ohlmann has received significant recognition for teaching excellence and has presented at international conferences including INFORMS and Metaheuristics International Conference. Key research areas: Operations Research, Logistics, Sports Analytics, Stochastic Programming, Dynamic Programming Applications in college football recruiting, delivery systems, and lean production

Anastasia Stuart-Edwardsمشاهده پروفایل

دانشیار

• Workplace Mindfulness
• Occupational Health
• Mental Health at Work
• +۲ مورد دیگر

Anastasia Stuart-Edwards is an Associate Professor at the Dhillon School of Business, University of Lethbridge, specializing in Human Resource Management & Labour Relations. Her research focuses on workplace mindfulness, occupational health, and mental health at work. Her recent work explores team mindfulness, reciprocal relationships in workplace mental health, multijobbing dynamics, and flow theory advancements. She employs interdisciplinary approaches spanning psychology, organizational science, and behavioral economics. Education: BA, PhD from the University of Manitoba (2019) Contact: a.stuartedwards@uleth.ca , (403) 317-5034

Lingzhong Guoمشاهده پروفایل

مدرس

• Signal Processing
• Biomedical Engineering
• Nonlinear Systems Identification
• +۳ مورد دیگر

Lingzhong Guo is a Lecturer in the Department of Automatic Control and Systems Engineering at the University of Sheffield , affiliated with the Insigneo Institute for in silico Medicine and Neuroscience Institute . His research bridges signal processing, nonlinear systems identification, and biomedical applications. PhD from Bristol Robotics Laboratory (UWE Bristol) Specializes in spatio-temporal system identification, PDE control, and machine learning for medical imaging Recent work focuses on deep learning applications for muscle segmentation in MR images and EIS analysis for oral disorder detection. Collaborations with Zilico Ltd. and participation in Horizon2020 projects highlight his translational research. Scientific Recognition SANO Centre grant (H2020, £2.5M) for computational diagnostics SPINe: Numerical and Experimental Repair strategies (H2020 European program, €1.58M) Innovate UK KTP for EIS-based medical diagnosis (£190K) His publications span nonlinear dynamics , multiscale modeling , and biomedical signal processing , with methodological contributions to Volterra series and coupled PDE-ODE systems.

• Pattern Mining
• Data Mining
• Machine Learning
• +۵ مورد دیگر

Dominique LI is a Professor in the Department of Computer Science at the University of Tours, affiliated with the Fundamental and Applied Computer Science Laboratory (LIFAT) and the Polytechnic School of the University of Tours (EPU). His research focuses on pattern mining, skyline computation, and data mining applications in domains like lithium-ion battery analysis and fluid mechanics. His recent publications highlight advancements in sequential pattern sampling, dynamic texture classification, and skyline maintenance for data streams. Keywords span Computer Science Machine Learning Database Systems Fluid Dynamics Text Classification Algorithm Design .

• Bayesian time series analysis
• forecasting
• finance
• +۴ مورد دیگر

Dr Kostas Triantafyllopoulos serves as Senior Lecturer in Statistics and MSc Statistics Course Director at the University of Sheffield's School of Mathematical and Physical Sciences. He joined Sheffield in February 2005 after academic positions at Newcastle University (2002-2004) and a post-doctoral appointment at Bristol University (2001-2002). His educational background includes: BSc in Mathematics from Aristotle University of Thessaloniki (1996) MSc in Quality Management from Napier University of Edinburgh (1998) PhD in Statistics from the University of Warwick (2002) Triantafyllopoulos specializes in Bayesian time series analysis and forecasting , with significant applications across finance, bioinformatics, medicine, signal processing, and quality control. His methodological innovations include multivariate stochastic volatility modeling using Wishart processes, real-time covariance estimation for state-space models, and particle filter applications for count time series. Recent work (2019-2022) demonstrates strong focus on medical decision making through flexible survival models and pandemic impact analysis using hybrid Bayesian-neural network approaches for shipping economics. Publication trends reveal a strategic evolution from foundational Bayesian state-space work (2006-2012) toward high-impact interdisciplinary applications. His 30+ journal articles show consistent emphasis on solving autocorrelation challenges in control charts, developing non-parametric monitoring systems for environmental data, and creating flexible parametric frameworks for survival data extrapolation in healthcare contexts. Research funding includes Nuffield Foundation support as Principal Investigator for "The multivariate general steady model" and EPSRC collaboration as Co-investigator on "Simulation Tools for Automated and Robust Manufacturing". He actively contributes to the Mathematical and Statistical Modelling research group, with current work bridging theoretical statistics and real-world industry/healthcare challenges.

