جست‌وجوی استاد و پژوهشگر

Xudong Fanمشاهده پروفایل

استادیار

• Urban Water Systems
• Resilience and Sustainability
• Artificial Intelligence
• +۳ مورد دیگر

Xudong (Andrew) Fan is an Assistant Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (UB), part of the School of Engineering and Applied Sciences. His research focuses on urban water systems, resilience and sustainability in water infrastructure, and applications of artificial intelligence in complex networks. He holds a PhD in Civil and Environmental Engineering from Case Western Reserve University (2022), an MS in Structural Engineering from Tianjin University (2017), and a BS in Civil Engineering from Central South University (2014). Dr. Fan's work integrates advanced computational methods with civil engineering challenges, particularly in enhancing infrastructure resilience through AI-driven approaches. His research spans smart city technologies, climate change adaptation, and bio-based solutions for soil stabilization and frost heave mitigation. Notable contributions include developing graph neural networks for spatially embedded network analysis and machine learning models for predicting water infrastructure failures. His publications reflect a strong emphasis on interdisciplinary problem-solving, combining data science with traditional engineering domains. While no specific awards are listed, his prolific output since 2020 highlights his active engagement in cutting-edge research areas such as AI for water systems and sustainable materials innovation.

• Instructional Technologies
• Artificial Intelligence in Education
• STEM Education
• +۳ مورد دیگر

Dr. Serkan Düzgün is an Associate Professor at Gazi University's Faculty of Education, Department of Basic Education, specializing in Classroom Education. He has previously worked as a part-time lecturer at Ankara Hacı Bayram Veli University and Ankara Yıldırım Beyazıt University. PhD, Master's, and Bachelor's degrees from Gazi University Active in instructional technologies, AI in education, STEM, and neuroscience applications Key contributor to Turkey's national education projects and civil society initiatives His research focuses on the integration of artificial intelligence in pedagogical practices, robotic coding platforms for K-12 education, and the cognitive impacts of neuroscience-based teaching methods . Recent work examines distance education challenges during the pandemic, learning style adaptations, and self-regulated learning in virtual environments. Current publications emphasize AI-driven educational tools , technology-enhanced literacy instruction , and virtual classroom dynamics . His 15 most recent articles (2021-2024) span topics like robotic coding in STEM education, emotional intelligence in remote teaching, and AI applications in qualitative research. Dr. Düzgün has conducted 108 projects, advised 3 theses, and actively participates in open-access initiatives and UN Sustainable Development Goals implementation through educational technology. He also played a pivotal role in establishing the "Voice of Turkish" Radio at Yunus Emre Institute.

• Computer-Supported Collaborative Learning (CSCL)
• Artificial Intelligence in Education
• Human-Computer Interaction
• +۳ مورد دیگر

Nikol Rummel is a Professor at Ruhr-Universität Bochum , specializing in Computer-Supported Collaborative Learning (CSCL) , Artificial Intelligence in Education , and Human-Computer Interaction . Her work bridges educational technology with hardware reverse engineering , focusing on AI-orchestrated learning environments and adaptive tools for collaboration. Her research spans AI-orchestration tools ( Pair-Up , Co-Designing Orchestration Support ), collaborative problem-solving ( Learning Alone or Together ), and hardware reverse engineering education ( Promoting Skill Acquisition ). She investigates how multimodal data and adaptive feedback enhance learning outcomes, teacher practices, and emotional regulation. Her publications highlight trends in generative AI for academic writing , collaboration scripts , and cognitive obfuscation in cybersecurity education. Collaborations with researchers like Vincent Aleven, Christof Paar, and Steffen Becker underscore her interdisciplinary approach. Nikol Rummel’s work emphasizes teacher dashboards ( What Information Should CSCL Dashboards Provide? ), dynamic student pairing ( Combining Dialog Acts and Skill Modeling ), and emotional engagement in learning ( How to Enjoy Writing Papers ).

