جست‌وجوی استاد و پژوهشگر

Paul Trottمشاهده پروفایل

استاد

• Innovation Management
• New Product Development
• Corporate Foresight
• +۳ مورد دیگر

Professor Paul Trott holds dual academic appointments as Professor of Innovation Management at the University of Portsmouth's Portsmouth Business School and Professor of Entrepreneurship and Innovation at the Technical University of Delft, Netherlands . His research focuses on innovation policy, corporate innovation strategies, and the management of technological change. With over £500,000 in research funding secured, his work includes projects such as analyzing product development opportunities for UK-based UPS manufacturing firms and aiding steel tube manufacturers in diversifying their customer base. Education: Holds a PhD from Cranfield University. Teaching experience spans universities in Germany, the Netherlands, and the United States. He has supervised over ten PhD students, contributing to academic mentorship in innovation disciplines. Research Interests: Innovation management, new product development (NPD), corporate foresight, technology management, and public sector innovation. His influential book Innovation Management & New Product Development (now in its 5th edition) is a global standard text. Grants & Projects: Principal Investigator for studies on UPS product development and steel tube diversification. Projects emphasize practical applications of innovation theory, including failure analysis, risk mitigation, and strategic foresight. Affiliations: Member of the Food Cultures in Transition research cluster and the Future of Law, Innovation and Technology Research Centre , demonstrating interdisciplinary engagement in innovation ecosystems.

Janusz Kacprzykمشاهده پروفایل

استاد

• Artificial and Computational Intelligence
• Fuzzy Logic
• Multivalued Logic
• +۱۳ مورد دیگر

Janusz Kacprzyk is a Full Professor at the Systems Research Institute, Polish Academy of Sciences (1970–present, full-time). He concurrently holds part-time professorships at WIT – Warsaw School of Applied Information Technology and Management (since 1998), the Industrial Institute of Automation and Measurements (PIAP) (since 2007), and the Department of Electrical and Computer Engineering, Cracow University of Technology (since 2010). He is an IEEE Fellow (since 2006) and IFSA Fellow (since 1997), a Full Member of the Polish Academy of Sciences (since 2010), and Foreign Member of the Bulgarian Academy of Sciences (since 2013) and the Spanish Royal Academy of Economic and Financial Sciences (since 2007). Education M.Sc. in Automatic Control and Computer Science, Warsaw University of Technology, Poland Ph.D. in Systems Analysis, 1977 D.Sc. in Computer Science, 1991 Research Interests Professor Kacprzyk’s research exploits modern computational and artificial intelligence techniques—especially fuzzy logic—to address uncertainty, imprecision, and human-centric reasoning in systems. Core themes include: Multivalued and fuzzy logic for uncertainty modelling Natural-language-based system representation and reasoning Data mining and linguistic summarisation of large data sets for decision support Flexible database querying with imprecise or bipolar user preferences Computational models for group decision making, social choice, voting, and consensus reaching Multistage optimal fuzzy control via dynamic programming These strands converge on real-world applications in ICT, mobile robotics, business analytics, and finance. Scientific Awards & Distinctions 2014 WAC Lifetime Achievement Award in Soft Computing 2013 IFSA Award for Outstanding Academic Contributions and Lifetime Achievement 2010 Medal of the Polish Neural Network Society 2007 IEEE CIS Silicon Valley Chapter Pioneer Award 2006 IEEE CIS Fuzzy Systems Pioneer Award 2006 Kaufmann Award and Gold Medal (SIGEF & FEGI) 2000 AutoSoft Journal Lifetime Achievement Award Fellow, IEEE (2006–) Fellow, IFSA (1997–) Foreign Member, Bulgarian Academy of Sciences (2013–) Full Member, Polish Academy of Sciences (2010–) Foreign Member, Spanish Royal Academy of Economic and Financial Sciences (2007–) Leadership & Service President, Polish Operational and Systems Research Society (PTBOiS), since 2007 Past President, International Fuzzy Systems Association (IFSA), 2009–2011 Member, Administrative Committee (AdCom), IEEE Computational Intelligence Society, since 2010 Member, Award and Fuzzy Pioneer Committee, IEEE CIS, since 2010 Distinguished Lecturer, IEEE Computational Intelligence Society, 2010–2013 He has held visiting appointments in the USA, Italy, UK, Mexico, and China, and serves as Editor-in-Chief of six Springer book series and two journals, while sitting on the editorial boards of approximately 40 further journals.

