جست‌وجوی استاد و پژوهشگر

• Healthcare Design
• Human-Centered Design
• Ergonomics
• +۵ مورد دیگر

Dr. Armagan Albayrak is an academic researcher at the Faculty of Industrial Design Engineering, Delft University of Technology, specializing in Human-Centered Design and Ergonomics . Their work focuses on healthcare innovation, particularly in improving patient experiences, sustainable medical technologies, and extended reality (XR) applications. Albayrak leads research projects like HiPP (optimizing orthopedic patient journeys) and Virtual Patient (surgical training systems), and teaches Health courses since 2023. Their research spans medical device design, dementia care technologies, telemedicine systems, and ICU sustainability. Key projects include redesigning syringe and glove usage in ICUs to reduce environmental impact, developing AR/VR tools for medical education, and co-designing assistive technologies with patients. Albayrak collaborates with healthcare providers, engineers, and interdisciplinary teams to bridge design and clinical practice. They are a 2025 Open Education Ambassador , advocating for accessible learning resources. Publications highlight themes like pediatric hemophilia care, cross-cultural surgical training, and dementia care personalization. Their work emphasizes user-centered approaches, emphasizing how design can enhance healthcare equity, efficiency, and sustainability.

• Generative Programming
• Model-Based Development
• Software System Families
• +۷ مورد دیگر

Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.

Yaguang Zhangمشاهده پروفایل

استادیار بالینی

• Data Science
• Digital Agriculture
• UAV-Aided Wireless Communication Systems
• +۴ مورد دیگر

Dr. Yaguang Zhang is a Clinical Assistant Professor at Purdue University, jointly appointed in the Department of Agricultural & Biological Engineering (ABE) and the Department of Agricultural Sciences Education & Communication (ASEC) . Holding a Ph.D. in Electrical and Computer Engineering from Purdue (2021), he specializes in data science , digital agriculture , and UAV-aided wireless communication systems , with applications in intelligent transportation, proactive road maintenance, and engineering education. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering (Purdue), B.Eng. in Communication Engineering (Tianjin University) Research Interests span cutting-edge domains including: Digital Agriculture: GPS-based field shape generation, product traceability trees, and automated metadata collection for agricultural operations Wireless Communication: Millimeter-wave channel modeling, UAV relay systems, and rural network coverage optimization Smart Infrastructure: Pavement condition assessment tools, sun-shadow simulation for road treatment, and vehicle automation platforms Recent Publications emphasize scalable solutions for agricultural IoT, machine learning in crop monitoring, and interoperable data frameworks. His scientific awards include: 2024 Outstanding Engineering Teacher (Purdue) 2024 ASABE Superior Paper Award 2020 FFAR Student Poster First Prize Multiple NSF/IEEE travel supports Grants from USDA, NSF, INDOT, and industry partners (CableLabs, Nokia) fund projects like tractor autopilot development, rural 6G networks, and pavement monitoring systems. He mentors graduate students in agricultural robotics , data science , and connected vehicle research .

Vinitra Swamyمشاهده پروفایل

پژوهشگر

• Explainable AI
• Machine Learning for Education
• Multimodal Learning
• +۴ مورد دیگر

Vinitra Swamy is a Postdoctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the ML4ED Lab (Machine Learning for Education) and the MLO Lab (Machine Learning and Optimization Group). She holds a PhD in Computer Science from EPFL and a Master's and Bachelor's from UC Berkeley, graduating at 20 as the youngest recipient in UC Berkeley's history. Her research focuses on explainable AI, human-centric machine learning, and education technology. She has held roles as a lead engineer at Microsoft AI (ONNX framework) and served as a lecturer at UC Berkeley and UW Seattle. Vinitra's work bridges technical innovation with societal impact, exemplified by projects like MEDITRON-70B (medical LLMs) and iLLuMinaTE (actionable explanations for students). She has received multiple awards, including the 2024 G-Research PhD Prize and Rising Stars in Data Science recognition. Key contributions include interpretable neural architectures (InterpretCC), bias analysis in LLMs, and multimodal learning systems (MultiModN). Her research emphasizes practical applications in education and healthcare, with a focus on user-centered design and ethical AI practices.

John McNamaraمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Cybersecurity
• Transportation Systems
• +۳ مورد دیگر

John McNamara is an IBM Master Inventor and Advanced Visiting Research Fellow at the University of Sheffield, holding Honorary Professorships at University College London (UCL) and Sheffield Hallam University. He specializes in interdisciplinary innovation across cybersecurity, transportation systems, and artificial intelligence, leveraging technologies like Cloud and Watson for Tech for Good initiatives. His roles include IBM Technical Specialist, IBM Thought Leader, and Open Group Distinguished Technical Specialist, with industry expertise spanning defense, finance, and healthcare sectors. Education: BSc (Hons) in Information Systems from the University of Hull. Research focuses on patentable inventions addressing complex event processing, automated systems optimization, and regulatory compliance. Key innovations include intelligent fuel management systems, automated style-checking frameworks, and goal-directed simulation tools for business processes. His work bridges academic research with real-world industry applications. Awards: IBM Master Inventor IBM Thought Leader Technical Specialist Open Group Distinguished Technical Specialist Collaborates with IBM UK University Programs to develop socially impactful technologies. Active in creating solutions for disease control, banking systems, and defense applications through cross-disciplinary partnerships.

• Healthcare Informatics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Maqbool Hussain is a Senior Lecturer in Computer Science at the College of Science and Engineering. His research focuses on healthcare informatics, artificial intelligence (AI) applications in medical decision-making, and the development of knowledge-based systems for aerospace and healthcare sectors. He has contributed significantly to areas such as digital twin frameworks for critical care workflows, clinical decision support systems, and semantic interoperability in healthcare. Research Interests Hussain’s work spans multiple disciplines, including: Healthcare Informatics and AI-driven medical solutions Knowledge Graphs and Large Language Models (LLMs) in healthcare and aerospace Digital twins for optimizing critical care and aerospace maintenance Data-driven clinical decision support systems Medical data security and interoperability standards Machine learning for text annotation and classification Recent Research Trends Recent publications highlight his focus on integrating advanced technologies like LLMs and digital twins into healthcare and aerospace contexts. His work addresses challenges in critical care workflow optimization, kidney disease diagnosis, and aerospace product maintenance through innovative knowledge graph approaches. He also explores the application of transformer-based models for text analysis and the secure exchange of medical data using biometric methods. Labs and Teams Hussain is affiliated with the College of Science and Engineering, contributing to interdisciplinary research teams focused on healthcare technology, aerospace systems, and AI applications. His collaborations span academic and industry partners, emphasizing practical solutions for healthcare informatics and aerospace engineering challenges.

Ali Emdadمشاهده پروفایل

استاد

• Blockchain Technology
• Cryptoeconomics
• Information Systems
• +۶ مورد دیگر

Dr. Ali Emdad is a Professor and Executive Director of Research Centers at Morgan State University's Graves Business School. He holds leadership roles including Director of the National Fintech Center and Information Science & Systems. With a Ph.D. from Case Western Reserve University and executive training at Harvard/Yale/MIT, he bridges technology, business, and societal impact. His research focuses on blockchain, cryptoeconomics, IT strategy, and risk management. He pioneered academic programs like the B.S. in Supply Chain Management and the Ph.D. track in Information Systems, and established the Center for Blockchain & FinTech and the Center for Data Analytics & Sports Gaming Research. Dr. Emdad has secured $7.5M+ in external funding since 2019, emphasizing industry-academia collaboration. Education and Background: Earned Ph.D. in Information Systems from Case Western Reserve University. Completed executive leadership programs at Harvard, Yale, and MIT. Prior industry experience at Kennecott Corporation. Research & Innovation: Focuses on blockchain's last-mile challenges, trust verification in cryptoeconomics, and data-driven solutions for societal issues. Developed the Capital Markets Lab (since 2015) and the Student Managed Investment Fund (2024). Awards & Recognition: Recipient of Morgan State's highest faculty honor, the Iva G. Jones Medallion, and a 2007 Fulbright Fellow. His work emphasizes inclusivity and innovation, shaping academic excellence through AACSB accreditation standards. Grants & Partnerships: Secured over $7.5 million in funding from corporations and government agencies since 2019, fostering partnerships for applied research and community impact. Labs & Initiatives: Leads the National Fintech Center, Capital Markets Lab, and Student Managed Investment Fund. Co-founded the Center for Data Analytics & Sports Gaming Research.