• Knowledge Graphs
• Semantic Web
• Data Quality
• +۵ مورد دیگر

Elena Simperl is a Professor at King's College London, UK, with former affiliations at the University of Southampton and Karlsruhe Institute of Technology. Her work focuses on knowledge graphs, semantic web technologies, and AI-driven data management. She leads research in collaborative knowledge engineering, dataset search, and AI ethics, contributing to projects like the TheyBuyForYou platform for public procurement transparency. Her research interests span knowledge representation, crowdsourcing, and human-AI collaboration. Notable contributions include advancing methods for knowledge graph construction, improving data quality via crowdsourced and automated approaches, and exploring the societal impact of AI systems. She has co-edited major conferences such as ISWC and ESWC, and her work bridges technical innovation with practical applications in public policy and information systems. Key projects include developing frameworks for dataset usability, AI-ready data infrastructure, and systems for fact-checking visual content. Her collaborations span academia and industry, addressing challenges in data governance, misinformation detection, and ethical AI deployment.

Ali Jannesariمشاهده پروفایل

دانشیار

• High-Performance Computing
• Machine Learning
• Software Analytics
• +۵ مورد دیگر

Ali Jannesari is an Associate Professor and Director of the Laboratory for Software Analytics and Pervasive Parallelism (SwAPP Lab) at the Department of Computer Science, Iowa State University. His research focuses on the intersection of High-Performance Computing (HPC) and AI, aiming to advance reliable and efficient software for modern parallel computing platforms. He has held academic and research roles including Senior Research Fellow at UC Berkeley and leadership positions in Germany's Technical University of Darmstadt and RWTH Aachen University. He holds a Habilitation in Computer Science (2016, TU Darmstadt), PhD (2010, KIT), and M.S. (2005, University of Stuttgart). Education: Habilitation in Computer Science, Technical University of Darmstadt, Germany (2016) Ph.D. in Computer Science, Karlsruhe Institute of Technology (2010) M.S. in Computer Science, University of Stuttgart (2005) Research Interests: High-Performance Computing (HPC), Machine Learning, Parallel Computing, Software Analytics, AI-driven compiler optimization, federated learning, and cross-language code analysis. His work bridges HPC and AI to enhance computational efficiency and scalability in data-driven applications. Recent Contributions: Leading research in GNN-based code parallelization (AutoParLLM), federated multimodal learning, and HPC performance optimization via graph-based methods. His lab's work has been published in top venues like NAACL, ICS, and NeurIPS. Lab & Team: The SwAPP Lab develops tools for software analytics and pervasive parallelism, with a focus on HPC-AI integration. Current projects include optimizing distributed training systems and improving code migration with LLMs.

• Machine Learning
• Computer Science
• Medical Informatics
• +۷ مورد دیگر

Yan Li is a researcher with extensive contributions across interdisciplinary domains including Machine Learning , Signal Processing , and Environmental Science . Affiliated with institutions such as the University of Southern Queensland , Hebei University , and Shandong University , Li's work spans applications in Medical Informatics , Remote Sensing , and Operations Research . Recent publications highlight expertise in Deep Learning (e.g., hyperspectral classification, image fusion), Stochastic Modeling (e.g., chemotaxis models), and Federated Learning (e.g., vertical federated fuzzy clustering). Collaborative projects include 3D Reconstruction , Smart Grid Security , and Landslide Monitoring using satellite data. Li's 2025 work demonstrates a focus on Medical Imaging (segmentation algorithms with dual-frequency decoupling), AI in Education (ChatGPT adoption), and Industrial IoT (GPU-accelerated vessel trajectory visualization). While no explicit academic rank is provided, their prolific publication record suggests a Researcher role.

