جست‌وجوی استاد و پژوهشگر

• Construction Logistics
• Digital Twin Frameworks
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.

Javier Rodriguez Sanchezمشاهده پروفایل

پژوهشگر ارشد

• Plant Breeding
• Genetics
• Genomics
• +۵ مورد دیگر

Javier Rodriguez Sanchez is a Postdoctoral Associate at the Institute of Plant Breeding, Genetics and Genomics (IPBGG) within the Department of Crop & Soil Sciences at the University of Georgia's College of Agricultural and Environmental Sciences (CAES), based at the Tifton Campus under Dr. Nino Brown's mentorship. His research integrates advanced technologies with plant science to revolutionize agricultural practices, specializing in: Autonomous field phenotyping systems using robotics and terrestrial laser scanning Deep learning applications for 3D/4D crop trait extraction and yield estimation Genetic improvement of cotton and peanut through seedling vigor and morphological trait analysis Spatiotemporal data fusion for real-time crop monitoring and precision agriculture Publications from 2017-2025 reveal a clear trajectory from horticultural robotization toward sophisticated AI-driven phenotyping platforms, with cotton and peanut as primary models. His work consistently bridges computer vision, LiDAR, and machine learning to solve breeding challenges, demonstrating increasing methodological complexity in data acquisition and analysis. No scientific awards were documented in the source materials. As a postdoctoral researcher, Dr. Sanchez operates within Dr. Nino Brown's mentorship structure with no reported advisees or independent grant leadership. His collaborative framework focuses on technology deployment rather than traditional academic advising. He contributes to the IPBGG's mission through the Tifton Campus research facility, which features specialized laboratories and field sites for crop genomics and phenomics. This environment supports his development of mobile robotic platforms for in-field data collection, positioning him at the intersection of agricultural engineering and plant breeding innovation.

• Programming Pedagogy
• Educational Technology
• Artificial Intelligence in Education
• +۲ مورد دیگر

Hugo G. Lapierre is an Assistant Professor at the University of Montreal’s Faculty of Education, Department of Educational Psychology and Andragogy. He holds a PhD in Education (2024) and an MA in Didactics (2017) from UQAM, alongside a BSc in Secondary Science and Technology Teaching (2024). His research focuses on programming pedagogy, educational technology integration, artificial intelligence literacy, and psychophysiological data applications in education. Education Doctorate in Education (2024), UQAM Master’s in Didactics (2017), UQAM BSc in Secondary Science and Technology Teaching (2024), UQAM Research Interests Lapierre investigates how educational robotics, visual programming languages, and AI impact science and technology learning. His work explores emotional and cognitive differences between novice and beginner programmers, psychophysiological data in educational research, and equitable AI integration in schools. He advocates for programming education to address cybersecurity risks and prepare students for future job markets. Grants and Projects He leads projects funded by the Fonds de recherche du Québec - Société et culture (FRQSC) and the University of Montreal, including studies on educational robotics’ effects on chemistry learning, AI literacy for disadvantaged schools, and virtual vs. in-person programming instruction. His grants (e.g., FRQSC PV113813) support early-career research in educational technology. Collaborations He collaborates with researchers like Patrick Charland (UQAM) and Martin Riopel (UQAM), focusing on interdisciplinary education, psychophysiological learning analytics, and teacher training in AI. His work spans scientific and professional domains, bridging empirical research with practical educational tool development.

Gabriel Dallagoمشاهده پروفایل

استادیار

• Animal Welfare
• Machine Learning Applications
• Livestock Production Systems
• +۳ مورد دیگر

Gabriel Dallago serves as Assistant Professor in the Department of Animal Science within the Faculty of Agricultural and Food Sciences at the University of Manitoba. His research integrates advanced data analytics with livestock production systems to enhance animal welfare and farm decision-making processes. His educational background includes: PhD from McGill University, Canada MSc from Federal University of the Vales of Jequitinhonha and Mucuri, Brazil BSc from Federal University of the Vales of Jequitinhonha and Mucuri, Brazil Dallago's research program centers on machine learning and deep learning applications for livestock management. Key initiatives include developing predictive models for animal bio-responses, integrating multimodal data streams to analyze complex farm systems, and optimizing dairy cow longevity through data-driven interventions. His work bridges computational science with practical agricultural challenges, focusing on tangible improvements in production efficiency and animal well-being. Precision monitoring of dairy cow behavior and welfare Early-life management impacts on herd productivity Computer vision applications for livestock assessment Economic modeling of livestock production systems Analysis of his 15 most recent publications (2022-2025) reveals strong thematic concentration in dairy science (47%), swine production (20%), and animal nutrition (20%), with consistent application of computational methods. Notable trends include increasing use of machine learning for welfare assessment (evident in 60% of recent works), growing emphasis on economic sustainability metrics, and innovative sensor integration for real-time livestock monitoring. Dallago teaches ANSC 7500 (Methodology in Agricultural and Food Sciences) and AGRI 4100 (Current Issues in Agricultural Systems), though specific advising relationships and grant details remain unreported in available materials. His research appears to operate through interdisciplinary collaborations leveraging computational tools and on-farm data collection systems, though dedicated laboratory descriptions are absent from current documentation.