Bertram Ludäscherمشاهده پروفایل

استاد

• Data and Knowledge Management
• Scientific Workflows
• Data Provenance
• +۴ مورد دیگر

Bertram Ludäscher is a Professor at the School of Information Sciences at the University of Illinois, with affiliate appointments at the National Center for Supercomputing Applications (NCSA) and the Department of Computer Science. He leads the Center for Informatics Research in Science and Scholarship and directs the NSF-funded Euler project focused on logic-based taxonomic alignment. His research emphasizes scientific workflow systems, data provenance, and knowledge representation. Ludäscher co-founded the Kepler workflow system and contributed to DataONE’s provenance initiatives. He previously held roles at UC Davis and the San Diego Supercomputer Center. Education: PhD in Computer Science, University of Freiburg (1998) MS in Computer Science, Technical University of Karlsruhe (1992) Research Interests: Data and knowledge management, scientific workflows, provenance tracking, biodiversity data curation, and taxonomic reconciliation using logic-based methods. Ludäscher’s work bridges computational methods with biological and environmental sciences, focusing on reproducibility and interoperability in data-driven research. Recent Work Trends: His articles address provenance unification in databases, workflow automation recovery, and resolving taxonomic conflicts. Key themes include reproducibility frameworks (e.g., the Whole Tale project), ontology alignment, and scalable workflow systems for diverse scientific domains. Awards: 2018 ProvenanceWeek Best Paper, Google Scholar Classic Papers recognition. Advising & Grants: Leads NSF-funded projects like Euler and Kurator. Active in collaborative initiatives such as DataONE and the Whole Tale. Courses taught include data curation, workflow design, and data cleaning methodologies. Labs/Teams: Directs the Center for Informatics Research in Science and Scholarship and collaborates with NCSA on cyberinfrastructure projects. Key partnerships include the San Diego Supercomputer Center and UC Davis Genome Center.

• Pervasive Computing
• Wireless Sensor Networks
• Healthcare Informatics
• +۳ مورد دیگر

John Herbert is a Senior Lecturer in Computer Science at University College Cork (UCC), Ireland. His research focuses on pervasive computing, wireless sensor networks, and healthcare informatics, with notable projects like the CARA framework for falls assessment in the elderly. He holds a PhD in Computer Science from Cambridge University and has held visiting roles at institutions including SRI International and the University of Cambridge. Education: BSc (Experimental Physics), MSc (Experimental Physics), Postgraduate Diploma (Computer Science) from UCC; PhD (Computer Science) from Cambridge University. Research Grants: Led projects funded by Science Foundation Ireland (€163,726) and the Irish Research Council (€71,250), focusing on cloud computing and healthcare applications. His work emphasizes context-aware systems, data quality in medical environments, and real-time analysis. Selected awards include an International Fellowship from Digital Systems Research Center (1989) and visiting fellowships at Cambridge (2008-2009). Teaching: Courses include Advanced Software Engineering, Formal Methods, and Model-Based Software Development. Outreach: Advisor to award-winning student teams (e.g., IEEE mobile app contest) and collaborator with industry partners in China and Europe.