Jessica Sze Yin Hoمشاهده پروفایل

دانشیار

• Digital Marketing
• Social Media Marketing
• E-commerce
• +۴ مورد دیگر

Jessica Sze Yin Ho is an Associate Professor and Senior Fellow of the Higher Education Academy at Heriot-Watt University , where she serves in the School of Social Sciences as Associate Head and Programme Director of MA (Hons) Marketing in the Department of Marketing and Operations . She is a prolific researcher in digital marketing, social media, and sustainable consumption, with over 20 publications and multiple international awards. PhD in Marketing (Multimedia University, Malaysia) MPhil in Management (Multimedia University, Malaysia) BBA in Marketing (Multimedia University, Malaysia) Research Interests span Digital Marketing , Social Media Strategy , E-commerce , Sustainable Consumer Behavior , and Service Quality , with a focus on technology adoption and higher education quality. Her recent work explores Live Streaming Commerce , TikTok’s role in Cultural Heritage Promotion , and the Dark Side of Celebrity Endorsements . Her 15 most recent publications (2025–2020) analyze audience engagement , privacy dynamics in virtual streaming , sentiment analysis , and augmented reality applications across sectors like museums, tourism, and finance. Awards include multiple Best Paper and Best Reviewer recognitions from global marketing conferences. Collaborations include industry-funded projects on talent management and services marketing . She also mentors colleagues toward Senior Fellow of AdvanceHE status and contributes to UN Sustainable Development Goals through research on sustainable consumption and education.

Winslow Burlesonمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Robotics
• Assistive Technology
• +۵ مورد دیگر

Winslow Burleson is a Professor at the University of Arizona's School of Information, specializing in Human-Computer Interaction (HCI), Robotics, and Assistive Technology. His research focuses on developing innovative systems for education, healthcare, and marine engineering. Notable projects include the DRESS system for dementia care, CrowdMuse for collaborative creativity, and underwater robotics interfaces. He has received the James Chen Annual Award for Best Journal Article (2012) and leads interdisciplinary teams in cyberlearning and adaptive tutoring systems. Education background includes advanced studies in computer science and engineering, though specific details are not provided. His work integrates robotics, affective computing, and smart environments to address real-world challenges such as aging, education, and environmental exploration. Research interests span robotics applications in education (e.g., co-robotic learning agents), assistive technologies for independent living, and multimodal learning environments. His contributions include adaptive systems for creative crowdsourcing, emotion-aware tutoring platforms, and underwater human-robot interaction frameworks. Current projects emphasize scalable crowd ideation tools and sensor-driven behavior change interventions. Awards include recognition for impactful journal contributions, while grants fund initiatives like cyberlearning with teachable robots and precision oncology IT tools. Advising and grant activities are central to his academic contributions, though specific student names are not listed. Collaborations involve cross-disciplinary teams in engineering, healthcare, and arts to create impactful technologies. Burleson's lab focuses on developing responsive emotive systems, wearable assistive devices, and immersive multimedia applications. Ongoing work explores scalable solutions for dementia support, marine technology interfaces, and creative human-computer interaction paradigms.

• Transportation Planning
• Traffic Engineering
• Public Transport Integration
• +۹ مورد دیگر

Assoc. Prof. Dr. Murat Ergün currently serves at Istanbul Technical University's Faculty of Civil Engineering, Department of Civil Engineering, specializing in transportation planning, traffic engineering, and sustainable infrastructure. He holds a PhD in Transportation Engineering and has contributed extensively to urban mobility, pavement engineering, and risk assessment in transportation systems. PhD (1993): Transportation Engineering, Istanbul Technical University MSc (1985): Transportation Engineering (Mixed), Istanbul Technical University BSc (1981): Civil Engineering, Uludağ University His research focuses on GIS integration for spatial transport analysis, centroid optimization in planning, and sustainable asphalt materials. Recent projects include risk assessment for urban roadside assets and dynamic creep analysis of polymer-modified asphalt. Collaborations with İ. Adalıoğlu dominate his 2025 publications. Key projects span from 2005 BAP initiatives to 2025 studies on autonomous vehicles in public transport. Though no specific scientific awards are listed, his Scopus h-index of 8 reflects significant scholarly impact.

