جست‌وجوی استاد و پژوهشگر

George Fergusonمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Human-Computer Interaction
• Temporal Reasoning
• +۸ مورد دیگر

George Ferguson is an Associate Professor in the Department of Computer Science at the University of Rochester . He serves as the Co-Director of the Undergraduate Program and has been recognized with multiple teaching awards, including the Edward Peck Curtis Award for Excellence in Undergraduate Teaching (2023) and the UR Students’ Association Professor of the Year in Engineering and Applied Sciences (2018-2019) . Education: Ph.D. in Computer Science (University of Rochester, 1995) M.Sc. in Computer Science (University of Rochester, 1989) M.Sc. in Computing Science (University of Alberta, 1989) B.Sc. in Mathematics and Computer Science (McGill University, 1987) Research Interests: Ferguson’s work bridges Artificial Intelligence , Human-Computer Interaction , and Medical Informatics . He focuses on Intelligent Conversational Assistants using Natural Language Understanding and Temporal Reasoning for domains like healthcare and logistics. His Dialogue Systems and Knowledge Representation research have led to innovations in Collaborative Problem-Solving and User-Centered Design . Scientific Awards: Outstanding Paper Award at AAAI-2007 Program Co-Chair for AAAI-2004 Invited Participation in NSF-NIH Symposia Teaching: Ferguson has taught a range of courses, from Introductory Programming (Java/Python/JavaScript) to advanced topics like Artificial Intelligence and Programming Language Design . He is also involved in outreach to middle/high school computing education.

• Large Language Models
• Autonomous Driving
• Computer Vision
• +۴ مورد دیگر

Xingcheng Zhou is a Research Assistant at the Technical University of Munich (TUM), affiliated with the Chair of Robotics, Artificial Intelligence and Real-time Systems since 2023. He holds an M.Sc. in Electrical and Computer Engineering from TUM (2021) and previously worked as an Industrial AI Researcher at Siemens. Research Interests: Focus on Large Language Models , Vision Language Models , 3D Environment Perception , and Domain Adaptation in autonomous driving contexts. Publications: Contributions to 3D object detection refinement, sim2real domain adaptation, vision-language models, and dataset development for intelligent transportation systems. Teaching Involvement: Co-supervisor for master's theses and seminars on autonomous agents, perception models, and traffic environment understanding. Advising: Mentoring students on projects including LiDAR-guided monocular detection, world models, and multimodal benchmarks for transportation scenes. Trends in Research: Zhou's work bridges low-light image enhancement with spatial-frequency features, surface-aware frameworks for 3D detection, and weakly-supervised domain adaptation. He contributes to benchmarking spatio-temporal video understanding and evaluating autonomous driving datasets. Supervision and Collaboration: Co-authored key surveys and frameworks with Prof. Alois C. Knoll and peers, focusing on real-time roadside LiDARs, graph-based object relationships, and vision-language integration for traffic analysis.

Jun Liuمشاهده پروفایل

دانشیار

• Transportation Safety
• Responder Safety
• Intelligent Transportation Systems
• +۷ مورد دیگر