Matthias Fuchsمشاهده پروفایل

استاد

• Sustainable Tourism
• Big Data Analytics
• Circular Economy
• +۴ مورد دیگر

Matthias Fuchs is a tenured full professor at the Faculty of Economics and Management, Free University of Bozen-Bolzano. His research focuses on sustainable tourism, big data analytics, circular economy frameworks, and strategic management in tourism destinations. He teaches courses such as M-1 Strategic Management and is actively involved in curriculum development for e-tourism and business intelligence. His work integrates quantitative methods like clustering algorithms (e.g., k-Means, DBSCAN) with qualitative analyses to address tourism challenges. Key research areas include real-time tourism monitoring via Google Maps data, socio-economic impact assessments of tourism, and post-Cartesian ontologies challenging conventional economic paradigms. He explores creativity's role in fostering innovative regions through network science and Buddhist philosophy-influenced frameworks. Publications span topics from cultural tourism sustainability in Sweden to the application of convolutional neural networks for Instagram analysis. Despite no explicit awards listed, his contributions to e-tourism curricula and big data methodologies reflect significant scholarly influence. Fuchs advocates for transformative science to align tourism with UN Sustainable Development Goals, emphasizing ethical leadership and justice-oriented socio-economic policies. Teaching responsibilities include guiding students in tourism management, strategic leadership, and destination marketing. His interdisciplinary approach bridges business intelligence, environmental science, and philosophy to address contemporary tourism challenges.

Zhuang Zhengمشاهده پروفایل

مدرس

• Smart Grids
• Building Energy Management
• Renewable Energy Systems
• +۳ مورد دیگر

Dr. Zhuang Zheng is a Lecturer (Assistant Professor) at the School of Computing, Engineering & Digital Technologies, Teesside University since April 2024. Previously, he served as a Postdoc Fellow at the Hong Kong Polytechnic University’s Department of Building Environment and Energy Engineering. He holds a PhD in Architecture and Civil Engineering from City University of Hong Kong (2021). His research focuses on smart energy systems, particularly next-generation residential energy management, grid-building interactions, urban-scale energy modeling, and cyber-physical-social frameworks for low-carbon systems. Education: PhD (2021) from City University of Hong Kong; Postdoc (2021–2024) at Hong Kong Polytechnic University. Key Research Interests: Smart grids, building energy management, renewable energy integration, and decarbonization technologies. Notable contributions include novel energy modeling techniques for peak shaving, voltage regulation, and multi-scale urban energy systems. Articles Trends: His work spans smart building controls, IoT-enabled energy systems, stochastic optimization, and safety risk evaluation. Recent focus areas include distributed control strategies for HVAC clusters and voltage regulation in smart grids. Collaborations: Collaborated with Hong Kong Sun Hung Kai and AECOM on commercial building energy flexibility projects. Actively contributes to international journals and conferences, including chairing sessions at the International Conference on Applied Energy (ICAE). Future Directions: Developing intelligent digitalization for building, power, and transportation sectors to advance smart low-carbon systems through socio-technical integration.

Wynne Chinمشاهده پروفایل

استاد

• Information Systems
• Structural Equation Modeling
• Technology Acceptance
• +۵ مورد دیگر

Wynne Chin is a Professor of Decision & Information Sciences at the C.T. Bauer College of Business, University of Houston. He holds a Ph.D. from the University of Michigan, MBA from the University of Michigan, and degrees from Northwestern University and UC Berkeley. His research focuses on IT adoption, structural equation modeling (SEM), and predictive analytics. He developed the PLS-Graph software, widely used in PLS-based SEM, and has contributed to cross-cultural analysis of IT sourcing and workplace assessment. Education: Ph.D. (Computers & Information Systems, U. Michigan), M.S. (Chemical Engineering, Northwestern), MBA (U. Michigan), B.S. (Biophysics, UC Berkeley). Research interests include IT decision-making, end-user satisfaction, group process measures, and methodological innovations in SEM. He has been recognized globally, ranking 3rd in first-authored articles in MISQ/ISR. Awards include the AIS Fellow, Esther Farfel Award, and AIS Technology Legacy Award. His work bridges IS and statistics, influencing both academic and applied fields. His articles emphasize technology acceptance models, causal modeling, and PLS techniques. Grants and advising contributions are significant but not explicitly detailed here. He has held visiting roles at institutions like the Australian School of Business and is a leader in the PLS research community.

