جست‌وجوی استاد و پژوهشگر

Matteo Montecchiمشاهده پروفایل

مدرس ارشد

• Consumer Behaviour
• Digital Marketing
• Artificial Intelligence in Marketing
• +۱۲ مورد دیگر

Dr. Matteo Montecchi is a Senior Lecturer (Associate Professor) in Marketing at King’s Business School, King’s College London, where he also serves as Theme Lead for Sustainable Consumption at the Centre for Sustainable Business and Programme Director for the Strategic Marketing (Open Executive) programme. He teaches core modules such as Consumer Behaviour, Digital Marketing, and Research Methods, and leads executive education initiatives. Previously, he was a Senior Lecturer at the London College of Fashion, University of the Arts London, and has held visiting positions at Milan Politecnico, Università Cattolica del Sacro Cuore, and Università Federico II. Montecchi earned his PhD in Marketing from King’s College London, an MRes in Marketing from Birkbeck College, an Executive Master in Marketing and Sales from SDA Bocconi and ESADE, and a Bachelor’s in Business Economics from the University of Modena and Reggio Emilia. He also holds a PgCert in Academic Practice and is a Fellow of the Higher Education Academy (FHEA). His research focuses on the digital transformation of marketing, particularly the role of artificial intelligence and blockchain in enhancing transparency and trust. He investigates ethical engagement with diverse consumer groups, inclusion, and corporate responsibility, with a special interest in marginalized communities. His work integrates consumer behavior, digital interactions, and decision-making with technological innovation, offering actionable insights for sustainable and responsible business strategies. The most recent 15 publications reflect a strong trend in AI in retail, brand transparency, consumer trust, ethical data use, voice technologies, and social sustainability. His research spans journals in marketing, psychology, interactive marketing, and business ethics, demonstrating interdisciplinary impact. Scientific Awards: KingsCAT: Capture and Analysis Tool for Social Media Research at King’s College London (2024) – Recognized as part of a collaborative team for advancing digital research infrastructure and media analysis. Montecchi is actively involved in PhD supervision and is accepting new students. He has led research projects using social media analytics (KingsCAT) and has contributed to strategic debates on grand challenges in marketing. His work connects academic research with real-world managerial applications, particularly in digital strategy and ethical innovation. He is a key contributor to interdisciplinary research through tools like KingsCAT, which supports collaborative social media analysis, and his publications often involve co-authorship with experts in data science, psychology, and organizational behavior.

Hugues Aschardمشاهده پروفایل

پژوهشگر

• Statistical Genetics
• Genome-Wide Association Studies (GWAS)
• Microbiome Research
• +۷ مورد دیگر

Hugues Aschard is a Principal Investigator and Structure Manager at the Pasteur Institute in Paris, where he leads research in statistical genetics, microbiome analysis, and computational genomics. He is the principal investigator of the MicMat project, the EpiGenCOV Consortium, and several bioinformatics software initiatives including JASS, RAISS, and MGMM. Research Interests: Statistical and computational methods in genetics Genome-wide association studies (GWAS) Gene-environment interactions Microbiome and host genetics in inflammatory bowel disease Genetic epidemiology of infectious diseases like COVID-19 Development of open-source tools for multi-trait and summary-statistic analysis Recent Research Trends: His recent publications and projects emphasize integrative genetic modeling, multi-trait analysis across diverse populations, and the development of novel computational methods to handle missing data and improve SNP discovery. His work bridges statistical innovation with biological and clinical applications in complex diseases. Scientific Contributions: Development of JASS, RAISS, and MGMM software tools Leadership in large-scale consortia like EpiGenCOV Advancing methods for cross-ancestry genetic studies Advising and Collaboration: He supervises multiple PhD students and postdoctoral fellows, including Christophe Boetto, Antoine Auvergne, and Lucas Chataigner. He collaborates with major institutions such as APHP and CNRGH. His team includes research engineers and administrative staff, indicating an active and well-supported research group. Laboratories and Teams: He is a key member of the Biomaterials and Microfluidics team at the Pasteur Institute, where he contributes to interdisciplinary research involving Bayesian decision processes and genetic modeling.