Ismini Lourentzouمشاهده پروفایل

استادیار

• Multimodal Machine Learning
• Vision-Language Models
• Interactive AI Agents
• +۶ مورد دیگر

Ismini Lourentzou is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, leading the Perception and LANguage (PLAN) Lab. Her research focuses on multimodal machine learning, vision-language models, and human-centric embodied AI systems. School of Information Sciences, University of Illinois Urbana-Champaign Former Assistant Professor, Virginia Tech Department of Computer Science (2021-2023) Research Interests: Multimodal learning with limited supervision Interactive AI agents and human-agent communication Vision-language navigation and task-driven conversational systems Self-supervised learning and grounding vision-language models Applications in healthcare, misinformation detection, and manufacturing Scientific Contributions: Recipient of DARPA, NSF, and Amazon funding Developed frameworks for vision-language co-segmentation and embodied navigation Keynote speaker at ACM PETRA 2022 on supervision signals in healthcare AI Awards & Recognitions: Best Vice Co-Chair at IEEE BigData 2023 Outstanding New Assistant Professor at Virginia Tech IBM Invention Plateau Award (2019)

Kerstin Preuschoffمشاهده پروفایل

دانشیار

• Neuroeconomics
• Neurofinance
• Decision Making Under Risk
• +۴ مورد دیگر

Kerstin Preuschoff is an Associate Professor at the University of Geneva affiliated with the Geneva Finance Research Institute . Her interdisciplinary research bridges Neuroeconomics and Neurofinance , focusing on the neural mechanisms of decision-making under risk, integrating neuroscience , financial economics , and psychology . Education : PhD in Computation and Neural Systems & Neuroeconomics, California Institute of Technology Previous Affiliations : Researcher and Lecturer at University of Zurich and EPF Lausanne Her research explores how the brain computes subjective value, processes surprise, and balances new vs. old information during learning. She employs fMRI , computational models , and behavioral experiments to investigate risk prediction errors and neural correlates of decision-making. Key trends in her publications include interdisciplinary work on reinforcement learning , cognitive flexibility , and neuroeconomic theory , with a focus on brain regions like the insula and temporo-parietal junction . She has contributed to executive courses on Psychology of Finance and Neurofinance , and her academic presentations span conferences like The Brain Conferences and Neurofinance Meetings .

• Artificial Intelligence
• Decision Support Systems
• Uncertain Data Analysis
• +۳ مورد دیگر

Zeineb El Khalfi is a Teacher-researcher at CESI Bordeaux Campus specializing in artificial intelligence and decision support systems, with research focused on mobility/smart transport and uncertain data analysis. Her academic credentials include: Doctorate from Paul Sabatier University of Toulouse and Higher Institute of Management of Tunis (2017) on "Lexicographic refinement in possibilistic sequential decision-making" Research Master's from École Polytechnique de Nantes (2014) in Data Mining and Knowledge Management Research Master's from Higher Institute of Management of Tunis (2014) in Computer Science and Knowledge Management Her research bridges theoretical AI frameworks with real-world applications, particularly in possibilistic reasoning for decision-making under uncertainty. Early work centered on lexicographic refinements in Markov decision processes and possibilistic decision trees, evolving toward smart mobility solutions where she applies spatio-temporal forecasting to micro-mobility redistribution challenges. This trajectory demonstrates a strategic shift from foundational AI theory to transportation-focused implementations while maintaining core expertise in uncertainty modeling. Analysis of her 2016-2023 publications reveals consistent contributions to possibilistic AI (6 conference papers, 3 journal articles), with recent work emphasizing practical transportation applications through micro-mobility systems and data-driven urban mobility solutions. No information is available regarding student supervision or research grants in the provided materials. She actively contributes to CESI's Engineering and Digital Tools Research Team, leveraging interdisciplinary collaboration to advance smart transportation technologies through computational methods.

