جست‌وجوی استاد و پژوهشگر

Eduardo José dos Foros Santos Gonçalvesمشاهده پروفایل

استادیار

• Sustainability
• Industrial Design
• Lighting Design
• +۸ مورد دیگر

Eduardo José dos Foros Santos Gonçalves is an Assistant Professor in the field of Design at Universidade Europeia, with a PhD in Design. He has been affiliated with IADE-Universidade Europeia since 2003, contributing to design education and research, and is a full member of the UNIDCOM research unit, where he served as Executive Director from 2018 to 2021. His work bridges academic research and practical applications in design, particularly focusing on sustainability and human-centered approaches. PhD in Design (2016, Faculty of Architecture of Lisbon) Master in Urban Design (2006, Universitat de Barcelona) Bachelor in Industrial Design (2000, IADE) His research spans multiple disciplines, emphasizing Sustainability , Industrial & Lighting Design , and the integration of Machine Learning and Robotics into design practices. He explores how Environmental Psychology and Design for Behaviour Change can shape sustainable solutions, and his work often involves Analogue and Digital Modelling for prototyping and Statistics in design analysis. Recent publications highlight his focus on crisis resilience, such as the 2023 Shelter Project for earthquake survival, and the 2022 study on Virtual Reality in design education. His 2021 papers address gender-neutral toy design and kitchen-based food waste reduction, reflecting his commitment to Design for Social Change and Sustainable Innovation . Earlier works (2019, 2017) explore ideation techniques and public lighting, respectively. He has supervised several Master’s and PhD students, including Neves Pimenta (2022) on kitchen sustainability and Dos Santos (2018) on creativity metrics. Active in academic governance, he participates in international conference committees and serves on the editorial board of DISCERN Journal , promoting design-driven sustainable solutions.

Robert L Lastمشاهده پروفایل

استاد

• Plant Biochemistry
• Specialized Metabolism
• Plant Resilience
• +۴ مورد دیگر

Robert L Last is a University Distinguished Professor in the Department of Biochemistry & Molecular Biology and holds the Barnett Rosenberg Chair in Plant Biology at Michigan State University. His research focuses on plant specialized metabolism, particularly in biosynthetic pathway regulation, with applications to food security and plant resilience. Education: Ph.D. in Biological Sciences from Carnegie-Mellon University (1986), B.A. in Chemistry from Ohio Wesleyan University (1980) Research interests include: Chloroplast-targeted protein function discovery through phenomics Specialized metabolite pathways in secretory glandular trichomes Systems biology approaches to plant metabolic networks Evolutionary origins of plant-specialized metabolism Genomics-driven improvements in plant nutritional and stress response Development of analytical chemistry techniques for metabolite profiling Recent publications highlight: Metabolic innovations in plant stress response (2025) Evolutionary mechanisms of biochemical pathway diversification (2024) Key enzyme discoveries in specialized metabolite production (2024) Gene cluster evolution across Solanaceae species (2022) Scientific awards include: 2017 Postdoctoral Mentor Award, MSU College of Natural Science 2012 Distinguished Faculty Award, MSU 2009 Fellow of American Association for the Advancement of Science 2009 Fellow of American Society of Plant Biologists 1990 NSF Presidential Young Investigator Award He leads the Last Lab , which collaborates with institutions like University of Arizona and University of Michigan on plant metabolism research. Current projects include NSF-funded Chloroplast Phenomics and Plant Specialized Evolution initiatives, utilizing advanced genomics and mass spectrometry techniques.

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +۳ مورد دیگر

William Henrich Due serves as a Lecturer at the Department of Computer Science (DIKU), University of Copenhagen, within the Machine Learning section. His work intersects with the SCIENCE AI Centre and leverages the department's high-performance compute cluster for research in quantum computing, sustainable AI, and medical applications. Research focuses span quantum machine learning (biomolecular simulations, photonic processors), sustainable AI systems (energy efficiency, climate impact), and clinical applications (EEG analysis, medical imaging). His recent publications reveal strong activity in quantum-classical hybrid systems, with 8/15 recent papers addressing quantum computing challenges. The work emphasizes practical implementations in medical imaging and resource-constrained environments. His research aligns with DIKU's Machine Learning section priorities including medical imaging biomarkers and sustainable computing. Key infrastructure includes TreeSense for remote sensing and the department's dedicated compute cluster. No scientific awards were explicitly documented in the provided materials. Due contributes to DIKU's teaching mission as a Lecturer while engaging with the SCIENCE AI Centre's interdisciplinary initiatives. His work connects with medical imaging applications and quantum computing infrastructure development. Active in the Machine Learning section's research ecosystem, his work intersects with medical imaging analysis and quantum computing applications, utilizing specialized resources like TreeSense for environmental monitoring.

