جست‌وجوی استاد و پژوهشگر

Marcus Norrgårdمشاهده پروفایل

استاد

• Intellectual Property Law
• Copyright Law
• Design Law
• +۳ مورد دیگر

Marcus Norrgård is a Professor of Law at the University of Helsinki , leading the Vaasa Unit of Legal Studies within the Faculty of Law. His expertise spans intellectual property law , copyright , design law , and the ethical implications of AI and 3D printing on legal frameworks. He actively contributes to Nordic legal research and EU copyright harmonization , with recent projects focusing on AI-generated content and virtue ethics in private law . His 15 most recent articles analyze topics such as Nordic copyright legislation , AI training data protection , and design law harmonization , reflecting his work with foundations like Harry Schaumans Stiftelse and Vaasan Aktiasäätiö . Norrgård serves on doctoral committees and as an opponent in thesis defenses , while advising Finnish parliamentary committees on copyright and telecommunications reforms . He has held leadership roles including Chairman of the Finnish Copyright Council (2008–2020) and Director of the IPR University Center (2018–2021).

• Business Model Innovation
• Digital Transformation
• Open Innovation
• +۷ مورد دیگر

Prof. Frank T. Piller ist Chair of Technology and Innovation Management an der RWTH Aachen University und Mitbegründer der RWTH Business School . Er forscht seit 2007 zu Disruptiver Geschäftsmodellinnovation , Industrie 4.0 und Kundenco-creation . Als Träger des ERC Synergy Grants SAFEr Grid (2025-2031) entwickelt er modulare Energienetze für die Zukunft. Lehrstuhlinhaber für Technologie- und Innovationsmanagement Gründungsdekan der RWTH Business School Internationaler Forschungskoordinator Seine Forschungsschwerpunkte umfassen: Business Model Innovation in etablierten Unternehmen AI-gestützte Wertschöpfung und digitale Plattformen Ökosystem-Governance für dezentrale Industrienetze Circular Economy Integration in massgeschneiderte Produktion Er erhielt: Co-Creation Award der PDMA Nominierung für HBR/McKinsey Innovation Award Mehrfachauszeichnung für "Flipped Classroom"-Lehre Google Scholar H-Index 73 mit >25.000 Zitierungen Als Keynote-Speaker und Executive-Education-Dozent an führenden Business Schools (MIT, IE, Vlerick) unterstützt er globalen Wandel. Sein Forschungsteam ( >30 Doktoranden ) arbeitet mit Industriepartnern wie Siemens , Vodafone und 3M .

Kudirat Ayinlaمشاهده پروفایل

مدرس

• Digital Technology in Construction
• Sustainable Construction Methods
• Artificial Intelligence & Machine Learning in AEC
• +۳ مورد دیگر

Kudirat Ayinla is a Lecturer in Construction Management and Programme Lead for the BSc (Hons) in Commercial Management and Quantity Surveying at the University of Loughborough. Her research focuses on enhancing construction industry efficiency through digital technologies like AI, BIM, and Digital Twins, with specific emphasis on offsite construction methods and sustainability. Education: BEng, MSc, PhD, PGCert Professional Affiliations: MCIOB, FHEA Key research areas include knowledge-based modeling, AI applications in construction, and circular economy integration in waste management. She leads the British Council UK grant project on Digital Manufacturing and collaborates with the Council for the Heads of the Built Environment on apprenticeship studies. Her recent articles explore TDABC models for offsite manufacturing, AI impacts on costing practices, and BREEAM perceptions in the industry. She actively supervises PhD candidates researching ontology applications and modern construction methods.