Ala Avoyanمشاهده پروفایل

دانشیار

• Microeconomic Theory
• Experimental Economics
• Behavioral Economics
• +۳ مورد دیگر

Ala Avoyan is an Associate Professor in the Department of Economics at Indiana University Bloomington, affiliated with the College of Arts & Sciences. Her research bridges microeconomic theory , experimental economics , and behavioral economics , focusing on attention allocation in strategic environments and communication mechanisms in games. B.Sc. in Mathematics, Tbilisi State University, Georgia M.A. in Economics, Tbilisi State University, Georgia Ph.D. in Economics, New York University, 2018 Her experimental work explores how attention influences decision-making in games, with recent studies on market design for digital platforms , information disclosure in crowdfunding , and teamwork under time constraints . She has published in top journals such as the American Economic Review and Management Science . Current projects include strategic uncertainty in sequential games and a meta-study of minimum effort game research. She also collaborates on interdisciplinary experiments involving communication, attention, and commitment mechanisms.

Annika Dixمشاهده پروفایل

عضو هیئت علمی

• Automotive Human Factors
• Human-Machine Interaction
• Cognitive Psychology
• +۸ مورد دیگر

Dr. Annika Dix is a research associate at the Chair of Automobile Engineering, TU Dresden, where since August 2023 she has been establishing the new research group for Automotive Human Factors. She previously held research positions at TU Dresden and the interdisciplinary Centre for Tactile Internet with Human-in-the-Loop (CeTI). Her expertise spans cognitive psychology, neuroscience, and human–machine interaction. Education & Training Diplom-Psychologin (equivalent to MSc Psychology), Humboldt-Universität zu Berlin, specializing in Cognitive and Neuropsychology Doctorate (Dr. rer. nat.), 2015, Humboldt-Universität zu Berlin & Berlin School of Mind and Brain, dissertation: “Count on the Brain: Using EEG Oscillations and Eye Movements to Disentangle Intelligent Problem-Solving in Math” Research Interests Dr. Dix investigates how human cognition—especially problem solving and decision making—interacts with complex technological environments. Her core themes include: Automotive Human Factors: driver behavior, autonomous vehicle acceptance, and technical supervision roles. Human-Machine Interaction: effects of feedback latency, multisensory augmentation, and interface design on motor skill learning. Cognitive & Neural Mechanisms: utilizing EEG, fNIRS, pupillometry, and drift-diffusion modeling to understand mathematical cognition, incentive motivation, and aging. Scientific Contributions & Trends Across 20 peer-reviewed works (2012-2025), Dr. Dix has progressively widened her focus from fundamental mathematical cognition toward applied challenges in cyber-physical and autonomous systems. Recent outputs emphasize ethical and social dimensions of robotics (robots giving moral advice, acceptance of robo-advisors) and the impact of system latency on fine motor performance in augmented reality and tactile internet environments. Teaching & Mentoring She currently coordinates teaching and study-program development for the Chair of Automobile Engineering. Earlier instructional activities at TU Dresden and Humboldt-Universität covered Cognitive Psychology, Embodied Cognition, Embodied AI, and teacher-training courses on child development. Labs & Teams Dr. Dix leads the nascent Automotive Human Factors research group at TU Dresden and actively collaborates with CeTI’s interdisciplinary consortium, integrating psychologists, engineers, and computer scientists to design human-centered tactile internet technologies.