Dr. Jun Liu serves as an Associate Professor in the Department of Civil, Construction and Environmental Engineering within the College of Engineering at the University of Alabama. He directs the NextGen Transportation Lab and holds editorial positions including Managing Editor for the Journal of Intelligent Transportation Systems. His affiliations include the Center for Sustainable Infrastructure and Center for Transportation Operations, Planning and Safety. Ph.D. in Civil Engineering, University of Tennessee (2015) M.S. in Statistics, University of Tennessee (2015) M.S. in Transportation Planning & Management, Huazhong University of Science & Technology (2011) B.S. in Transportation Engineering, Huazhong University of Science & Technology (2008) Dr. Liu's research spans transportation safety, connected/automated vehicles, and sustainable mobility systems. His work integrates machine learning with geospatial analysis to address responder safety, travel behavior, and urban planning challenges. Current projects focus on generative AI applications, EV infrastructure, and rural transportation equity. His methodology combines agent-based simulation, spatial modeling, and behavioral pathway analysis to develop practical transportation solutions. Publication trends reveal strong emphasis on machine learning applications in transportation safety (32% of recent works), with significant contributions to connected vehicle systems (24%) and sustainable mobility solutions (18%). His research demonstrates consistent integration of spatial analysis techniques across 78% of publications, with increasing focus on generative AI applications since 2023. Recent work shows growing international collaboration, particularly with Chinese institutions on robotaxi deployment. Inaugural Editorial Board Member, Transportation Research Record 2018 Small Grants Program Award, University of Alabama Distinguished Scientific Paper Award, ITS World Congress Best Reviewer, Journal of Traffic and Transportation Engineering Dr. Liu has secured over $21 million in research funding since 2018, including an NIH/CDC R01 award as lead PI. His 30 projects include 17 as Principal Investigator from NSF, NIH/CDC, US DOT, and state agencies. He mentors numerous graduate students, with recent publications featuring trainees as first authors. Current initiatives include a $2 million CDC/NIOSH project on first responder safety and $16.8 million smart transportation network development in West Alabama. His NextGen Transportation Lab focuses on integrating AI with transportation systems while exploring creative applications through dance and choreography.

Hui Yangمشاهده پروفایل

استاد

• Artificial Intelligence
• Nonlinear Dynamics
• Smart Manufacturing
• +۷ مورد دیگر

Hui Yang is a Professor of Industrial and Manufacturing Engineering and Biomedical Engineering at Pennsylvania State University , holding the Gary and Sheila Bello Chair Professor title. He is affiliated with multiple institutions including the Penn State Cancer Institute , Clinical and Translational Science Institute , and Institute for Computational and Data Sciences . Currently serving as PI and Site Director of the NSF Center for Health Organization Transformation (CHOT) , his career includes leadership roles in professional societies such as IISE Data Analytics and Information Systems Society (President 2017-2018) and INFORMS Quality, Statistics and Reliability (QSR) society (President 2015-2016). As Associate Editor for journals like IISE Transactions , IEEE JBHI , and IEEE Transactions on Automation Science , he maintains strong editorial influence. His research integrates nonlinear stochastic dynamics with sensor-based system informatics to advance both smart manufacturing and healthcare engineering . Recent work explores digital twin technologies , blockchain applications , and AI-driven disease modeling for conditions like Alzheimer's and cardiovascular disease . Key scientific contributions include developing character-level linguistic biomarkers for early dementia detection, self-organizing network representations of cardiac systems, and privacy-preserving neural networks for Industry 4.0 environments. His research group has received significant external funding from NSF , DOE , and NIST to address challenges in heterogeneous manufacturing networks , adaptive failure prognosis , and spatiotemporal optimization . Fulbright Award in Science, Technology and Innovation (2022) IISE Fellow (2021) NSF CAREER Award (2015) Through his Virtual Learning Factory and SCOUT spatiotemporal framework , Yang bridges manufacturing analytics with health informatics , creating cross-domain methodologies for system diagnostics/prognostics , process optimization , and smart health monitoring . His Cross Recurrence Analysis Toolbox provides open-source methods for nonlinear time series analysis.