• Information Retrieval
• Machine Learning
• Evaluation
• +۴ مورد دیگر

Maria Maistro is a Tenure Track Assistant Professor at the Department of Computer Science, Faculty of Science, University of Copenhagen. Her research focuses on Information Retrieval (IR) with emphasis on evaluation, reproducibility, click log analysis, learning to rank, expert search, and machine learning applications to IR. She contributes to the AMAOS project aiming to advance expert search methodologies. PhD in Computer Science (IR) from University of Padua (2017) MSc in Mathematics (probability, stochastic methods) from University of Padua (2014) Maria's research addresses critical challenges in IR evaluation through stochastic modeling and user signal analysis. She investigates fairness-relevance tradeoffs in recommender systems, cross-cultural retrieval frameworks, and explainability techniques for language models and recommendation algorithms. Her work combines theoretical foundations with practical applications in healthcare records, insurance domains, and culinary contexts. Recent publications (2024–2025) demonstrate her expertise in: Retrieval-Augmented Generation (RAG) for cross-cultural adaptation Fairness evaluation in recommender systems EEG-based semantic relevance analysis Session-based recommendation explainability Language model pruning consistency Reproducibility frameworks for IR experiments Maria actively participates in academic activities through conference organization roles, including: Organizer, CENTRE@CLEF 2019 Organizer, CENTRE@NTCIR 2019 Organizer, CENTRE@CLEF 2018 Organizer, LEARNER 2017

Pei-Hsun Hsiehمشاهده پروفایل

پژوهشگر

• Political Economics
• Political Psychology
• Climate Change Policy
• +۴ مورد دیگر

Pei-Hsun Hsieh is a Postdoctoral Researcher at the University of Pennsylvania, focusing on political and social behavior in democratic societies. They hold a Ph.D. in Political Science from Stony Brook University (2023) and specialize in examining public perceptions of government influence, electoral behavior, and policy support for inequality and climate change mitigation. Doctoral Degree: Political Science, Stony Brook University, 2023 Dr. Hsieh combines theory-driven and data-driven methodologies, including natural language processing, statistical modeling, economic games, and agent-based simulations. Their work explores the intersection of political economy, social norms, and environmental policy through large-scale social media analysis and behavioral experiments. Key research trends include analyzing how crises like pandemics affect climate change discourse, redistributive preferences under merit-based systems, and the role of emotions in policy debates. Publications span journals like PNAS, Journal of Environmental Psychology, and Humanities and Social Sciences Communications. Teaching includes Computational Text Analysis for Social Sciences , covering machine learning and NLP techniques. Current projects investigate plant-based diets as climate solutions, sanction effectiveness in international politics, and the dynamics of norm strength in cooperative settings. Affiliated with the Center for Social Norms and Behavioral Dynamics and the Philosophy, Politics, and Economics program at UPenn, they apply computational methods to understand political behavior, policy preferences, and institutional trust.

• Game Technology
• Game Design
• Serious Games
• +۷ مورد دیگر

Professor Remco Veltkamp holds a faculty position at Utrecht University's Faculty of Science with a focus on Game and Media Technology . As Scientific Director of AI Labs and coordinator of the Utrecht Center for Game Research , his work bridges serious games, virtual reality, and human-centered AI applications. He leads the Dynamics of Youth Hub 'Healthy Play, Better Coping' exploring gaming's role in pediatric chronic illness management. Academic leadership in gaming technology Director of Utrecht's AI Labs Founder of Serious Game Society Editor of International Journal of Serious Games Research spans game design, AR/VR interaction, 3D object recognition, and multimedia systems with applications in: Healthcare gamification Energy conservation Bioinformatics Social behavior analysis Computer vision Recent work includes: 2025: Developing fatigue management therapy games 2024: Analyzing protest dynamics through social media 2023: Creating equine pain assessment systems 2022: Gamification in food sustainability As educator, he teaches Game Programming and Small Project Game and Media Technology , while pioneering applications of gaming in healthcare and education sectors.