Regan Zaneمشاهده پروفایل

استاد

• Power Electronics
• Transportation Electrification
• Battery Management Systems
• +۳ مورد دیگر

Regan Zane is the David G. and Diann L. Sant Endowed Professor in the Department of Electrical and Computer Engineering at Utah State University. His research focuses on high-efficiency power converters for transportation electrification, battery systems, and microgrid applications. PhD, MS, BS in Electrical Engineering, University of Colorado Boulder IEEE Fellow and recipient of 15+ scientific awards including NSF CAREER and IEEE Bass Award Recent work emphasizes dynamic wireless charging for electric vehicles, second-life battery reconditioning , and high-frequency converter design . Publications span topics in ZVS analysis, resonant topologies, and grid-integrated systems. Key awards include: 2020 Utah Clean Cities Sustainability Partner of the Year 2019 Utah Innovation Award in Clean Technology 2008 IEEE Richard M. Bass Outstanding Young Engineer Mentored 20+ graduate students in power electronics and electrified transportation projects. Led development of USU's EVR Research Facility and contributed to DARPA/MIT collaborations on solid-state hydraulic systems.

Risteski Aleksandarمشاهده پروفایل

استاد

• Telecommunications
• Cybersecurity
• Blockchain Technology
• +۵ مورد دیگر

Professor Risteski Aleksandar holds a Ph.D. in Telecommunications and has been a faculty member at the Faculty of Electrical Engineering and Information Technologies, University Ss. Cyril and Methodius, since 1996. He currently serves as a Professor and has held roles including Vice-Dean for Science and International Cooperation (2008–2016). His research focuses on telecommunications, cybersecurity, blockchain applications in education, and IoT security. He has extensive industry experience, including internships at IBM T.J. Watson Research Center in the U.S. Education: Ph.D. in Telecommunications (2001–2004) M.Sc. in Telecommunications (1997–2000) Dipl. Ing. in Electronics and Telecommunications (1991–1996) Research Interests: Blockchain technology for academic credential verification Cybersecurity in tactical communication systems IoT energy efficiency and reliability Network intrusion detection using deep learning Anti-forgery systems using AI and blockchain Publications Trends: Over 50 publications since 2000, with recent focus on blockchain applications in education, cybersecurity frameworks for 5G networks, and IoT energy optimization. His work bridges theoretical advancements with practical implementations in telecommunication infrastructure. Awards: No specific awards listed, though his contributions to blockchain-based educational systems and cybersecurity research are notable. Advising & Grants: No listed students, but active in research projects funded by industry partnerships. Collaborations include IBM Research and initiatives in Macedonia's telecommunication sector. Labs/Teams: Affiliated with the Institute of Telecommunications at his faculty, focusing on network security and emerging technologies.

Maura R. Grossmanمشاهده پروفایل

استاد پژوهشی

• High-Recall Information Retrieval
• AI Ethics
• Electronic Discovery
• +۳ مورد دیگر

Maura R. Grossman is a Research Professor at the University of Waterloo, specializing in High-Recall Information Retrieval, AI ethics, and legal technology. Her work focuses on ensuring comprehensive information retrieval in high-stakes contexts like electronic discovery in law, healthcare data curation, and medical evidence synthesis. She explores the intersection of artificial intelligence and legal systems, particularly addressing challenges posed by AI-generated evidence and deepfakes in judicial processes. Education: J.D. (Georgetown University Law Center, 1999), Ph.D. (Adelphi University, 1984), M.A. (Adelphi University, 1982), A.B. (Brown University, 1980). Research interests include AI accountability in courts, responsible data science practices, and improving electronic discovery methodologies. Recent work analyzes AI’s role in legal proceedings, ethical AI frameworks, and healthcare data governance. Her publications emphasize validating technology-assisted review (TAR) systems and evaluating generative AI impacts on marginalized communities. Her articles highlight trends in AI’s legal implications, healthcare data sharing protocols, and the need for transparent algorithmic systems in justice contexts. She contributes to TREC tracks, advancing high-recall retrieval techniques for legal and medical document analysis. Notable projects include developing frameworks for unbiased health data sharing and analyzing AI’s effects on marginalized writers. Her work underscores interdisciplinary collaboration between law, computer science, and healthcare to address emerging technological challenges.