• Wind Engineering
• Structural Engineering
• Cyclone and Windstorm Damage Assessment
• +۷ مورد دیگر

David Henderson is the Director of the Cyclone Testing Station (CTS) in the School of Engineering and Physical Sciences at James Cook University, Australia. He has over two decades of experience as a research engineer specializing in the performance of low-rise buildings under extreme wind conditions. He previously served as the CTS Research Fellow and Manager, and was seconded as a Postdoctoral Researcher at the University of Western Ontario, Canada, working on full-scale house testing under simulated wind loads. His work bridges engineering research, disaster assessment, and policy development. David's research focuses on wind engineering, structural resilience, and disaster mitigation. His key interests include cyclonic wind loading, internal and external pressure dynamics in buildings, fatigue failure of structural connections, and the vulnerability of housing to severe wind events. He has conducted post-disaster surveys across Australia and Canada, assessing damage from cyclones, tornadoes, and earthquakes. His research has direct applications in building codes, retrofitting strategies, and community risk reduction. The recent publications highlight a strong trend in understanding and mitigating wind-induced damage to residential structures, particularly through full-scale testing, modeling of pressure dynamics, and fragility assessment of roofing systems. His work spans experimental, theoretical, and policy-oriented domains, with a growing emphasis on climate change adaptation and community resilience. Topics such as internal pressure design, load sharing in roof frames, and retrofitting for wind resistance are central to his contributions. 14 research awards (specific names not listed) Active member of Standards Australia code committees Invited speaker at national and international conferences Media contributor on storm damage and building safety David has led multiple research projects funded by councils and agencies focused on extreme wind mitigation, data systems (SWIRLnet), and community risk reduction. While formal student supervision is not explicitly listed, he collaborates extensively with researchers such as John Ginger, Korah Parackal, and Daniel Smith. He has contributed to major studies involving wind load testing, housing vulnerability modeling, and climate adaptation planning. David is a key figure in the Cyclone Testing Station, leading its full-scale testing program and contributing to the development of software for controlled load and measurement systems. His team conducts wind risk assessments for communities and large installations, incorporating terrain analysis and retrofitting evaluations. The CTS serves as a national resource for wind engineering research and disaster resilience innovation.

James C. Geeمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Medical Imaging Computing
• Image Segmentation
• +۵ مورد دیگر

James C. Gee is a Professor of Radiologic Science in Radiology at the University of Pennsylvania's Perelman School of Medicine. He serves as Director of the Penn Image Computing and Science Laboratory and Co-Director of the Translational Biomedical Imaging Center , with affiliations in Bioengineering and Applied Mathematics graduate groups. His research focuses on biomedical image analysis, specialization in segmentation, registration, and morphometry applied to neurodegenerative diseases and multi-organ systems. Education : B.S. in Computer Science/Electrical Engineering (University of Washington, 1987), Ph.D. in Computer and Information Science (University of Pennsylvania, 1996) Research : Quantitative medical imaging methods, brain connectomics, neurodegeneration mapping, and translational imaging technologies Publications : 15+ recent works on AI-driven image analysis for Alzheimer's disease, cardiac amyloidosis, and radiomics applications Leadership : Directs MSE-DS Online Degree Program, co-chairs Radiology DCOAP Committee, and founded RISE (Radiology Initiative to Support Inclusive Excellence) His laboratory develops advanced computational tools like ITK-SNAP for biomedical imaging, with applications in both in vivo clinical imaging and ex vivo histology . The work spans cross-disciplinary collaborations in computer science, neuroscience, and clinical medicine.