Mohammad T. Khasawnehمشاهده پروفایل

استاد

• Healthcare Systems Engineering
• Operations Management
• Data Science
• +۳ مورد دیگر

Mohammad T. Khasawneh is a SUNY Distinguished Professor and Director of the School of Systems Science and Industrial Engineering at Binghamton University. He leads the Watson Institute for Systems Excellence (WISE) and the Healthcare Systems Engineering Center. His roles include Director of the Manhattan Graduate Program in Health Systems. Education: BS and MS in Mechanical Engineering from Jordan University of Science and Technology (1998, 2000), PhD in Industrial Engineering from Clemson University (2003). Research focuses on healthcare systems engineering, operations management, and data science. His work optimizes healthcare systems for improved patient outcomes and cost efficiency. Key areas include predictive analytics, hospital resource utilization, and clinical performance improvement. He has generated over $15M in external funding and led projects with U.S. hospital systems. Notable achievements include developing the Executive Master of Science in Health Systems and an MS in Healthcare Systems Engineering. His research has produced 60+ journal articles and 120+ conference papers. Awards include SUNY Chancellor’s Awards for Teaching (2011) and Scholarship (2021), University Awards for Graduate Director (2015) and International Education (2016). He is an IISE Fellow and holds honorary visiting professorships at Hebei University of Technology (China) and Vellore Institute of Technology (India). Grants and funding: $2.5-3M annually via WISE, $39M in software/equipment grants. Lab/Initiatives: Healthcare Systems Engineering Center, WISE, and multiple hospital partnerships.

• Operations Research
• Data Analytics
• Machine Learning
• +۴ مورد دیگر

Dr. Katie McConky is a Professor and Department Head of Industrial and Systems Engineering at Rochester Institute of Technology (RIT). She holds a Ph.D. in Industrial Engineering from SUNY Buffalo and prior experience as a research scientist at CUBRC Inc., where she worked on military and data mining projects. Her research focuses on operations research, machine learning, and energy systems optimization, addressing challenges in combinatorial optimization, cyberattack forecasting, and sustainable energy management. She has secured funding from agencies like ONR, AFRL, NASA, and NYSERDA. Education: BS and MS (RIT), Ph.D. (SUNY Buffalo) Key Roles: Department Head, Faculty Member, Research Scientist (CUBRC) Her work spans applications such as kidney exchange optimization, rover mission planning, and energy demand forecasting. She emphasizes interdisciplinary collaboration in her research, integrating machine learning with traditional optimization techniques. Dr. McConky’s publications highlight advancements in forecasting methodologies for cyber threats, energy systems, and transportation logistics. She teaches courses including Operations Research and Forecasting Methods, emphasizing practical software tools like Gurobi. Her contributions include patents on remote activity detection and energy storage optimization. Her research is supported by grants from federal agencies and industry partners, reflecting her expertise in both academic and applied domains.

• Decision making
• Knowledge engineering
• Knowledge graphs
• +۳ مورد دیگر

Marie-Hélène Abel is a Professor and Director of the Computer Science Department at the University of Technology of Compiègne (UTC), France. She leads the Heudiasyc laboratory (UMR CNRS 7253) and specializes in decision making, knowledge engineering, knowledge graphs, and multi-agent systems. Her work focuses on collaborative systems, organizational learning, and the integration of social data into decision support frameworks. She has been recognized with prestigious awards, including Senior IEEE membership (2017) and the 2017 K2 Trophy for participatory computing innovations. Her research emphasizes the development of systems like the MEMORAe platform, which supports learning ecosystems through collaborative environments and organizational memory. She collaborates internationally with institutions such as the Pontifical Catholic University of Paraná (Brazil) and industry partners including Thales, Alstom Transport, and PSA. Key projects include crisis simulation systems and ontology-based frameworks for Industry 4.0 collaboration. Abel’s academic contributions span over 50 peer-reviewed articles, with recent works addressing context-aware recommender systems, crisis management simulations, and teacher efficacy in digital education. Her leadership roles include directing research projects, overseeing the Computer Engineering Department, and advancing ethical AI practices through initiatives like the Sorbonne.AI network. Education: HDR (Habilitation à Diriger des Recherches) on 'Contribution of Organizational Memories in a Learning Context' (2007) Administrative Roles: Equality Officer, University Antiracism/Anti-Semitism Officer International Collaborations: Brazil, Egypt, and Tunisia