Vinh Nguyenمشاهده پروفایل

استادیار

• Advanced Manufacturing
• Industry 4.0
• Human-Robot-Machine Interaction
• +۵ مورد دیگر

Vinh Nguyen is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Michigan Technological University, where he directs the Michigan Tech Center for AI and coordinates the NIST-PREP program. His research focuses on advanced manufacturing through Industry 4.0, human-robot-machine interaction, and physics-based/data-driven modeling. He has developed solutions for machining, additive manufacturing, metal forming, and robotic assembly to promote smart and sustainable manufacturing. Prior to joining Michigan Tech in 2022, he was a National Research Council Postdoctoral Fellow at NIST (2020–2022). Dr. Nguyen earned his PhD (2020), MS in Mechanical Engineering (2017), and MS in Electrical & Computer Engineering (2017) from Georgia Institute of Technology. He received dual bachelor’s degrees in Electrical and Mechanical Engineering from Rensselaer Polytechnic Institute (2014). His research portfolio spans Advanced Manufacturing Industry 4.0 and 5.0 Human-Robot Interaction Physics-Based/Data-Driven Modeling Industrial Automation based on his lab’s interdisciplinary focus on human-centric, resilient solutions. His recent publications address trends in Machine Learning for Manufacturing Autonomous Vehicle Sensors Hybrid Additive/Subtractive Manufacturing Augmented/Mixed Reality Interfaces Industrial Robot Diagnostics Material-Specific Machining with keywords spanning Robotics, Data Science, and Industrial Engineering.

• Consumer Behavior
• Anthropomorphism
• Service Marketing
• +۵ مورد دیگر

Professor Sara Kim serves as Professor and Head of the Marketing Area at the University of Hong Kong, where she has established herself as a leading scholar in consumer behavior since joining in 2012. Her interdisciplinary research bridges psychological theory and marketing practice, with findings published in premier journals including Journal of Marketing and Journal of Consumer Research , and featured in major media outlets such as The New York Times and Time . Her academic credentials include: Ph.D., Booth School of Business, University of Chicago MBA, Booth School of Business, University of Chicago M.S., KAIST Business School, Korea B.S., KAIST, Korea Professor Kim's research program centers on how consumers interpret humanlike qualities in objects and services, with three interconnected pillars: (1) anthropomorphism in technology-mediated contexts like robotics and digital interfaces; (2) emoticon/emoji usage in service communications; and (3) implicit theories shaping consumer decision-making. Her recent work examines how money anthropomorphism influences financial behavior and how leader emojis affect team creativity, demonstrating practical applications for service industries navigating digital transformation. Analysis of her 15 most recent publications reveals a clear trajectory toward technology-intensive service contexts, with 60% of 2023-2025 work focusing on human-AI interaction dynamics. Her scholarship consistently applies social psychology frameworks to contemporary marketing challenges, particularly in service employee-consumer relationships within digital environments, while maintaining strong theoretical contributions to attribution theory and person perception literature. Her accolades include: MSI 2024 Scholar designation AP-ACR Best Consumer Behavior Working Paper Award Outstanding Area Editor at International Journal of Research in Marketing (2023) Multiple university-level teaching and research awards from 2014-2021 Professor Kim has received significant institutional recognition for postgraduate supervision, evidenced by her 2021 Faculty Research Postgraduate Supervision Award, though specific student names and grant funding details are not publicly documented. Her ongoing research agenda continues to explore the psychological mechanisms underlying consumer-technology interactions in service ecosystems.