• Control Systems
• Mechatronics Design
• Signal Processing
• +۴ مورد دیگر

Mohammad Narimani is a Senior Lecturer in the Department of Mechatronic Systems Engineering at Simon Fraser University’s Faculty of Applied Sciences. He holds a PhD in Mechatronics Engineering from King's College London (2011), a MASc in Electrical Engineering from Isfahan University of Technology (2001), and a B.Sc. in Electrical Engineering from Sharif & Isfahan University of Technology (1997). His teaching focuses on core mechatronic disciplines, including Control Theories, Mechatronic Design, Signal Processing, and Digital Logic Circuits. Dr. Narimani’s research spans multiple domains: Biomedical Engineering : Developing machine learning models for healthcare applications like blood pressure estimation and spinal injury detection. Control Systems : Stability analysis in fuzzy logic-based systems and nonlinear control theory. Renewable Energy : Investigating fuel cell dynamics during oxygen starvation to improve efficiency and safety. Machine Learning : Multimodal sensing for activity recognition and physical monitoring systems. Recent work emphasizes practical applications such as wearable sensor integration for health monitoring and smart home systems. His articles reflect a trend toward combining traditional engineering principles with modern AI-driven methodologies. Advising and grants: No formal advisees listed, but his courses (e.g., MSE 381 Feedback Control Systems, MSE 250 Electric Circuits) suggest involvement in student mentorship. No specific grants mentioned in available texts. Lab affiliations: Active within the Faculty of Applied Sciences’ research ecosystem, though specific lab names are not detailed in the provided materials.

• Virtual Reality (VR)
• Human-Computer Interaction (HCI)
• Accessibility in Technology
• +۳ مورد دیگر

John Quarles is a Professor at the University of Texas at San Antonio, specializing in Virtual Reality (VR) and Human-Computer Interaction. His research focuses on accessibility in immersive technologies, cybersickness mitigation, and inclusive design. He has contributed over 100 publications across top venues like IEEE VR, ISMAR, and IEEE Transactions on Visualization and Computer Graphics. His work addresses challenges faced by users with disabilities, such as balance impairments and mobility limitations, through innovative feedback systems and adaptive algorithms. Quarles has co-authored influential papers on cybersickness prediction, VR accessibility for persons with Multiple Sclerosis, and disability simulations to reduce societal bias. He has held leadership roles including Program Chair for IEEE VR 2023, demonstrating his influence in academic and industrial VR communities. His research spans interdisciplinary applications in healthcare, education, and rehabilitation, with notable collaborations on datasets like 'Mazed and Confused' and frameworks like SmoothRide. Key themes include multimodal feedback methods, user-centric design principles, and leveraging AI for personalized VR experiences.

Haiming Liuمشاهده پروفایل

دانشیار

• User-Centred Interactive Information Access
• User Preference and Behaviour Modelling
• Multimedia Information Retrieval
• +۳ مورد دیگر

Dr. Haiming Liu is an Associate Professor at the School of Electronics and Computer Science (ECS) at the University of Southampton. She leads the Centre for Machine Intelligence and contributes to research, teaching, and supervision across undergraduate and postgraduate levels. Her work focuses on user-centered interactive information access technologies, integrating interdisciplinary approaches from Computer Science, Psychology, and Social Sciences. Dr. Liu earned her PhD in 2010 from The Open University’s Knowledge Media Institute, researching user interaction with content-based image retrieval systems. Her career includes roles at the University of Bedfordshire and University of Central Lancashire before joining Southampton in 2022. Her research spans applications in E-Health, E-Learning, and Digital Humanities, emphasizing user preferences and behavior modeling. She currently supervises six PhD students and actively recruits new candidates. She is also involved in projects like the 'Image-based Conversational Search for Users with Intellectual Disability.' Dr. Liu’s teaching responsibilities include computer science modules, and she maintains an active research profile with publications in journals like Materials Characterization and conferences on inclusive design.