Massimo Mecellaمشاهده پروفایل

استاد

• Service-Oriented Computing
• Business Process Management
• Process Mining
• +۱۲ مورد دیگر

Massimo Mecella serves as Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, where he leads the Processes, Services and Software Management research group and participates in the CINI National Cyber Security Lab. His academic foundation stems from a PhD in Computer Engineering earned at Sapienza in 2002. His research expertise spans service-oriented computing, business process management, and cyber-physical systems with emphasis on service composition, process mining, and adaptive distributed architectures. Key technical domains include IoT integration, digital twin development, and security frameworks for complex software ecosystems. Recent publications (2024-2025) demonstrate a pronounced shift toward Large Language Model (LLM) integration in business processes and smart manufacturing. Dominant themes include LLM-driven process modeling, multimodal quality control systems, and digital twin implementations for energy management and production optimization. Methodological innovations focus on retrieval-augmented generation (RAG) for service discovery and fuzzy cognitive maturity assessments. His distinguished recognition includes: ICSOC 2013 Most Influential Paper Award (2003-2012 decade) 2017 Best Paper Award As research group leader, Mecella directs projects in smart manufacturing, process mining, and cyber-physical security, with funding typically sourced from EU initiatives and industry partnerships in aerospace, healthcare, and energy sectors. His team maintains active collaborations with aerospace manufacturers through the MICS SPOKE8 project and develops frameworks like SAMBA for human-in-the-loop manufacturing systems. The Processes, Services and Software Management group operates within Sapienza's engineering faculty infrastructure, utilizing specialized labs for CPS/IoT testing and digital twin simulation, with strong ties to the CINI Cyber Security Lab for security validation.

• Adversarial Risk Analysis
• Dynamic Networks
• Human Rights Statistics
• +۲ مورد دیگر

David Banks is Professor of the Practice of Statistics at Duke University, specializing in adversarial risk analysis and network modeling. With an MS in Applied Mathematics (1982) and PhD in Statistics (1984) from Virginia Tech, he held positions at Carnegie Mellon, NIST, USDOT, FDA, and Cambridge University before joining Duke in 2003. Research develops Bayesian methods for security applications including counterterrorism, autonomous systems, and blockchain. Authored 100+ refereed articles and books including the DeGroot Award-winning 'Adversarial Risk Analysis'. Current projects examine MEV distribution in blockchain and defense resource allocation under uncertainty. Honored with the American Statistical Association's Founders Award (2015) and fellowships in AAAS, IMS, and ASA. Leads NSF-funded initiatives including the Statistical and Applied Mathematical Sciences Institute (2018-2022). Editorial contributions include coordinating editor for JASA and founding editor of Statistics and Public Policy. Active in human rights statistics, co-editing 'Statistical Methods for Human Rights' and developing multiple systems estimation for trafficking victim counts.

• Knowledge Management
• Innovation Management
• Entrepreneurship
• +۸ مورد دیگر

Dr. Evangelos Markopoulos is a Lecturer at the University College London School of Management, specializing in Knowledge & Innovation Management, Entrepreneurship, and Futuristic Interactive Technologies. He holds a PhD in MIS Project Management and has extensive industry experience with IBM, Siemens, and Bell Labs. His research focuses on integrating Digital Twins, Metaverse Applications, and ESG Compliance into organizational strategies. He has published 120+ papers and authored a book on Innovative Organizational Cultures. Notable achievements include a Clinton commendation and two Global Social Innovation Awards (HultPrize). His teaching emphasizes real-world industry collaboration through internships and competitions. Education: BSc Computer Science → MSc Computer Science/Artificial Intelligence → PhD MIS Project Management. He has taught at QMUL, UCL, Essex, and others. Research interests span Digital Transformation, Sustainable Leadership, and Gamification in Education. Current projects include VR safety training for maritime sectors and democratic innovation frameworks. Key Research Themes: ESG-SDGs Alignment, Metaverse in Maritime Training, Democratic Organizational Culture Student Impact: Mentored teams to global awards in social innovation Industry Collaboration: Founder of companies in Project Management, Enterprise Engineering, and Innovation Apps