• Innovation Management
• Technology Transfer
• University-Industry Collaboration
• +۳ مورد دیگر

Dr. Samuel Horner is a Lecturer in Innovation Management at the University of Liverpool Management School. He previously conducted Leverhulme-funded research at the Leverhulme Centre for Materials Design. He earned his PhD from the University of Liverpool Management School in 2019 and has since taught on undergraduate and postgraduate programs. His research focuses on university-industry collaboration, technology transfer, artificial intelligence, and innovation, with a theoretical emphasis on processual approaches to organizational time and temporality. He serves as an editorial board member for Academy of Management Learning and Education and has reviewed for journals like Organization Studies . He received the 'Outstanding Emerging Reviewer' prize in 2020. Education: PhD, University of Liverpool Management School, 2019 Research Interests: Horner’s work bridges empirical and theoretical domains, examining strategic agency in university technology commercialization, the role of time in organizational processes, and innovation management. His recent focus on AI and innovation reflects broader trends in digital transformation. He employs processual frameworks to analyze dynamic organizational phenomena. Grants: Manufacturing and Digital Transformation: A Business Model Innovation Perspective (British Council, 2024–2025) Teaching & Professional Activities: Coordinates modules like 'Innovation and Entrepreneurship' and 'Innovation in a Global Perspective.' He serves as an examiner for the University of Portsmouth’s Innovation Management program. His editorial and review roles underscore his engagement with scholarly discourse. Labs/Teams: Affiliated with the Entrepreneurship research group at the University of Liverpool Management School.

Salvatore T. Marchمشاهده پروفایل

استاد

• Business Intelligence
• Information Systems
• Forecasting
• +۵ مورد دیگر

Salvatore T. March is a Professor specializing in Information Systems, Business Intelligence, and Design Science. He holds leadership roles as Editor-in-Chief of ACM Computing Surveys and has served on editorial boards for prestigious journals like MIS Quarterly. His research focuses on conceptual modeling, database design, and process theory in project management. March has organized major conferences such as the International Conference on Conceptual Modeling and contributed to advancing methodologies in distributed database systems. Education: Ph.D., Operations Research, Cornell University, 1978 M.S., Operations Research, Cornell University, 1975 B.S., Industrial Engineering & Operations Research, Cornell University, 1972 Research Interests: March’s work emphasizes the intersection of theoretical frameworks and practical systems design. Key areas include: Design Science Methodology Conceptual Modeling for Active Information Systems Process Theory in Project Management Ontology Engineering for Semantic Technologies Temporal Dynamics in Business Systems His contributions bridge academic rigor and real-world IT applications, particularly in manufacturing and service industries. Publications & Impact: With over 150 publications, March’s work spans foundational topics like distributed database design to modern challenges in predictive maintenance and digital surveillance ethics. His recent focus includes meta-theoretical debates in information systems research. Grants & Labs: While specific grants are not listed, his leadership roles indicate sustained funding in systems research. Active involvement in editorial and conference committees highlights his role in shaping the discipline’s future directions.

Stefano Martinianiمشاهده پروفایل

استادیار

• Computational and Statistical Physics
• Materials Science
• Artificial Intelligence for Science
• +۵ مورد دیگر

Stefano Martiniani is an Assistant Professor of Physics, Chemistry, Mathematics, and Neuroscience at New York University, affiliated with the Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry. His interdisciplinary research explores computational physics of complex systems, including neural circuit theories, non-equilibrium statistical mechanics, and AI-driven materials discovery. He has pioneered methods for analyzing high-dimensional energy landscapes and received prestigious awards like the NSF CAREER Award (2024) and IUPAP Early Career Prize (2023). Education: PhD in Physics (2017), University of Cambridge MPhil in Physics (2013), University of Cambridge BSc in Physics (2012), Imperial College London Research Interests: His work bridges statistical physics and artificial intelligence, focusing on: Engineering disordered materials with tailored spectral properties Quantifying entropy production in active matter Developing open science frameworks like ColabFit for machine learning interatomic potentials Neural circuit models for cortical communication Grants & Collaborations: Funded by NSF, NIH, Chan Zuckerberg Initiative, and Simons Foundation. Leads interdisciplinary teams in computational physics, AI, and materials science. Labs/Initiatives: Core member of NYU's Center for Soft Matter Research; develops software tools like FReSCo and KLIFF-Torch for computational materials science.