• Business Process Management
• Process Mining
• Information Systems
• +۳ مورد دیگر

Jan Mendling is a Professor at Humboldt-Universität zu Berlin, Germany, with a former affiliation at Vienna University of Economics and Business, Austria. His research focuses on Business Process Management (BPM), Process Mining, Decision Modeling, and Information Systems. Over 500+ publications highlight his contributions to advancing process-aware systems, including seminal work on process mining techniques, decision model comprehension, and systematizing BPM challenges. He actively participates in leading conferences like BPM, CAiSE, and EDOC, and collaborates with global researchers on topics ranging from sustainability compliance to AI-driven process automation. His work addresses both technical innovations (e.g., timeline-based process discovery, LLM integration) and organizational aspects (e.g., process redesign frameworks, audit risk perception). Recent trends in his publications emphasize interdisciplinary approaches combining AI, sustainability, and ethics with traditional BPM domains. He chairs sessions, delivers keynotes, and contributes to methodological advancements in visual analytics and process complexity measurement.

• Business Process Management
• Design Science Research
• Information Systems
• +۷ مورد دیگر

Jan vom Brocke is a Professor at the University of Liechtenstein, specializing in Design Science Research, Business Process Management, and Information Systems. His work emphasizes the intersection of technology and organizational practices, focusing on process mining, blockchain applications, and digital innovation. He has co-authored over 300 publications and played a pivotal role in shaping the field through initiatives like the DESRIST conference series. Key research interests include design science methodologies, process-aware information systems, and the societal impact of emerging technologies. His contributions span theoretical frameworks for transparency in design research, practical applications of AI and blockchain, and strategies for sustainability transformations. As a conference organizer and academic leader, he has co-edited books and special issues, fostering collaboration across academia and industry. His work bridges technical innovation with organizational context, addressing challenges in digital transformation and complexity management.

• Database Systems
• Semantic Heterogeneity
• Federated Databases
• +۳ مورد دیگر

Dennis McLeod is a Professor at the University of Southern California , specializing in Database Systems , Ontology Engineering , and Semantic Heterogeneity resolution. His work bridges Federated Database Systems and Web Engineering , focusing on component-based architectures, adaptive ontologies, and geospatial data processing. Key Research Areas : Semantic heterogeneity, ontology-driven data mining, mobile web information management, and distributed systems. Collaborations : Extensive partnerships with researchers like Qing Li , Cyrus Shahabi , and Stefania Leone across institutions. Publications (2014-1995) span topics from component-based web engineering to distributed earthquake science , with recent work on geostreaming, social network tag-geotag analysis, and spam filtering using ontologies. His contributions include frameworks for multi-resolution document transmission , object-oriented database sharing , and adaptive query optimization in federated systems. Scientific Impact : Co-chairs and tutorials at major conferences (VLDB, CoopIS, ICDE). Co-edited proceedings for ICWL 2008 and contributed to Expert Database Systems (1989-1991). Pioneered INTERBASE for controlled sharing in federated databases (1990).