• Industrial metrology
• Instrumented indentation test
• Performance measurement systems
• +۵ مورد دیگر

Maurizio Galetto serves as Full Professor and Director of the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin. He holds multiple leadership positions including membership in the Academic Senate, Regulations Commission, and University Committee for Research, Technology Transfer and Services to the Territory. His academic career spans decades of teaching in quality engineering, mechanical measurements, and production systems across bachelor's, master's, and doctoral programs. Professor Galetto's research focuses on industrial metrology, instrumented indentation testing, performance measurement systems, quality engineering, and technological surface characterization. His work bridges theoretical metrology with practical industrial applications, particularly in manufacturing technologies and systems. His research intersects with key Sustainable Development Goals including Quality Education, Industry Innovation, and Responsible Consumption and Production. His publication record from 2023-2025 reveals strong emphasis on surface characterization techniques, quality control systems in manufacturing, collaborative robotics applications, and sustainable production methods. The research demonstrates consistent application of metrology principles to solve real-world industrial problems across diverse sectors including automotive, electronics, food processing, and additive manufacturing. Professor Galetto actively supervises PhD students working on quality engineering applications, with current research focusing on sustainable agri-food processes, collaborative robotics in quality control, and digital traceability systems. His research group has secured significant funding through competitive tenders, EU projects, and commercial contracts with major industrial partners including Electrolux and Lavazza. His laboratory work centers around the Quality Engineering research group (DIGEP), with special focus on metrology systems, surface characterization, and quality control methodologies. The research integrates advanced measurement techniques with statistical process control and digital twin technologies for enhanced manufacturing quality assurance.

• Animal Welfare
• Veterinary Ethics
• Farmed Animal Welfare
• +۵ مورد دیگر

Siobhan Mullan is a Professor at the School of Veterinary Medicine, University College Dublin. A veterinary surgeon who transitioned from clinical practice to research and teaching, she focuses on delivering large-scale, long-term improvements in animal welfare. She serves on the Farmed Animal Welfare Advisory Committee (FAWAC) and the Advisory Council on Companion Animal Welfare (ACCAW), influencing national policy. Her educational background includes a PhD from the University of Bristol. As a foundation diplomate of the European College of Animal Welfare and Behavioural Medicine (AWSEL sub-speciality), she ranks among only 120 EU-recognized veterinary specialists in this field. Mullan's research centers on developing valid methodologies to assess animal welfare that drive large-scale improvements across multiple species. Her work spans: Farmed animal welfare assessment methodologies Companion animal ethics and welfare Racehorse welfare in training and post-racing careers Veterinary ethics through her 'Everyday Ethics' column and co-authorship of 'Veterinary Ethics- Navigating Tough Cases' Her recent publications reveal a focus on practical welfare assessment tools across diverse species, from cattle and pigs to racehorses and companion animals. She has pioneered innovative approaches including machine vision monitoring for dairy welfare and ethical frameworks for animal welfare labeling, often bridging traditional welfare science with cutting-edge technology. Her scientific recognition includes being a foundation diplomate of the European College of Animal Welfare and Behavioural Medicine. Her policy influence extends through FAWAC and ACCAW memberships, where she helps shape animal welfare standards. Mullan supervises PhD students and has led significant projects including the AssureWel project and the Christian Ethics of Farmed Animal Welfare funded by the Arts and Humanities Research Council. Her collaborative approach spans multiple disciplines, working with industrial partners to integrate welfare outcome assessments into farm assurance schemes, delivering documented benefits for over 2 million farm animals annually. Her research team develops welfare assessment protocols emphasizing both scientific validity and practical implementation. She champions multi-disciplinary collaborations that combine animal welfare science with ethics, policy development, and technological innovation to create meaningful improvements in animal lives.