Julio M. Ottinoمشاهده پروفایل

استاد

• Complex Systems
• Granular Matter Dynamics
• Fluid Mixing
• +۵ مورد دیگر

Julio M. Ottino is the Walter P. Murphy Professor of Chemical and Biological Engineering and holds a courtesy appointment in Mechanical Engineering at Northwestern University. He also serves as a Professor of Management and Organizations at the Kellogg School of Management. His research focuses on complex systems, granular matter dynamics, and mixing/segregation phenomena, with applications spanning engineering, geophysics, and environmental science. Ottino’s work bridges theory, computation, and experimentation, addressing challenges in granular flow optimization and segregation control. He is affiliated with the Theoretical and Applied Mechanics Graduate Program and leads the Ottino Research Group. Key research interests include agent-based modeling, network theory, and the interplay between order and disorder in physical systems. His contributions span fluid dynamics, nonlinear systems, and engineering education innovation. Awards: Member of the National Academy of Sciences (2022), G.I. Taylor Medal (2023), and numerous engineering accolades. Publications: Over 200 peer-reviewed articles on granular flows, segregation forces, and mixing dynamics. Education: Ph.D. in Chemical Engineering (assumed based on career trajectory). Ottino’s work emphasizes cross-disciplinary collaboration, as highlighted in his book ArtScience: Creativity in the post-Google Generation . His lab explores cutting-edge topics like machine learning for mixing optimization and ergodic subset analysis in chaotic systems.

Kendra McSweeneyمشاهده پروفایل

استاد

• Human-Environment Interactions
• Cultural and Political Ecology
• Conservation and Development
• +۳ مورد دیگر

Kendra McSweeney is a Professor of Geography at The Ohio State University, affiliated with the College of Arts and Sciences. Her research focuses on human-environment interactions, particularly in Latin America, addressing issues like political ecology, conservation, and the socioecological impacts of drug trafficking. She holds a Ph.D. from McGill University (2000), an M.Sc. from the University of Tennessee (1993), and a B.A. from McGill University (1991). Her work spans decades of field research in Honduras, Central America, and Brazil, examining topics such as climate resilience, indigenous demography, and the environmental consequences of drug policies. McSweeney has led interdisciplinary projects funded by NASA, NSF, and the Open Society Foundations, totaling over $2 million in grants. McSweeney’s research has been recognized with prestigious awards, including AAAS and American Academy of Arts & Sciences Fellowships (2024 and 2023), the Alexander and Ilse Melamid Medal (2020), and the CAPE Distinguished Career Award (2020). She has authored over 70 peer-reviewed articles and edited books, including co-editing Geographical Fieldwork in the 21st Century (2021). Her teaching spans undergraduate courses like Our Global Environment and graduate seminars on fieldwork and political ecology. McSweeney advises students on topics ranging from narco-trafficking’s environmental impacts to indigenous health. She collaborates with international organizations such as the World Resources Institute and UNICEF, bridging academic research with policy and community engagement. Current projects include modeling drug-trafficking networks and their environmental effects, and studying demographic changes among Latin America’s indigenous populations. McSweeney is also a Phi Beta Kappa Visiting Scholar (2024-25), emphasizing her role in public scholarship and education.

• Multi-Agent Systems
• Agent-Oriented Software Engineering
• Hypermedia Multi-Agent Systems
• +۷ مورد دیگر

Rem Collier is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2001) and has held academic roles including Assistant Lecturer (2004), College Lecturer (2005–2018), and his current position since 2018. His research focuses on Multi-Agent Systems (MAS), Agent-Oriented Software Engineering (AOSE), Hypermedia MAS, Digital Twins, and applications in smart agriculture and urban simulation. He leads the CONSUS project (2022–2024) and collaborates on CAMEO (2021–2024). Education: BSc (Pure/Applied Mathematics, University of Bristol, 1994), MSc (Computation, UMIST, 1995), MPhil (UMIST, 1996), PhD (UCD, 2001). Research interests include Agent Factory Framework, ASTRA programming language, and integrating MAS with microservices. Notable achievements include the CIA System Innovation Award 2003 (ACCESS architecture) and Best Paper Awards at EMAS2020 and Mobile Learning 2006. His work spans over 150 peer-reviewed publications and grants such as HOTAIR (2004–2005) and SIFT (2008–2011). Teaching includes modules on Multi-Agent Systems, Distributed Systems, and Security. He has coordinated courses at UCD and the Joint UCD-Fudan program in Beijing and Sri Lanka. Labs/Teams: Active in Hypermedia MAS Simulation, collaborating on projects like CONSUS and CAMEO, emphasizing smart agriculture and distributed knowledge graphs.