• Artificial Intelligence
• Collective Intelligence
• Digital Strategy
• +۷ مورد دیگر

Overview Prof. Harris Kyriakou is an Associate Professor and Chair Holder of the Media & Digital Chair at ESSEC Business School. His research focuses on leveraging artificial and collective intelligence to enhance organizational value creation, digital strategy, and data-driven decision-making. He has advised multinational firms like Airbnb, Facebook, and Yelp, and his work is supported by grants from NSF and the Spanish government. Education Ph.D. in Management Sciences (Stevens Institute of Technology, 2016) M.S. in Engineering & Technology Innovation Management (Carnegie Mellon University, 2010) B.Sc. in Digital Systems (University of Piraeus, 2007) Research Focus His research explores intersections between AI/collective intelligence, blockchain, sharing economy regulations, and platform governance. Key themes include data network effects, algorithmic regulation, and digital transformation. Recent work on ChatGPT vs. Google examines AI-driven competitive dynamics in search markets. Recognition Awarded the 2024 Case Centre Triple Award, 2022 Early Career Award (AIS), and multiple best paper awards (AoM, INFORMS). Recognized as a 40-Under-40 MBA Professor by Poets & Quants. Teaching & Leadership Co-leads the 'Algorithmic Governance in Platform Economy' thesis Teaches courses on AI, digital strategy, and IT management at ESSEC and IESE Former Assistant Professor at IESE Business School (2016–2021) Professional Contributions Serves as a European Commission advisor on digitalization, reviewer for top journals (MIS Quarterly, Academy of Management Review), and mentor for doctoral candidates.

Anna Mayoمشاهده پروفایل

استادیار

• Organizational Behavior
• Team Dynamics
• Dynamic Teams
• +۳ مورد دیگر

Anna Mayo is the Anna Loomis McCandless Assistant Professor of Organizational Behavior at Carnegie Mellon University’s Heinz College. Her research focuses on dynamic teamwork in modern organizations, particularly in healthcare and cross-sector settings. She investigates how teams adapt to fluid participation, technology integration, and volatile environments to enhance productivity and collaboration. Education: Ph.D. & M.S. in Organizational Behavior & Theory, Carnegie Mellon Tepper School of Business B.A. in Psychology, Denison University Research Interests: Mayo explores team coordination, cognitive versatility, and the impact of organizational structures on teamwork efficacy. She combines lab and field studies (e.g., healthcare, sales teams) to address challenges like rapid team formation/dissolution and distributed member roles. Her work emphasizes agility while mitigating risks to team outcomes. Publications: Her research appears in top journals such as Administrative Science Quarterly, Academy of Management Annals, and BMJ Leader. Recent studies address pandemic teamwork dynamics, nursing-physician collaboration, and the role of coordinated attention in group performance. Prior Experience: Before joining CMU, Mayo held roles at Johns Hopkins Carey Business School and worked in nonprofit human services. She teaches Organizational Design & Implementation (Course 94-700).

• Compact and reconfigurable antennas
• Antenna arrays
• Microwave components
• +۷ مورد دیگر

Dimitrios E. Anagnostou is Associate Professor in the Institute of Sensors, Signals & Systems within Heriot-Watt University’s School of Engineering & Physical Sciences, Edinburgh. He directs an anechoic-chamber & microwave characterisation facility, leads a thriving research group, and is currently recruiting PhD candidates. Education & Career: BSEE, Democritus University of Thrace, Greece (2000) MSEE, University of New Mexico, USA (2002) PhD, University of New Mexico, USA (2005) Post-doc, Georgia Tech (2005-2006) Assistant → tenured Associate Professor, South Dakota School of Mines & Technology (2007-2016) Associate Professor, Heriot-Watt University (2016-present) Research Focus: His work spans compact & reconfigurable antennas, 5G Massive-MIMO arrays, metasurfaces, metamaterials, functional materials (VO 2 ), RF-MEMS, microwave packaging, radar sensing for assisted-living, and AI/deep-learning applications in electromagnetics. He pursues “green” RF electronics printed on paper/organic substrates and hybrid integration of antennas on solar cells. Recent Publication Trends (2022-2025): Output is dominated by metasurface-enabled beam-steering antennas, VO 2 -based reconfigurable devices, radar absorbers/rasorbers, biomedical radar for vital-sign monitoring, and AI-assisted signal processing, with strong emphasis on experimental validation and open-access dissemination. Scientific Awards & Fellowships: IEEE John D. Kraus Antenna Award DARPA Young Faculty Award Marie Skłodowska-Curie Individual Fellowship (H2020) ASEE Campus Star Award Young Alumni Award, University of New Mexico Honored Faculty Award, SDSMT (×4) Distinguished Scientist Living Abroad, Hellenic Ministry of Defense Advising & Grants: He has mentored numerous PhD and MSc researchers; his students have won Best PhD Thesis and faculty-wide Engineering Prizes. He is supported by EU and UK research grants and continuously seeks motivated doctoral applicants. Facilities & Teams: He manages the Microwave Facility (anechoic chamber, mm-wave measurement systems) and collaborates with international academic/industry partners across Europe, North America and beyond.