Stephanie Ludiمشاهده پروفایل

استاد

• Accessibility in Computing
• Computer Science Education
• Human-Computer Interaction
• +۴ مورد دیگر

Stephanie Ludi is a Professor and Associate Dean for Academic Affairs in the Department of Computer Science and Engineering at the University of North Texas. Her office is located in Discovery Park (A160A), with office hours held Mondays 12:00-1:00 PM and Tuesdays 1:00-2:00 PM. She maintains an active research program focused on accessibility in computing education and assistive technologies. Her research centers on accessibility in computer science education , with specific expertise in designing accessible programming environments for visually impaired users, usability analysis of educational platforms, and integration of accessibility principles into curricula. Key focus areas include block-based programming adaptations, LMS accessibility (particularly Canvas), mobile app quality assessment, and WCAG compliance automation. Her work bridges human-computer interaction, educational technology, and inclusive design principles to address systemic barriers in computing education. Dr. Ludi's publication analysis reveals consistent themes: Prioritization of accessibility in educational technologies across K-12 and higher education Methodological emphasis on empirical usability studies and developer challenge analysis Increasing integration of machine learning techniques for accessibility compliance and review analysis Strong advocacy for inclusive pedagogy in computer science curricula While no specific awards are listed in the provided text, her research impact is evidenced through publications in ACM SIGACCESS conferences and sustained focus on critical accessibility gaps. As Associate Dean for Academic Affairs, she oversees academic programs while maintaining an active research agenda. Her work demonstrates commitment to translating research into practice through curriculum development and institutional partnerships. Current projects indicate exploration of LLM applications for accessibility auditing and continued refinement of accessible programming tools.

• Semantic Web
• Digital Libraries
• Metadata
• +۷ مورد دیگر

Jason A. Clark is a Professor and Head of Research Optimization, Analytics, and Data Services (ROADS) at Montana State University (MSU) Library. He holds an MLS from the University of Wisconsin-Madison (2003), an MA from the University of Vermont (2002), and a BA from Marquette University (1996). His work focuses on semantic web development, metadata systems, and AI ethics in libraries. Clark has led initiatives such as the Open SESMO project and contributed to standards like RO-Crate. He is a recipient of the 2024 MUS Teaching Scholar and MSU Public Engagement Fellow awards. Education: M.L.S., University of Wisconsin-Madison, 2003 M.A., University of Vermont, 2002 B.A., Marquette University, 1996 Key Roles: Lead, Research Informatics (MSU Library, 2020–present) Head, Special Collections & Archival Informatics (2017–2020) Clark’s research explores algorithmic literacy, machine UX, and ethical AI in libraries. His recent work includes leveraging reinforcement learning for scholarship accessibility and developing frameworks for responsible AI in archives. He has authored over 50 publications and led grants funded by IMLS and the Council on Library and Information Resources (CLIR). Awards and Recognition: MUS Teaching Scholar (2024) MSU Public Engagement Research Fellow (2024) Leading Change Institute Fellow (2019) Library Journal Mover and Shaker (2015) Grants and Outreach: Clark oversees projects like the National Forum on Web Privacy and the RE:Search initiative. He chairs the DLF eResearch Network and contributes to open science initiatives such as the Barcelona Declaration on Open Research Information. Labs/Teams: Leads the ROADS team at MSU Library, focusing on data-driven solutions for research, analytics, and library services.

Norberto Díaz-Díazمشاهده پروفایل

استاد

• Artificial Intelligence
• Bioinformatics
• Computational Biology
• +۴ مورد دیگر

Dr. Norberto Díaz-Díaz is a Full Professor in the Department of Computer Science at Pablo de Olavide University. With expertise in Artificial Intelligence and Bioinformatics, he focuses on knowledge extraction and validation from biological databases, semantic similarity in gene networks, and educational technologies. His research spans computational methods for gene network validation, leveraging metabolic pathways and indirect gene-gene relationships. He has developed tools like GFD-Net and GRNCOP2 for Cytoscape, enhancing biological coherence analysis. Recent work explores AI in education, including student performance prediction models and competency development frameworks. Publications from 2011–2025 reflect interdisciplinary trends: 2011–2018: Bioinformatics tools and gene network validation 2019–2022: Semantic similarity, fuzzy gene associations, and digital health observatories 2023–2025: AI ethics, educational analytics, and social interaction analysis