Pınar Doğanمشاهده پروفایل

مدرس ارشد

• Industrial Organization
• Economics of Networks
• Regulation
• +۱ مورد دیگر

Pınar Doğan is a Senior Lecturer in Public Policy at Harvard Kennedy School, Harvard University. She holds a PhD in Economics and a Master's in Mathematical Economics from the University of Toulouse, France. Her academic roles include serving as Faculty Chair of the Master in Public Policy Program (2021-2023) and Associate Editor of Information Economics and Policy . Previous affiliations include visiting positions at the Institute for Advanced Study (Princeton), Télécom ParisTech, and Koc University. Her research centers on industrial organization, network economics, regulatory frameworks, and competition policy. Key themes include market incentives, digital innovation, telecommunications regulation, and strategic decision-making. Publications emphasize telecommunications regulation (e.g., fiber/copper transitions, broadband access), digital markets (e.g., music digitization, pricing models), and collaborative strategies (e.g., R&D joint ventures). Recurring topics include game theory applications, regulatory impacts on infrastructure investment, and competition in network industries. No scientific awards, grants, or student advising details are documented.

• Reinforcement Learning
• Machine Learning Theory
• Algorithms
• +۴ مورد دیگر

Ruosong Wang is an Assistant Professor in the Machine Learning Department within the School of Computer Science at Carnegie Mellon University. His research focuses on theoretical aspects of machine learning, particularly reinforcement learning, bandit problems, and algorithmic foundations. Wang's research interests span several key areas in theoretical machine learning. He has made significant contributions to reinforcement learning theory, particularly in understanding sample complexity, horizon dependence, and function approximation. His work on bandit algorithms explores variance-aware and sparse linear settings, while his research on subspace embeddings contributes to fundamental algorithmic techniques. Wang's approach combines rigorous theoretical analysis with practical implications for learning algorithms. His publication record shows a strong focus on theoretical guarantees and tight bounds for various learning problems. Wang's research demonstrates a progression from foundational algorithmic work to increasingly sophisticated analyses of reinforcement learning systems. His papers often address fundamental questions about the limits and possibilities of learning algorithms in complex environments. Wang has published extensively at top-tier machine learning and theoretical computer science venues including ICML, NeurIPS, ICLR, and STOC. His collaborative work with leading researchers in the field demonstrates his integration into the theoretical machine learning community. As an advisor and researcher, Wang contributes to advancing the theoretical foundations of machine learning, with particular emphasis on understanding the fundamental limits and possibilities of learning algorithms in sequential decision-making contexts.

• Applied Statistics
• Statistical Analysis
• Fuzzy Logic
• +۱ مورد دیگر

Zeynep GÖKKUŞ is a Lecturer at Kastamonu University , specifically within the Computer Programming Program of the Kastamonu Vocational School . She has held this full-time position since 2023, previously working at the same institution's Computer Technology and Programming Department in the İnebolu Vocational School from 2009 to 2021. Her academic career has been consistently focused on Applied Statistics and Statistical Analysis , with additional expertise in Fuzzy Logic and Biostatistics . PhD in Statistics from Ondokuz Mayıs University (2018) MSc in Mathematics from Kafkas University (2008) BSc in Mathematics from Atatürk University (2005) Research Interests : Her work spans Statistical Modeling for agricultural and aquacultural applications, including Fuzzy ANOVA , Cox Regression , and Group Sequential Testing . She has developed innovative approaches in Multi-Criteria Decision Making for environmental assessments and contributed to Nanofiber Synthesis and heavy metal removal studies. Article Trends : Her publications (2012–2025) show increasing focus on Fuzzy Logic integration with traditional statistical methods (ANOVA, AAS), alongside applications in Aquaculture Survival Analysis and Environmental Remediation . Recent works emphasize Circular Intuitionistic Fuzzy Control Charts and Geospatial Agricultural Quality Rankings . Scientific Impact : According to Google Scholar metrics, she has 10 citations and an h-index of 2 . Her research has been published in journals like Aquaculture (SCI) and Turk Tarım ve Doğa Bilimleri Dergisi (TR Dizin), with conference presentations at international events including INFUS 2023–2024 and the International Sport Sciences Congress.