Wilfried Kubingerمشاهده پروفایل

استاد

• Embedded Systems
• Machine Vision
• Autonomous Robotics
• +۳ مورد دیگر

Prof. Wilfried Kubinger serves as the Head of the Department of Electronic Engineering at the University of Applied Sciences Technikum Wien, Austria. He holds a PhD in Technical Sciences from the Technical University of Vienna (1999) and has extensive experience in research and industry. His academic roles include leading the 'Automation & Sensor Technology' competence field and managing the 'Automation & Robotics' research area. **Research Focus:** His work centers on embedded systems, machine vision, autonomous robotics, and real-time control systems. Notable projects include obstacle detection for autonomous vehicles, stereo vision algorithms, and agricultural robotics applications. He actively contributes to IEEE and OVE engineering associations. **Professional Journey:** Prior to academia, he worked at Siemens Austria (2000–2003) as a software developer and project manager, and at AIT Austrian Institute of Technology (2003–2010) managing research projects in autonomous systems. He participated in DARPA Grand Challenge/Urban Challenge as a principal scientist for vision-based obstacle detection. **Publications:** His research spans embedded vision systems, FPGA implementations, and autonomous vehicle technologies. Recent work emphasizes agricultural robotics and Industry 4.0 applications. He also leads R&D project acquisition and implementation for Technikum Wien.

Marco Portaمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• Eye Tracking
• +۴ مورد دیگر

Marco Porta is a Full Professor at the University of Pavia, Department of Electrical, Computer and Biomedical Engineering. He teaches Web and Multimedia Technologies in the Computer Engineering Master's program and Web Design and Technologies in the interdepartmental CIM Bachelor's program. His research focuses on Eye Tracking, Vision-Based Perceptive Interfaces, and Human-Computer Interaction, with recent emphasis on AI applications for human-centered systems. He leads the Computer Vision & Multimedia Lab and chairs teaching councils for CIM and CoD programs. Education: Master's in Electronic Engineering (Polytechnic of Milan) and Ph.D. in Electronic & Computer Engineering (University of Pavia). Professional roles include vice-chair of IEEE's Technical Committee on Factory Automation. Over 118 publications in journals/conferences, with contributions to biometrics, e-learning interfaces, and industrial automation. Research highlights include gaze-based authentication systems, interactive museum interfaces, and ergonomic in-vehicle infotainment evaluations. Current projects explore gaze-driven intelligent tutoring systems and public space interaction frameworks.

Wessel Reijersمشاهده پروفایل

پژوهشگر ارشد

• Technology Ethics
• Emerging Technologies
• Social Credit Systems
• +۵ مورد دیگر

Wessel Reijers is a Postdoctoral Researcher at the Department of Media Studies, Paderborn University, Germany, with visiting scholarships at the Technion and the Robert Schuman Centre, European University Institute. Previously, he was a Max Weber Fellow at the European University Institute, a Research Associate in the ERC project "BlockchainGov" led by Dr. Primavera de Filippi, and a postdoctoral researcher at the University of Vienna. Reijers received his PhD in technology ethics from Dublin City University. His academic journey has spanned multiple European institutions, focusing consistently on the ethical implications of emerging technologies for society and citizenship. His research primarily explores how emerging technologies impact citizenship, with particular attention to social credit systems and their effects on civic virtue. He also investigates distributed governance models, analyzing both their potential to enhance democratic processes and their inherent risks. His work bridges philosophy, political theory, and technology studies, offering critical perspectives on how technological developments reshape societal structures. Recent publications demonstrate a growing focus on AI ethics, interpretability, and what he terms "Positive Luddism"—a critical yet constructive approach to technological development that emphasizes human flourishing while acknowledging technology's dangers. Reijers is the author of "Narrative and Technology Ethics" and co-editor of "Interpreting Technology." His upcoming book "Introduction to the Ethics of Emerging Technologies" (2025) further establishes him as a leading voice in technology ethics. His work has gained recognition in both academic and public spheres, with media appearances including a Deutschlandfunk interview on "Positive Luddism" (2024). Beyond academia, Reijers is a creative individual who writes fiction, composes and produces music (available on Soundcloud), and creates paintings. He is part of an international music collaboration called "Conditio Humana," demonstrating his commitment to interdisciplinary engagement between technology, ethics, and the arts.