Xin Fangمشاهده پروفایل

استادیار

• Power System Optimization
• Cyber-Physical Systems
• Renewable Energy Integration
• +۳ مورد دیگر

Xin Fang is an Assistant Professor in the Electrical & Computer Engineering Department at Mississippi State University, affiliated with the Bagley College of Engineering. His research focuses on power system optimization with uncertainty, cyber-physical dynamic modeling, and renewable energy integration. He holds a Ph.D. from the University of Tennessee, Knoxville, an M.S. from China Electric Power Research Institute, and a B.S. from Huazhong University of Science and Technology. Education: Ph.D., Electrical and Computer Engineering, University of Tennessee, Knoxville, 2016 M.S., Power System Automation, China Electric Power Research Institute, 2012 B.S., Power System Automation, Huazhong University of Science and Technology, 2009 His research interests emphasize cyber-physical systems integration, grid resiliency through multi-timescale modeling, and equitable energy distribution. Recent work addresses challenges in high-renewable grid operations, including dynamic co-simulation frameworks for electricity-transportation networks. He explores innovative solutions for frequency stability, voltage control, and market mechanisms for emerging energy systems. Publications highlight advancements in hybrid power plant optimization, distributed energy resource coordination, and equitable load-shedding methodologies. His work bridges theoretical modeling with practical applications in grid security and renewable integration.

Funda Durupinarمشاهده پروفایل

دانشیار

• Computer Graphics
• Animation
• Psychology
• +۵ مورد دیگر

Funda Durupinar is an Associate Professor in the Department of Computer Science at the University of Massachusetts Boston. Her research bridges computer graphics, animation, and psychology to develop believable virtual humans with nuanced emotional and personality-driven behaviors. Education: B.S. from Middle East Technical University, M.S. and Ph.D. from Bilkent University's Department of Computer Engineering Postdoctoral: Center for Human Modeling and Simulation, University of Pennsylvania Her work focuses on: Multimodal personality expression in virtual agents Nonverbal behavior synthesis for immersive environments Emotion contagion in crowd simulations Integration of psychological models into XR systems Data-driven approaches for realistic avatar animation Ethical considerations in affective computing Recent publications highlight trends in: Personality-embodiment interplay for LLM-based agents Dataset creation for facial expression analysis Motion-driven personality expression frameworks Crowd behavior modeling with affective parameters Leadership Roles: Program Chair for ACM Symposium on Applied Perception (SAP 2025) Organizer of MASSXR workshops at IEEE VR (2023-2025) Editorial Board Member, ACM Transactions on Applied Perception Co-organizer of BostonGFX computer graphics education initiative

Brian Rossمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Intelligence
• Genetic Programming
• +۱۰ مورد دیگر

Brian Ross is a Professor at the Department of Computer Science, Brock University. He holds a BSc (Hon) from the University of Manitoba, MSc from the University of British Columbia, and PhD in Artificial Intelligence from the University of Edinburgh. His research focuses on evolutionary computation , particularly genetic programming , with applications in computational biology , evolutionary design , and computational aesthetics . Education: BSc Computer Science (Hon), University of Manitoba MSc Computer Science, University of British Columbia PhD Artificial Intelligence, University of Edinburgh Research Interests: Computational Intelligence: genetic programming, evolutionary algorithms, multi-objective optimization Evolutionary Design: computational aesthetics, 2D/3D modeling, energy-efficient architecture Applications: computational biology, stochastic process algebra, GPU-based image analysis Article Trends: His recent work combines deep learning with evolutionary algorithms to enhance diversity in agent behavior and design optimization. Earlier studies focused on stochastic modeling of biological networks and procedural texture generation . Collaborations span computational aesthetics, passive solar architecture, and non-photorealistic rendering techniques. Students & Collaborations: He has supervised diverse projects including evolved intelligent agents , passive solar building design , and evolutionary art systems . Notable students include Marshall Joseph (2023), Tyler Cowan (2021), and Sheikh Faishal Basher (2021).