• Creative Technology
• Internet of Things
• Open Hardware
• +۲ مورد دیگر

Jon Rogers is Professor of Creative Technology at Northumbria University with a PhD in neural networks from Imperial College London. His research examines human relationships with emerging technologies through hands-on making and critical design practices. Rogers' work explores alternative narratives for digital futures through internet-connected objects and open hardware systems. He develops tangible interfaces that challenge conventional technology design paradigms and enable public participation in technological discourse. Recent research includes experimental prototyping platforms for open hardware development and methodological frameworks for reflecting on connected devices. His publications document innovative approaches to tangible computing and participatory design methodologies. Rogers founded the OpenDoTT doctoral training program exploring trust in IoT systems. He regularly organizes workshops at major technology conferences and maintains collaborations with international makerspaces and research institutions.

Miklós Korenمشاهده پروفایل

استاد

• International Trade
• Economic Development
• Productivity Analysis
• +۵ مورد دیگر

Miklós Koren is a Professor of Economics at Central European University and Senior Research Fellow at the HUN-REN Centre for Economic and Regional Studies. His work bridges international trade , economic development , and managerial economics , focusing on trade policy, productivity spillovers, and the role of managers in development. Ph.D., Harvard University (2005) M.A., Central European University (2000) M.Sc., Budapest University of Economics (1999) His research explores trade facilitation , managerial impact on firm performance , and technological diversification . Recent work includes studies on expatriate managers, pandemic-related business disruptions, and the legacy of communist-era management practices. Key trends in his publications (2020–2024) emphasize managerial mobility and firm productivity (2024) machine learning vs. gravity models (2024) trade volatility and development (2023) data transparency standards (2022) Scientific awards include ERC Starting Grant (2012) Nicholas Káldor Prize (2014) Young Economist Award (2002, 2004) As Data Editor for Review of Economic Studies and Associate Editor for Journal of International Economics , he shapes methodological rigor in empirical research. His 2013 paper on technological diversification remains foundational for understanding volatility in developing economies.

Matt Nowinskiمشاهده پروفایل

دانشیار

• Aerospace Engineering
• Asteroid Dynamics
• Machine Learning
• +۵ مورد دیگر

Matt Nowinski is a Collegiate Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. His professional roles include advisory board memberships and leadership positions within the department. He holds multiple degrees including a Ph.D. in Mechanical Engineering from ETH Zurich (1999), an M.S. in Computer Science from Syracuse University (2022), and prior mechanical/aerospace engineering degrees from Virginia Tech. His research focuses on asteroid dynamics (particularly D-type and V-type asteroids), gas turbine engines, aeroelasticity, and education technology. Notable areas include lightcurve analysis, surface mineralogy modeling, and machine learning applications in astronomy. His work bridges aerospace engineering with astrophysics, leveraging both experimental and computational methods. Dr. Nowinski has over 24 years of industry experience as a Boeing subject matter expert in military communications systems, complemented by academic roles at George Mason University and University of Chicago. He is a recipient of the John Jones Faculty Fellowship and Society of Distinguished Alumni honor. His research contributions span asteroid characterization, turbine blade flutter mechanisms, and telescope instrumentation. Current work emphasizes observational astronomy through the Stone Edge Observatory and Slack-based collaborative platforms. He actively contributes to advancing STEM education through innovative curricula and research integration.