Divya Mahajanمشاهده پروفایل

استادیار

• Computer Architecture
• Distributed Systems
• Machine Learning Systems
• +۲ مورد دیگر

Divya Mahajan is an Assistant Professor holding dual appointments in the College of Computing and College of Engineering at Georgia Institute of Technology. She directs the Systems Infrastructure and Architecture Research Lab, focusing on sustainable computing platforms for large-scale AI, machine learning, and data storage systems. Her research integrates computer architecture, distributed systems, and database technologies to optimize end-to-end data pipelines. Mahajan earned her PhD from Georgia Tech and Bachelor's from IIT Ropar (President's Gold Medal). Prior to academia, she was a Senior Researcher at Microsoft Azure, leading communication collective designs for distributed DNN training. Awards include NCWIT Collegiate Award (2017) and HPCA Distinguished Paper Award (2016). Research spans hardware-software co-design for ML systems, efficient recommendation architectures, federated learning optimization, and PIM/NPU acceleration. Recent projects address challenges in large-scale model serving, edge-cloud integration, and sustainable computing. Student advisees include PhD and MS researchers in systems and architecture. Publications demonstrate consistent innovation in accelerating ML workloads through novel hardware/software techniques, with work appearing in ISCA, MICRO, ASPLOS, NeurIPS, and VLDB. Current projects explore energy-efficient AI infrastructure and domain-specialized systems for emerging economies.

Mehdi Dastaniمشاهده پروفایل

استاد

• Artificial Intelligence
• Multi-Agent Systems
• Formal Methods in AI
• +۵ مورد دیگر

Prof. Mehdi Dastani is a Professor and chair of the Intelligent Systems group within the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. He leads the Master's program in Artificial Intelligence and focuses on formal and computational models in AI, particularly multi-agent systems. His research integrates insights from philosophy, psychology, and law to develop autonomous agents that reason about social and cognitive concepts like norms, emotions, and responsibility. Dastani has held academic roles at Utrecht University since 2001, including postdoctoral research and faculty positions. Education: M.Sc. Computer Science (University of Amsterdam, 1991), M.Sc. Philosophy (University of Amsterdam, 1992), Ph.D. in Humanities (University of Amsterdam, 1998). His work spans theoretical and applied projects, including grants for initiatives like Golden Agents (simulating Golden Age creative industries) and traffic control systems using virtual organizations. He is actively involved in academic committees, editorial boards, and organizing international conferences like AAMAS and PRIMA. Research Interests: Multi-Agent Programming, Normative Systems, Autonomous Agents, Cognitive Robotics, and Human-Centered AI. His projects address challenges like norm enforcement, decision-making in complex systems, and ethical AI integration with societal needs. Advising & Grants: Supervised numerous PhD students (e.g., Birna van Riemsdijk, Bas Testerink) and secured grants for projects such as 'Controllable AI: Human-Centered Approach'. His work includes collaborations on urban governance, autonomous driving, and AI tools for literacy support in children. Labs & Teams: Leads the Intelligent Systems group, contributing to agent-based simulations, ethical AI frameworks, and interdisciplinary collaborations with social scientists and urban planners.

• Remote Sensing
• GIS
• Ecology
• +۶ مورد دیگر

Dr. Harm Bartholomeus is an Assistant Professor of Remote Sensing at the Department of Geo-information Science and Remote Sensing, Wageningen University & Research. He received his MSc in Physical Geography (2000) and a Geography teaching degree (2001) from Utrecht University. His career includes part-time PhD research (2004–2009) on soil property estimation via spectral measurements and vegetation influence. Since 2009, he has focused on remote sensing techniques like imaging spectroscopy, LiDAR, and UAV-based methods applied to forestry, soil science, and climate studies. In 2012, he co-founded the Wageningen UR Unmanned Aerial Remote Sensing Facility (UARSF), advancing UAV research in environmental studies. His expertise spans Ecology, Geographical Information Systems (GIS), Remote Sensing, Soil Science, Spectroscopy, and 3D analysis. He teaches courses such as Advanced Earth Observation, Remote Sensing and GIS Integration, and MSc thesis supervision in Geo-information Science and Remote Sensing. His work integrates cutting-edge technologies for environmental monitoring, including terrestrial laser scanning and drone-based sensing. Research interests include vegetation-soil interactions, UAV applications in agriculture and ecology, and climate resilience. He collaborates on projects like the UARSF and contributes to global initiatives like the IDEAS-QA4EO network. No scientific awards are explicitly mentioned, but his contributions to UAV and LiDAR methodologies are widely recognized. He advises MSc students on thesis and internship projects in remote sensing and geo-information science.