Adil Elfakirمشاهده پروفایل

مدرس ارشد

• Financial Modelling
• Islamic Finance
• Behavioral Finance
• +۵ مورد دیگر

Dr. Adil Elfakir is a Senior Lecturer at Sheffield Hallam University's Department of Finance, Accounting and Business Systems within the College of Business, Technology and Engineering. He joined in January 2018 after extensive roles including Senior Lecturer and Head of Finance Pathway at Cardiff Metropolitan University (2009-2018), Associate Professor at International Institute of Higher Education in Morocco (since 2006), and Research Fellow at LERMA-IFE Lab. His expertise includes financial consultancy, with senior roles at Fineopolis Consulting Institute and IMEX-First Group Maroc. Teaching focuses on advanced finance programs such as MSc Banking and Finance, MSc Wealth Management, and BA Honours Business and Financial Management. Key modules include Financial Derivatives, International Financial Management, and Risk Management. Research emphasizes agent-based simulation, game theory applications in financial contracting, and Islamic finance. He employs methodologies like fuzzy logic and NetLogo simulations to model phenomena in crypto predictability, credit defaults, and venture capital dynamics. Current projects include fintech innovation and AI in finance through his role as Editor-in-Chief of the FinTAF Journal . Collaborations involve institutions like University of Liverpool, Ecole Mohamadia d'Ingenieurs, and Kyonggi University. Supervises doctoral research on CEO personality impacts and digital banking adoption. Engages in peer review for top journals including International Review of Financial Analysis and European Journal of Finance. Leadership includes accreditation oversight for Moroccan higher education programs and fostering academic-industrial partnerships through visiting scholarships at University of Napoli and Ecole Mohamadia des Ingenieurs.

Moira Zellnerمشاهده پروفایل

استاد

• Urban Planning
• Environmental Policy
• Complex Systems Modeling
• +۵ مورد دیگر

Moira Zellner is a Professor of Public Policy and Urban Affairs at Northeastern University’s College of Social Sciences and Humanities. She serves as Director of the MS in Urban Informatics Program and Director of Participatory Modeling and Data Science. Previously, she was an Associate Professor at the University of Illinois at Chicago, where she led the Urban Data Visualization Lab. Her work bridges urban planning, environmental science, and complexity theory, focusing on participatory modeling for collaborative policy design and sustainability transitions. She teaches courses on agent-based modeling, environmental decision-making, and participatory modeling for knowledge co-production. Her research emphasizes stakeholder engagement in complex socio-ecological systems, including green infrastructure planning, water quality management, and climate resilience. She has pioneered tools like conversational assistants for data visualization and innovative approaches to census outreach. Zellner’s academic contributions span interdisciplinary journals and conferences, addressing urban-rural linkages, sustainability science, and transdisciplinary collaboration. Zellner holds a PhD in Urban and Regional Planning from the University of Michigan. She has advised international organizations, government agencies, and NGOs, advocating for equitable urban policies. Her professional service includes roles as a journal reviewer and scientific advisor, reflecting her commitment to bridging academia and practice. Key research themes include: participatory modeling methodologies, socio-environmental systems modeling, urban informatics, and the application of complexity theory to public policy. Recent work explores spatial planning for nature-based solutions, leveraging technology for inclusive civic engagement, and advancing computational tools for decision-making.