• Cultural Geography
• Urban Geography
• Social Geography
• +۷ مورد دیگر

Associate Professor Kathleen Mee is a cultural geographer at the University of Newcastle, where she serves as Associate Dean for Equity Diversity and Inclusion in the School of Environmental and Life Sciences. She is a member of both the Discipline of Geography and Environmental Studies and the Centre for Urban and Regional Studies, with over two decades of academic experience. An award-winning educator, Mee has received multiple teaching honors including the University of Newcastle Excellence in Teaching Award (1998), Faculty of Science and IT Excellence in Teaching Awards (2008, 2017), and the Vice Chancellor's Award for Teaching Excellence and Contribution to Student Learning (Science) (2017). Her research program focuses on three interconnected themes: (i) the changing nature of social vulnerability in urban and regional areas, (ii) housing for socially vulnerable groups, and (iii) the diverse workings and practices of urban regeneration. Mee employs cultural geography frameworks to examine how places are understood, represented, valued, and experienced across different scales. Her current work utilizes assemblage theory to investigate urban regeneration processes, with particular attention to the role of care in housing transitions from public to community-managed models. Her research methodology combines theoretical analysis with community engagement, producing both academic publications and practical resources for industry partners. Mee's scholarly output reveals a consistent trajectory toward understanding care infrastructures within urban contexts, particularly examining housing as a fundamental component of social support systems. Her recent work has increasingly focused on shadow care infrastructures that sustain marginalized populations in post-welfare cities, with significant attention to the impacts of the COVID-19 pandemic on community support networks. This research bridges housing studies, urban geography, and social policy, contributing to theoretical frameworks while maintaining practical relevance for policymakers and community organizations. Scientific Awards and Recognition: University of Newcastle Excellence in Teaching Award (1998) Faculty of Science and IT Excellence in Teaching Award (2008) Faculty of Science and IT Excellence in Teaching Award (2017) Vice Chancellor's Award for Teaching Excellence and Contribution to Student Learning (Science) (2017) Urban Studies Fellowship, University of Glasgow (2007) As an academic supervisor, Mee has guided 5 PhD students to completion and currently mentors 6 doctoral candidates. Her research program has secured over $1.3 million in competitive funding, including multiple ARC Discovery and Linkage Projects that have fostered strong regional engagement with state agencies in the Hunter and Central Coast regions. These projects have examined public housing management, interagency collaboration, and urban regeneration processes in Newcastle. Mee has also made significant contributions to curriculum development, particularly through her work as Program Convenor of the Bachelor of Development Studies, where she has led efforts to Indigenise the curriculum—a project recognized as best practice both at the University of Newcastle and across the higher education sector.

Mike Mozerمشاهده پروفایل

استاد پژوهشی

• Cognitively Informed Artificial Intelligence
• Machine Learning
• Human Optimization
• +۵ مورد دیگر

Michael Mozer is a Research Professor at the University of Colorado Boulder, affiliated with the Institute of Cognitive Science and the Department of Computer Science. His research bridges human cognition and machine learning, focusing on improving human learning through AI tools and designing cognitively informed AI architectures. He leads the Mozer Lab and collaborates with Google Brain. Key projects include the 'Adaptive House' (self-learning home systems), smart digital textbooks for optimized learning, and the Colorado Optimized Language Tutor. Mozer's research interests span cognitively informed AI, human optimization, cognitive modeling, and intelligent environments. He has contributed to neural networks, reinforcement learning, and the integration of human psychological insights into ML systems. His work on adversarial image manipulations and object-centric learning highlights his exploration of human-machine perception synergies. Teaching focuses on machine learning, neural networks, and computational modeling. He has developed courses like 'Neural Networks and Deep Learning' and mentored numerous students in interdisciplinary projects. Mozer’s affiliations include the Institute for Cognitive Science, the Neuroscience Program, and the Temporal Dynamics of Learning Center.