• Food Science
• Biotechnology
• Material Science
• +۴ مورد دیگر

Prof. Remko Boom is a Full Professor of Food Process Engineering at Wageningen University & Research. His research focuses on sustainable food systems, plant-based alternatives, and advanced food processing technologies such as 3D food printing, membrane filtration, and protein functionalization. Key areas include edible robotics, animal-free cheese alternatives via artificial casein micelles, and functional ingredient extraction from plant and insect-based sources. He collaborates globally on biorefinery processes and contributes to edible robotic systems through material science innovations. Education Background: PhD in Food Technology (exact details not specified) Master's/Undergraduate degrees in relevant engineering disciplines (not explicitly stated) Research Interests: Prof. Boom's work spans food process engineering with emphasis on: - Development of plant-based protein ingredients using mild fractionation techniques - 3D-printed food materials with tailored mechanical properties - Electrophoretic and membrane-based separation technologies for food components - Engineering edible casein micelles for cheese analogues - Biodegradable robotics using food-grade materials Recent Research Trends: Publications from 2024-2025 highlight advancements in: - 3D-printed starch cryogels and protein-based composites - Oleosome extraction and encapsulation of bioactive compounds - Functional characterization of artificial casein micelles - Edible robots powered by Marangoni propulsion Awards & Recognition: No specific awards listed in available data, though his work has received significant media attention including features on edible robotics and sustainable food innovations. Advising & Collaboration: Supervising 87+ PhD projects including work on: - Electrohydrodynamic drying - Brewer's spent grain valorization - Recombinant protein purification Active in industry partnerships for scaling-up electrophoretic separation and 3D food printing technologies Labs & Teams: Leads research groups focused on: - Advanced Food Processing Technologies - Sustainable Ingredient Development - Biorefinery Applications in Food Systems

Yannis Konstasمشاهده پروفایل

دانشیار

• Natural Language Processing (NLP)
• Artificial Intelligence (AI)
• Natural Language Generation (NLG)
• +۳ مورد دیگر

Yannis Konstas is an Associate Professor (Reader in the UK system) at Heriot-Watt University’s School of Mathematical & Computer Sciences, Department of Computer Science. He co-leads the Safe and Secure AI for Robotics (SAIR) theme at the National Robotarium. His research focuses on Responsible, Safe, and Explainable AI applications using NLP, including Gender-Based Violence (GBV) detection via LLMs, Social Behavior Modeling, and Vision-Language-Action (VLA) models for robotics. He holds a PhD from the University of Edinburgh (2013), supervised by Mirella Lapata, and has held postdoctoral roles at the University of Washington and the University of Edinburgh. Research interests include Natural Language Generation (NLG), representations, modeling, and evaluation across domains like math problems and dialogue systems. His work spans Psycholinguistics, semantics, and Information Retrieval. He actively explores new fields, such as LLM interpretability and instruction-driven robotic manipulation. He accepts PhD students and collaborates on interdisciplinary projects, including regulatory compliance digitalization and embodied AI for egocentric video understanding. Education: PhD in Computer Science (2013), University of Edinburgh; Postdoctoral Researcher at University of Washington (2015–2017) and University of Edinburgh.

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +۵ مورد دیگر

Gwenn Englebienne is an Assistant Professor at the Digital Society Institute and Human Media Interaction group of Utrecht University. Their research focuses on Artificial Intelligence, Computer Vision, and Human-AI Interaction, with applications in robotics, health, and social computing. They have contributed to over 80 research outputs since 2007, emphasizing embodied AI, social robotics, and explainable machine learning. Research interests span activity recognition, teleoperation systems, and ethical AI design. Notable work includes developing GNN-based group detection algorithms and evaluating chatbot reliability through automated question-answering frameworks. Their studies often bridge technical innovation with human-centered design, such as measuring embodiment via pupil dilation or addressing asymmetry in video-conferencing interactions. Key collaborations include work on social robotics, telepresence systems, and health monitoring using ambient sensors. Publications span conferences like IDA, CogMI, and LREC-COLING, reflecting interdisciplinary impact. A dataset on robot social positioning behavior is publicly accessible via 4TU.Centre for Research Data. Current work explores semi-supervised domain adaptation, spiking neural networks, and the psychological dimensions of AI trustworthiness. They lead initiatives in the Digital Society Institute to align technological advancements with societal needs.