• Clinical Informatics
• Emergency Medicine
• Electronic Health Records
• +۵ مورد دیگر

Mark Iscoe, MD, MHS is an Assistant Professor of Emergency Medicine and Biomedical Informatics and Data Science at Yale School of Medicine. He holds fully joint appointments in both the Department of Emergency Medicine and the Department of Biomedical Informatics & Data Science, reflecting his interdisciplinary work at the critical intersection of clinical emergency care and health informatics innovation. Dr. Iscoe completed his medical degree at Johns Hopkins University School of Medicine in 2017, followed by residency training in Emergency Medicine at New York University / Bellevue Hospital in 2021. He further specialized with a Master of Health Science (MHS) in Clinical Informatics from Yale School of Medicine in 2023. He is board certified in both Emergency Medicine (2022) and Clinical Informatics (2024). His research spans several interconnected domains with a focus on optimizing the interface between emergency physicians and health information technology. Key areas include electronic health record (EHR) optimization, artificial intelligence applications in emergency settings, clinical decision support systems, and medication safety protocols. His 2024 JAMA Network Open publication 'Benchmarking Emergency Physician EHR Time per Encounter Based on Patient and Clinical Factors' represents a significant contribution to understanding the digital burden on emergency clinicians. More recently, he has pioneered work applying large language models to emergency medicine challenges, with multiple 2025 publications on AI applications for deprescribing, symptom identification, and risk stratification. His research trajectory shows a clear evolution from foundational EHR usage studies toward increasingly sophisticated AI implementations that bridge theoretical informatics with practical clinical tools in high-pressure emergency settings. YCCI Scholar Award for AI Research on Drug Reactions (2024) Dr. Iscoe has received research funding from multiple prestigious sources including the National Institute on Drug Abuse (NIDA), the American Medical Association (AMA), the National Institutes of Health, and Yale New Haven Health System. His collaborative network includes prominent researchers such as Andrew Taylor (6 joint publications), Ted Melnick (5 joint publications), and Rohit Sangal (4 joint publications), reflecting his work's multidisciplinary nature spanning clinical departments, informatics specialists, and data scientists.

• Information Systems
• Model-Driven Engineering
• Requirements Engineering
• +۲ مورد دیگر

Alberto Rodrigues da Silva is a Professor at the Institute Superior Técnico , part of the University of Lisbon . He teaches Fundamentals of Information Systems , primarily during the 1st Semester of the 2025/2026 academic year. His scientific interests revolve around Information Systems , Model-Driven Engineering (MDE), Requirements Engineering (RE), Social Computing , and Software Engineering . He has extensively contributed to the development of rigorous requirements specification languages like RSL (Requirements Specification Language) and its extensions (e.g., RSL-IL4Privacy for privacy policies). His collaborative work spans automated acceptance testing, GDPR compliance, and domain-specific languages (DSLs) for applications such as mobile development , digital twins , and legal contexts (e.g., LegalLanguage ). His research trends focus on integrating model-driven engineering with privacy policies , IoT applications , and low-code platforms . He has also explored tools like Maestro for data classification and usability testing, and RiverCure for flood simulation. Email: alberto.silva@tecnico.ulisboa.pt .