Michael D. Kimbroughمشاهده پروفایل

استاد

• Corporate Financial Reporting
• Voluntary Disclosure Practices
• Accounting for Intangible Investment
• +۳ مورد دیگر

Michael D. Kimbrough is a Professor and Area Chair in Accounting and Information Assurance at the Robert H. Smith School of Business, University of Maryland. He joined in 2010 after eight years at Harvard Business School. His research focuses on corporate financial reporting, with emphases on voluntary disclosure practices and intangible investment accounting. He holds a B.A. in Economics from Washington University in St. Louis and a Ph.D. in Accounting from Indiana University. Educations: B.A. Economics (Washington University), Ph.D. Accounting (Indiana University) His research explores cybersecurity implications in financial information systems, AI's impact on analyst performance, and the intersection of legal leadership with financial transparency. Key areas include the strategic costs and benefits of corporate transparency, consumer responses to earnings reports, and mitigating earnings overstatement risks through legal expertise in leadership roles. Recent work includes the AI-powered Analysts study (2023) showing how AI improves analyst forecasts, and collaborations on cybersecurity policy at UMD forums. He serves on the editorial board of The Accounting Review and received the LeRoy J. Herbert Fellowship. He secured $150K in 2023 for an AI Initiative in capital market research. Prior experience includes work as a CPA with Price Waterhouse, advising manufacturing and tech clients.

August Wilhelm Scheerمشاهده پروفایل

استاد

• Business Informatics
• Process Management
• Digital Transformation
• +۵ مورد دیگر

Prof. Dr. August-Wilhelm Scheer is a Professor of Business Informatics at Saarland University and founder of the Scheer Group, a leading IT enterprise. He pioneered the ARIS method for integrated information systems and established the School of Digital Sciences at Saarland University. His work bridges academic research and industry application through ventures like IDS Scheer Holding and IMC AG. Educations: Founded Institute of Business Informatics at Saarland University Doctoral supervision of 76 theses (over 3/year average) Research collaborations with German Research Center for Artificial Intelligence (DFKI) Research Interests: Focuses on business process management, digital transformation, and AI-driven enterprise solutions. His ARIS method revolutionized IT-business alignment through process modeling. Current work explores composable enterprise architectures and AI agent systems in business contexts. Awards: German Research Hall of Fame Inductee (2017) Lifetime Achievement Award (Global University Alliance) Advising & Innovation: Supervised 76 doctoral students and spun-off 1,300+ client companies through Scheer Group solutions. Spearheaded digital learning platforms via IMC AG. Labs/Teams: Leads August-Wilhelm Scheer Institute for Digital Products and Processes, fostering research-practice partnerships in digital innovation.

• Autonomous Industrial Systems
• Model Predictive Control
• Optimization
• +۷ مورد دیگر

Mehmet Mercangoz is an Associate Professor in Autonomous Industrial Systems at the Department of Chemical Engineering, Faculty of Engineering, Imperial College London. His research focuses on developing intelligent systems for industrial processes and energy systems, emphasizing safety, reliability, and sustainability through process modeling, model predictive control, optimization, and machine learning. His recent publications highlight applications of large language models , reinforcement learning , and hybrid mechanistic-machine learning models to address challenges in industrial automation, fault handling, energy storage, and gas compression systems. Key themes include decarbonization, electrification of process industries, and adversarially robust control frameworks. Current affiliations include Imperial College London and ABB, with prior roles at ABB Corporate Research Switzerland and ABB Future Labs. His work bridges chemical engineering , control theory , and artificial intelligence , targeting zero-emission industrial operations.