• Computational Fluid Dynamics
• Chemical Engineering
• Porous Media
• +۷ مورد دیگر

Gianluca Boccardo is an Associate Professor at the Department of Applied Science and Technology (DISAT) at Polytechnic University of Turin, where he conducts research at the intersection of computational fluid dynamics, deep learning, and porous media applications. His work bridges theoretical chemical process development with practical industrial applications in energy systems and sustainable engineering. His research interests span multiple domains of engineering and computational science: Computational Fluid Dynamics for complex engineering systems Deep learning applications in chemical process modeling Multiscale modeling of transport phenomena in porous media Energy processes engineering and sustainable technologies Fluid mechanics applications in industrial contexts Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional computational methods to solve challenging problems in chemical engineering. His work particularly focuses on applying these hybrid approaches to porous media systems, pharmaceutical processes, and energy storage technologies, demonstrating a commitment to both theoretical advancement and practical industrial application. Professor Boccardo actively supervises numerous PhD students working on cutting-edge research topics and leads significant research initiatives including the MULTIPHASE Erasmus Mundus Joint Master program and the BATCAT Battery Cell Assembly Twin project. His research group receives funding from both competitive EU grants and commercial contracts with industry partners. He is an active member of the Molecular Engineering Lab (MolE) and the Multiscale Modeling research group at DISAT, where his team develops innovative approaches to modeling complex chemical processes and developing sustainable engineering solutions.

David Swainمشاهده پروفایل

استاد مدعو

• Behavioral Ecology
• Livestock Management
• Sensor Networks
• +۴ مورد دیگر

David Swain is an Adjunct Professor at CQUniversity within the School of Health, Medical and Applied Sciences, affiliated with the Institute for Future Farming Systems. His research focuses on the behavioral ecology of livestock in extensive production systems, particularly how behavioral strategies address resource limitations. He holds a PhD in Ecology and has extensive experience, including roles as Senior Research Scientist at CSIRO and Honorary Lecturer at the University of Glasgow. Swain’s research interests include automated monitoring of animal behavior, sensor networks, and precision livestock management. He has contributed to developing technologies like virtual fencing and sensor-based calving detection systems. His work emphasizes integrating environmental drivers with livestock behavior to improve management practices. Key awards include the Queensland Science Champion (2014) and the iAward for Virtual Fencing Technology. His publications span 30+ years, covering topics like cattle behavior, sensor applications, and livestock health. He has coordinated courses such as AGRI12006 and AGRI12003, focusing on livestock industry analysis and leadership. Swain’s current research trends highlight machine learning applications in livestock management, sensor-driven behavioral analysis, and sustainable farming practices. His work bridges technological innovation with ecological principles to enhance agricultural efficiency and animal welfare.

Reza Khanbilvardiمشاهده پروفایل

استاد

• Climate Impact and Adaptation
• Hydrology and Remote Sensing
• Water Resources Engineering
• +۳ مورد دیگر

Dr. Reza Khanbilvardi is a Professor of Civil Engineering at The City College of New York (CCNY), CUNY. He serves as the Executive Director of the CUNY Remote Sensing of the Earth Institute and co-Executive Director of the United Nations University Hub (R-SIRUS). His leadership roles include founding and directing NOAA Cooperative Science Centers (CREST/CESSRST) from 2001-2021. He holds advanced degrees from Penn State University and has led over $100M in research grants from agencies like NOAA, NASA, and NSF. Dr. Khanbilvardi's research focuses on satellite-based remote sensing applications in hydro-climate studies, including flood modeling, climate change impacts, and water resources management. His work integrates machine learning, hydrological modeling, and geospatial technologies. Notable contributions include urban flood prediction systems for NYC, disaster resilience frameworks, and validation of snow/precipitation models. He has authored over 220 peer-reviewed publications, edited five books, and holds professional engineering licenses in NY/CT. He leads interdisciplinary initiatives like the CREST-SAFE field experiments and the UNU-Hub's socio-technical research on critical infrastructure resilience. His education initiatives include training programs for underrepresented STEM students through NOAA-funded partnerships. Labs/Teams: CUNY-CREST Institute, UNU-Hub R-SIRUS, Earth System Science & Environmental Engineering Program.