Barbara Drosselمشاهده پروفایل

استاد

• Complex Systems Theory
• Theoretical Ecology
• Random Boolean Networks
• +۷ مورد دیگر

Barbara Drossel is a Full Professor at the Institute of Solid State Physics within the Faculty of Physics at the Technical University of Darmstadt, where she has been conducting research since February 2002. Her work bridges theoretical physics, complex systems theory, and theoretical ecology, focusing on interdisciplinary approaches to understanding emergent phenomena in natural systems. She leads the AG Drossel research group that investigates the theoretical foundations of complex networks, ecological communities, and quantum systems. Professor Drossel's research spans multiple domains with emphasis on complex systems theory, where she has made significant contributions to understanding random Boolean networks, food web modeling, and the physics of ecological communities. Her work demonstrates how simple rules can lead to complex emergent behavior across different scales, from quantum systems to ecological networks. She investigates how top-down causation operates in complex systems and explores the relationship between microscopic dynamics and macroscopic patterns in diverse contexts. Analysis of her recent publications reveals a consistent focus on theoretical frameworks that connect physics with ecology. Her work shows increasing integration of quantum mechanics with ecological modeling, particularly in understanding emergence and time evolution in complex systems. She frequently employs network theory to analyze ecological communities and has developed innovative approaches to studying species interactions, mutualistic networks, and spatial dynamics in meta-communities. Minerva Fellowship Heisenberg Fellowship DFG Fellowship for research at MIT Professor Drossel has supervised numerous doctoral students whose work spans theoretical ecology, complex systems, and statistical physics. Her research group has secured funding for projects examining the stability of ecological networks, quantum decoherence, and the mathematical foundations of complex systems. She maintains active collaborations with researchers across Europe and has contributed to major theoretical advances in understanding how complexity emerges from simple interactions in diverse systems. The AG Drossel research group operates at the intersection of physics and theoretical biology, maintaining strong connections with both the physics and biology departments at TU Darmstadt. The group combines mathematical rigor with biological relevance, developing models that capture essential features of complex natural systems while remaining analytically tractable. Their work has influenced both theoretical physics and ecological theory, demonstrating the power of interdisciplinary approaches to complex systems.

Andrea Burattinمشاهده پروفایل

دانشیار

• Process Mining
• Business Process Management
• Petri Nets
• +۶ مورد دیگر

Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.

Kelly Bennionمشاهده پروفایل

دانشیار

• Emotional Memory
• Sleep and Memory
• Stress and Memory
• +۳ مورد دیگر

Kelly Bennion serves as an Associate Professor in the Psychology and Child Development Department at California Polytechnic State University. Her research examines how real-life variables—such as emotion, stress, physiological arousal, and sleep—affect memory encoding and consolidation using behavioral experiments, eye tracking, polysomnography, and neuroimaging. She investigates how sleep selectively enhances memories for emotionally salient or future-relevant information in ecologically valid contexts. (78 words) Her educational background includes: Ph.D. and M.A. in Psychology (Cognitive Neuroscience concentration) from Boston College Ed.M. in Mind, Brain, and Education from Harvard Graduate School of Education B.A. in Psychology and Spanish (summa cum laude, Phi Beta Kappa) from Middlebury College Dr. Bennion's work focuses on memory prioritization mechanisms during sleep-wake cycles, particularly how emotional arousal and physiological stress modulate consolidation. She explores real-world applications including educational strategies and mental health interventions, emphasizing the interaction between cortisol levels and sleep-dependent memory processing. Her multi-method approach bridges laboratory findings with naturalistic memory phenomena. (92 words) Analysis of her 2020-2025 publications reveals three dominant research streams: (1) sleep's role in enhancing emotional and future-relevant memories through selective consolidation, (2) cross-episode memory integration via semantic relatedness and surprise mechanisms, and (3) interdisciplinary extensions into public health (postpartum interventions) and environmental toxicology (bisphenol A effects). Her methodology increasingly combines behavioral metrics with physiological monitoring to capture memory dynamics in complex scenarios. (68 words) Dr. Bennion actively mentors undergraduate researchers, evidenced by student co-authorships on publications including Jackson (2019) on school shooter perceptions. While specific grant details aren't provided, her sophisticated research infrastructure implies substantial external funding. She teaches core psychology courses including Research Methods, Biopsychology, and Memory, emphasizing hands-on methodology training. Her laboratory maintains advanced capabilities for sleep monitoring, eye tracking, and neuroimaging to investigate memory consolidation across physiological states. (76 words)