• Internet of Things
• Machine Learning
• Data Security
• +۴ مورد دیگر

Farhan Amin is a prolific researcher in computer science with a focus on Internet of Things (IoT) technologies, data security, and smart systems. He has published extensively in high-impact journals like IEEE Access and PeerJ Comput. Sci., collaborating with international experts such as Rashid Abbasi and Gyu Sang Choi. His work spans domains including smart city analytics, medical data protection, and next-generation IoT frameworks. Key Contributions: Dynamic trust management in IoT, 3D arthritis detection models, and hybrid data watermarking techniques. Collaborators: Rashid Abbasi, Salabat Khan, Abdul Mateen, Isabel de la Torre Díez. His research bridges theoretical innovation and practical applications, particularly in cybersecurity for IoT, network navigation, and healthcare analytics. Recent publications highlight advancements in zero-knowledge proofs, deep learning for medical imaging, and 6G-enabled healthcare systems. Farhan’s work on anticancer peptide prediction and child custody decision modeling demonstrates interdisciplinary reach. While not explicitly stated, his output suggests a faculty or senior research role at an institution engaged in cutting-edge computational science.

• Artificial Intelligence
• Explainable AI
• Machine Learning
• +۵ مورد دیگر

Isel Grau Garcia is an Assistant Professor in the Information Systems group at Eindhoven University of Technology (TU/e). Her research focuses on advancing Artificial Intelligence, particularly in explainable AI, recurrent neural networks, and bias mitigation. She holds a PhD from Vrije Universiteit Brussel (2020) and has co-authored over 80 peer-reviewed publications. She has supervised three PhD students and received awards including the Best Demo Award at BNAIC 2021 and the Industria Students Award 2024. Her work spans healthcare and business applications, emphasizing interpretable machine learning and trustworthy decision systems. Educational Background: PhD in Computer Science, Vrije Universiteit Brussel (2020) MSc in Artificial Intelligence, Central University of Las Villas (2014) BSc in Computer Science, Central University of Las Villas (2011) Research Interests: Her work addresses AI interpretability, time-series analysis, and ethical AI. She develops methods to enhance transparency in machine learning models and collaborates with institutions like the Interuniversity Institute of Bioinformatics Brussels. Recent projects include ENFIELD (Trustworthy Green AI) and semiconductor demand forecasting using cognitive networks. Grants & Projects: She is a project member of the ENFIELD initiative (2023–2026), focusing on trustworthy and green AI. Her research also involves collaborations with industry partners such as Collibra BV. Labs & Teams: Active in TU/e’s Information Systems group, she leads interdisciplinary teams advancing XAI and healthcare applications. Her lab develops tools like FCM Expert for scenario analysis and pattern classification.

Tullio Salmon Cinottiمشاهده پروفایل

استاد مدعو

• Internet of Things (IoT)
• Smart Agriculture
• Structural Health Monitoring
• +۵ مورد دیگر

Tullio Salmon Cinotti is an Adjunct Professor at the University of Bologna's Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi'. His teaching focuses on logic design and digital systems, including courses like 'Logic Design T' for automation and electronics engineering students. His research spans IoT applications in smart agriculture, structural health monitoring, and energy systems. Key areas include interoperable IoT architectures, semantic integration, wireless sensor networks, and embedded systems. Research interests emphasize IoT toolchain development for condition monitoring, precision irrigation via soil moisture calibration, and drone-based environmental sensing (BEE-DRONES project). He explores semantic-driven agent programming, smart energy grids, and elderly care solutions like the HABITAT project for fall detection and indoor localization. His work integrates RFID, radar, and visual technologies for smart spaces and cultural heritage management. Publications highlight interdisciplinary approaches to electromobility, grid integration, and semantic middleware (e.g., Smart-M3). Teaching materials include course units on sequential networks, combinational logic design, and digital system synthesis. Contact: Email , +39 051 20 9 5421.