Himanshu Jainمشاهده پروفایل

استاد

• Glass Science and Technology
• Photonics
• Nanomaterials
• +۵ مورد دیگر

Dr. Himanshu Jain is the T.L. Diamond Distinguished Chair in Engineering and Applied Science and a Professor of Materials Science & Engineering at Lehigh University. He leads the International Materials Institute for New Functionality in Glass and previously directed the Institute for Functional Materials and Devices (I-FMD). His research focuses on advancing glass science through innovations in photonics, bioactive materials, crystal engineering, and laser processing. Education: D.Eng.Sc., Materials Science, Columbia University M.Tech., Indian Institute of Technology (India) M.S., Banaras Hindu University (India) B.S., Kanpur University (India) Research Interests: Laser-induced single-crystal architectures in glass Optical and electronic functionalities in glass Biomedical applications of bioactive glass (e.g., bone scaffolds) Thermal and radiation effects on glass properties Machine learning for crystal growth modeling Awards: Recipient of Otto Schott Research Prize for atomic fluctuation models Zachariasen Award for lithium transport discovery Morey Award for defining new glass science horizons Fulbright and Humboldt Fellowships Advising & Grants: Has supervised numerous students and secured grants for interdisciplinary projects. Active in collaborative initiatives like the Lehigh-NC A&T flood damage mapping partnership. Labs/Teams: Oversees Lehigh's advanced materials facilities, including Sinclair Lab 120A. Coordinates global networks for glass science education and research.

• Machine Learning
• Artificial Intelligence
• Computer Science
• +۳ مورد دیگر

Prof. Felix Bießmann holds a professorship in Computer Science and Media at Berlin University of Applied Sciences' Department VI. His research focuses on machine learning applications in diverse fields including healthcare, urban planning, environmental science, and robotics through his Cognitive Algorithms Lab. He teaches courses such as Machine Learning, Deep Learning, and Data Science Workflows, alongside roles at TU Berlin and Korea University. Education: PhD (Dr. rer. nat.) in Natural Sciences Research interests span machine learning theory and practical implementations across domains like computer vision, generative AI, and sensor data analysis. His work addresses challenges in automated systems, healthcare monitoring, and sustainable technologies. Recent student theses explore topics like license plate recognition, adaptive game soundtracks, and bird song detection using TinyML. Collaborations include projects with the Charité Berlin and Robert-Koch Institute. Lab: Cognitive Algorithms Lab (developing machine learning methods/applications) Contact: felix.biessmann@bht-berlin.de | Office D138, Berlin University of Applied Sciences.

Xuebin Weiمشاهده پروفایل

دانشیار

• Geographic Information Systems (GIS)
• Social Media Analysis
• Machine Learning
• +۴ مورد دیگر

Xuebin Wei is an Associate Professor of Geography at the College of Integrated Science & Engineering (CISE) at James Madison University (JMU). He holds a Ph.D. in Geography from the University of Georgia, complemented by advanced degrees in GIS and Urban Planning from Wuhan University and ITC at the University of Twente. Dr. Wei specializes in integrating geospatial technologies with social media analysis, machine learning, and cloud computing to address urban and environmental challenges. His research focuses on spatial-social networks, 3D urban modeling using LiDAR and aerial imagery, and applying social media data for disaster response and public health. Notable projects include the JMU Virtual 3D Campus and LBSocial initiative exploring geosocial data frameworks. Wei teaches courses in GIS, cloud computing (AWS), programming for data science, and machine learning. His publications span topics like election prediction using Twitter data, spatial analysis of climate phenomena (El Niño), and optimizing urban transit infrastructure. While no specific awards are listed, his work reflects interdisciplinary innovation at the intersection of geography, technology, and society. He advises students in CISE's data science and geospatial programs through courses like IA340 Data Mining and GEOG215 Cartography.