Kuanchin Chenمشاهده پروفایل

استاد

• Artificial Intelligence
• Business Analytics
• Data Mining
• +۷ مورد دیگر

Kuanchin (KC) Chen is the Upjohn Chair of Business Administration and Professor of Business Information Systems at the Haworth College of Business, Western Michigan University, where he also directs the Center for Business Analytics. His expertise spans artificial intelligence, business analytics, electronic business, and privacy/security in digital environments. Dr. Chen earned a D.B.A. in Information Systems from Cleveland State University, an M.S. from the University of Colorado, and a B.B.A. from Tunghai University. He is an award-winning researcher and educator, recognized for contributions to trust in technology, data-driven decision-making, and interdisciplinary applications of AI. Research interests include AI ethics, social media analytics, consumer trust dynamics, and human-AI collaboration. He has published extensively in top journals and serves in editorial leadership roles. Notable accolades include the MAC Outstanding Faculty Award for Student Success and multiple Excellence in Research awards. Dr. Chen has delivered over 70 academic and industry talks globally, focusing on bridging technical and behavioral aspects of technology adoption. Education: D.B.A., Information Systems, Cleveland State University M.S., Information Systems, University of Colorado B.B.A., Tunghai University Awards: Upjohn Chair of Business Administration (2025) John W. Snyder Faculty Fellow (2017–present) U.S. Fulbright Specialist (2019–2024) His work emphasizes practical applications of analytics and AI, particularly in workforce upskilling through human-AI symbiosis. Active in editorial roles, he co-edits academic book series and journals. Dr. Chen’s teaching portfolio includes AI, data mining, project management, and software development. Research and advisory work focuses on trust, privacy, and digital transformation across sectors. The Center for Business Analytics under his leadership advances data-driven strategies for organizations.

• Computational imaging
• Image processing
• Computer Vision
• +۳ مورد دیگر

Rudi Bartels is a Research Fellow in the Department of Electrical and Electronic Engineering within the School of Engineering and Built Environment at Griffith University. He is also a member of the Institute for Integrated and Intelligent Systems (2016-2024) and works at the Nathan Campus in office N66 1.29. His research focuses on computational imaging and image processing with practical applications in agricultural settings. Bartels specializes in developing vision systems for industrial applications, particularly in agricultural automation and quality control. His work bridges computer vision techniques with real-world agricultural challenges. His recent publications demonstrate expertise in color analysis for food production lines and methods to improve lighting conditions for vision systems. These works reflect his focus on solving practical problems in agricultural automation through computer vision techniques. Bartels is actively involved in several funded research projects with applications in the agricultural sector, collaborating with industry partners to implement vision systems for quality assessment and optimization. He collaborates extensively with researchers including Busch A, Gao Y, Eaton G, and others on projects related to agricultural imaging systems and AI applications in farming practices.

Christopher M Greeneمشاهده پروفایل

دانشیار

• Industry 4.0
• Robotics (Collaborative Robots/Cobots)
• Quality Engineering
• +۵ مورد دیگر

Dr. Christopher M. Greene is an Associate Professor at the School of Systems Science and Industrial Engineering, Binghamton University. His research focuses on applying Industry 4.0 technologies to enhance manufacturing systems, including collaborative robotics, additive manufacturing, and data analytics. He holds a BS from Syracuse University and MS/PhD degrees from Binghamton University. His expertise spans quality engineering, AI-driven robotics, and electronics manufacturing. Key research areas include improving solder joint reliability, optimizing manufacturing processes via DMAIC/Six Sigma, and leveraging augmented reality in cobotics. Recent publications emphasize defect analysis in electronics, healthcare robotics ethics, and material science advancements. He actively contributes to advancing quality control frameworks in printing and pharmaceutical processes. His work bridges theoretical models with industrial applications, aiming to solve real-world manufacturing challenges.

George van Voornمشاهده پروفایل

دانشیار

• Socio-ecological Systems
• Resilience Analysis
• Agent-Based Modelling
• +۷ مورد دیگر

Dr. George van Voorn is an Associate Professor in Applied Modelling & Machine Learning at Wageningen University & Research, affiliated with the Biometris department. His research focuses on developing and applying mathematical and computational models to study socio-ecological systems, resilience, and complex adaptive systems. He specializes in agent-based modelling (ABM), hybrid machine learning approaches, and dynamical systems analysis (e.g., stochastic differential equations). Van Voorn coordinates courses such as MAT15003 (Mathematics 3), SSB-30806 (Modelling in Systems Biology), and PhD-level modelling courses. He also leads projects on resilience quantification in socio-ecological systems, including agricultural and fisheries systems. His work addresses topics like tipping points, bifurcation analysis, and model validation methodologies for health-economic and environmental policy applications. Key research areas include: Resilience metrics for socio-technical systems Climate change adaptation strategies using ABM Machine learning integration with crop and ecological models Model validation frameworks (e.g., AdViSHE tool) He collaborates on interdisciplinary projects such as the 4TU DeSIRE initiative, focusing on systems resilience engineering. His recent publications emphasize model-based analysis of socio-environmental feedbacks, food system dynamics, and health-economic decision-making.