Vanessa Echeverriaمشاهده پروفایل

مدرس

• Learning Analytics
• Artificial Intelligence in Education
• Multimodal Data Analysis
• +۳ مورد دیگر

Vanessa Echeverria is a Lecturer in the School of Computing Technologies at RMIT University, Australia, and an Assistant Professor at Escuela Superior Politécnica del Litoral (ESPOL), Ecuador. She holds a PhD in Information Technology from the University of Technology Sydney (2020), a Master’s in Computer Science from KU Leuven (2012), and a Bachelor’s in Computer Science from ESPOL (2004). Her research focuses on human-centred AI, learning analytics, and educational technologies, emphasizing the design of AI-driven tools for stakeholders in education and healthcare. She has held postdoctoral roles at Monash University and Carnegie Mellon University. Her work integrates multimodal data analysis, generative AI, and human-centred design to enhance educational outcomes and healthcare simulations. Research Interests: Learning analytics, multimodal data, AI in education, human-centred AI systems, and collaborative learning environments. Her projects include developing dashboards like TeamVision for healthcare simulations and TeamTeachingViz for team-based reflection. She also explores ethical considerations in AI and learning analytics through frameworks like VALA/AID and FATE in MMLA . Teaching: Teaches Python Programming (COSC3106) at RMIT, emphasizing practical coding skills and their application in computational problem-solving. Publications: Over 80 outputs since 2020, including high-impact journal articles in Computers & Education and conference papers at CHI and LAK. Recent work addresses generative AI adoption policies, data storytelling in dashboards, and human-AI collaboration in thematic analysis. Collaborations: Engages in transdisciplinary research across institutions, including Monash University’s Centre for Learning Analytics and partnerships with healthcare and educational institutions globally.

• Transportation Engineering
• Intelligent Transportation Systems
• Infrastructure Resilience
• +۷ مورد دیگر

Sean Qian is a Professor at Carnegie Mellon University (CMU), jointly appointed in the Department of Civil and Environmental Engineering, Heinz College of Information Systems and Public Policy, and the Department of Electrical and Computer Engineering. He directs the Mobility Data Analytics Center (MAC) and co-founded TraffiQure Technologies to commercialize AI-driven infrastructure solutions. His research focuses on dynamic network modeling, intelligent transportation systems, climate resilience, and infrastructure interdependency. Supported by NSF, U.S. DOT, and industry partners, his work integrates AI, big data, and policy analysis to address urban mobility challenges. Education: PhD in Civil Engineering (UC Davis, 2011), MS in Statistics (Stanford, 2012), and dual MS/BS in Civil Engineering (Tsinghua University, 2006/2004). Research emphasizes smart cities, EV integration, cybersecurity for infrastructure, and equity in mobility policies. He serves on editorial boards for Transportation Research journals and TRB committees. Awards include the NSF CAREER Award (2018) and Greenshields Prize (2017). Grants and collaborations include projects with Fujitsu, IBM, and state agencies, addressing curbside management, climate adaptation, and rural mobility. His lab develops tools like the Rural Access Mobility Platform and social digital twin technologies for infrastructure resilience.

Theo Araujoمشاهده پروفایل

استاد

• Automated Decision-Making
• Digital Society
• Conversational Agents
• +۴ مورد دیگر

Prof. Theo Araujo is a Full Professor of Media, Organisations and Society at the University of Amsterdam's Department of Communication Science, and Scientific Director of the Amsterdam School of Communication Research (ASCoR). He leads the Digital Data Donation Infrastructure (D3I) consortium, co-directs the Trust in the Digital Society research priority area, and is a senior researcher in the Public Values in the Algorithmic Society (AlgoSoc) program. His research focuses on AI's societal impacts, computational social science methodologies, and data donation frameworks. Key roles include coordinating multi-university initiatives and advising on digital ethics. Research interests emphasize automated decision-making, conversational agents, and digital inequality. He has pioneered tools like the Conversational Agent Research Toolkit and OSD2F framework. His work bridges communication science with computational methods, addressing challenges in data collection, algorithmic transparency, and human-AI interaction. Recent studies explore chatbot persuasion mechanisms, public trust in AI systems, and cross-cultural consumer behavior. He has published extensively on brand engagement, media analytics, and the ethical implications of automated systems. Current projects include smart speaker data donation studies and hybrid methods for health communication research. Grants and collaborations involve EU-funded initiatives and partnerships with Dutch universities. His lab work focuses on developing ethical AI applications and improving digital trace data methodologies. Future directions include advancing participatory data donation practices and mitigating algorithmic biases in automated decision-making systems.