• Agricultural Engineering
• Robotics
• Computer Vision
• +۳ مورد دیگر

Xin Wang is an External employee in the department of Agricultural Biosystems Engineering at Wageningen University & Research. Their research focuses on advancing robotics, computer vision, and machine learning applications in precision agriculture. Key areas include plant node tracking, 3D plant reconstruction, and agricultural automation systems. Recent work emphasizes multi-view active vision, self-supervised learning algorithms, and semantic-guided robotics for crop analysis. Research projects include the FlexCRAFT PostDoc initiative, where Wang serves as Principal Investigator. Their contributions span datasets such as 3D tomato peduncle pose estimation and genome sequencing projects. Collaborations involve interdisciplinary teams focusing on agricultural robotics and plant biology, with a strong emphasis on practical applications in greenhouse and orchard environments. Publications highlight advancements in object tracking, next-best-view planning, and machine learning-driven solutions for agricultural challenges like combine harvester optimization and crop ripeness detection. Their work bridges theoretical computer vision techniques with real-world agricultural engineering problems.

• Machine Learning
• Artificial Intelligence
• Data Mining
• +۶ مورد دیگر

Lily Popova Zhuhadar is a Professor of Analytics & Information Systems at Western Kentucky University's Gordon Ford College of Business, where she also serves as Director of the WKU Center for Applied Data Analytics and Coordinator of the Undergraduate Business Data Analytics Program. Her academic journey began with a Master of Sciences in Computer Science from Western Kentucky University in 2004, followed by a Doctor of Philosophy in Computer Engineering and Computer Science from the University of Louisville in 2009. Dr. Zhuhadar's educational background includes: Doctor of Philosophy, Computer Engineering and Computer Science, University of Louisville (2009) Master of Sciences, Computer Science, Western Kentucky University (2004) Her research interests span Machine Learning, Artificial Intelligence, Data Mining, Pattern Recognition, Data Science, Analytics, Semantic Web, Smart Cities, and Computers in Human Behavior. Dr. Zhuhadar's work bridges theoretical computer science with practical applications in healthcare, business analytics, and educational technology. She has made significant contributions to semantically enriched e-learning resources, intelligent tutoring systems, and data analytics for crisis management, with particular expertise in applying analytical techniques to solve complex real-world problems across multiple domains. Dr. Zhuhadar's publication record demonstrates a consistent focus on applying advanced data analytics techniques to solve real-world problems. Her recent work has increasingly focused on healthcare applications, including stroke prediction, diabetes diagnosis, and ecosystem management. She has also maintained a strong interest in educational data mining, particularly in understanding student success pathways in STEM disciplines. Her research methodology often combines semantic web technologies with traditional data mining approaches to create innovative solutions. Her scientific achievements have been recognized through numerous awards: College Faculty Award for Research & Creativity (2023-2024) College Faculty Award for Service (2023-2024) College Faculty Award for Research & Creativity (2022-2023) College Faculty Award for Teaching (2021-2022) University Award for the Most Prolific Grant Proposer (2014-2015) Dr. Zhuhadar has secured over $600,000 in external research funding and more than $100,000 in internal grants. She has served as Principal Investigator on diverse projects ranging from AI applications in healthcare to financial fraud detection. Her mentorship of undergraduate students through the WKU Faculty-Undergraduate Student Engagement program has resulted in numerous collaborative research projects and conference presentations, with over 15 students co-authoring publications and presentations with her in the past two years alone. As Director of the WKU Center for Applied Data Analytics, Dr. Zhuhadar has built a thriving research infrastructure that supports faculty and student research across multiple disciplines. Under her leadership, the Center secured over $101,000 in research grants in 2022-2023, with 33% of funds allocated to support student educational pursuits. She has organized multiple webinar series and research enrichment programs to build data analytics capacity across the university community.