جست‌وجوی استاد و پژوهشگر

Mehwish Nasimمشاهده پروفایل

مدرس ارشد

• Complex Systems
• Social Network Analysis
• Human-Centric Cyber Security
• +۵ مورد دیگر

Mehwish Nasim is a Senior Lecturer at The University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing's Department of Computer Science and Software Engineering. She previously held roles at the University of Adelaide, Flinders University, and CSIRO. As the Social Media Coordinator for the Australian Mathematical Society (AustMS), she bridges academic communication and public engagement. Her research focuses on complex systems, social network analysis, cyber security, and health analytics. Current projects include AI-driven detection of misinformation, polarization modeling on social media, and predictive models for population-level events. She also explores decision-making frameworks using complex systems methodologies. Recent publications highlight her work on large language models in social science, video moment retrieval, and mental health surveillance. Her contributions span computational methods for social good, environmental prediction, and ethical AI applications. Awards: Shining Star in AI (WiTWA 2023), PMC School Special Commendation (2023), Anne Penfold Street Award (2023) External Roles: Adjunct Lecturer at Flinders University and University of Adelaide; Visiting Scientist at CSIRO-Data61; Associate Investigator at ARC Centre of Excellence for Mathematical and Statistical Frontiers Activities: Organized the 1st International Workshop on Multimodal Content Analysis for Social Good (2023); Public outreach on cybersecurity and data science She actively supervises PhD students in areas like AI ethics and social network dynamics, contributing to UWA's research degree opportunities.

Andy Huntمشاهده پروفایل

استاد

• Interactive Sonification
• Human-Computer Interfaces
• Signal Processing: Audio
• +۳ مورد دیگر

Professor Andy Hunt is a faculty member in the School of Physics, Engineering and Technology at the University of York. His academic rank is Professor, and he holds roles such as Chair of the Engineering Teaching Committee and Stream Leader for Music Technology programmes. He has a PhD in Music Technology and extensive industry experience in electronic engineering. His research focuses on Interactive Sonification, the science of displaying data as sound with real-time user interaction. Notable contributions include co-founding the Interactive Sonification Workshop and co-editing the Sonification Handbook . His work spans healthcare applications (e.g., biomedical data analysis), music therapy, and engineering education. Key publications include over 50 articles, with a focus on sonification systems, human-computer interfaces, and audio technologies. He has received the RAE Engineering Teaching Prize 2007 for contributions to engineering education. Teaching responsibilities include courses on Audio Technology, Multimedia Sound Design, and iOS Programming. He emphasizes practical project management and student success through his authored books like Surviving and Thriving at University and Managing your Project . Grant funding includes EPSRC and EU projects, such as Improved Data Mining through an Interactive Sonic Approach and Sonification of cervical smear data . His work addresses diverse applications, from disability support in music to data analysis in sports and healthcare.

• Human-Computer Interaction
• Mobile Computing
• Educational Technology
• +۳ مورد دیگر

Alistair Morrison is a Lecturer in Computing Science at the University of Glasgow, specializing in Human-Computer Interaction (HCI), mobile computing, and educational technology. His research focuses on app usage analysis, user behavior modeling, and ethics in data-driven systems. He has contributed to studies on work-based learning in software engineering, digital phenotyping, and large-scale mobile HCI deployments. His work bridges academia and industry, addressing challenges in educational technology such as skill transfer between university and workplace environments. He has explored topics like student engagement in computing science, ethical guidelines for mobile app trials, and screen time tracking. Morrison's research often involves collaborations with international conferences like CHI and IEEE, resulting in over 40 peer-reviewed publications. Key areas of interest include improving consent processes for data collection, analyzing smartphone usage patterns, and designing systems that foster professional competency development. His recent projects emphasize practical applications in software engineering apprenticeships and the ethical implementation of digital tracking technologies.

• Machine Learning
• Human-Computer Interaction
• Dynamic Systems
• +۵ مورد دیگر

Professor Roderick Murray-Smith is a Professor of Computing Science at the University of Glasgow, affiliated with the School of Computing Science. He leads the Inference, Dynamics and Interaction Research Group and the Information, Data & Analysis Section . Previously, he held positions at institutions including MIT, Technical University of Denmark, and Daimler-Benz Research. His research focuses on Closed-loop Data Science , Machine Learning in Science , and Mobile Human-Computer Interaction . Notable projects include quantum imaging, music recommender systems, and collaborations with industry leaders like Nokia and Samsung. He served as Director of the SICSA research pool and founding Head of the Information, Data & Analysis Section. Key technical contributions span medical image segmentation , neural network architectures , and biomechanical VR simulations . His work bridges control theory, machine learning, and interactive systems, emphasizing real-world applications in healthcare, robotics, and mobile devices.

Tung Kieuمشاهده پروفایل

استادیار

• Data Science
• Time Series Analysis
• Forecasting
• +۴ مورد دیگر

Tung Kieu is a Tenure Track Assistant Professor in the Department of Computer Science at Aalborg University (Denmark), affiliated with The Technical Faculty of IT and Design and the Daisy Center for Data-intensive Systems. His research focuses on data engineering, time series analysis, anomaly detection, and machine learning applications in traffic forecasting and smart systems. Education: Ph.D. in Computer Science (Awarded May 2021). Research interests include time series forecasting, traffic modeling, robust autoencoder architectures for anomaly detection, and spatio-temporal data analysis. His work contributes to UN Sustainable Development Goals related to smart cities and infrastructure. Recent publications explore bias mitigation in text-video retrieval (BiMa), topology-aware traffic forecasting (TEAM), and stochastic routing in uncertain road networks. His frameworks emphasize lightweight algorithms (LightTS), causal relational learning, and continual calibration for quantized models (QCore). Collaborations involve international teams in data management and AI, with notable work on ensemble methods, explainable AI, and transfer learning in smart building systems.

• Deep learning
• Multimedia
• Applied statistics and mathematics
• +۸ مورد دیگر

Dacheng Tao is a Professor of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2010 and holds an ARC Future Fellowship since 2013. His work bridges statistics, mathematics, and advanced data analytics, with a focus on machine learning, computer vision, and multimedia technologies. Research Interests : Deep learning, computer vision, image processing, data mining, pattern recognition, geoinformatics, and video surveillance. Academic Contributions : Author of one monograph and over 400 publications in prestigious journals and conferences, with multiple best paper awards, including the 2014 ICDM 10 Year Highest Impact Paper Award. Honors and Recognition : 2015 ESI Highly Cited Researchers in Engineering and Computer Science. 2015 Australian Scopus-Eureka Prize, ACS Digital Disruptors Award (Gold Disruptor), and UTS Vice-Chancellor’s Medal for Exceptional Research. Fellowships in IEEE, IAPR, SPIE, OSA, IET, and BCS. Leadership and Service : Guest editor for 10+ special issues, editor for 10+ journals (including 7 IEEE Transactions), 4 conference keynote speeches, 60+ conference chairmanships, and service on 150+ major conferences and 60+ international journals.

Luo Jieboمشاهده پروفایل

استاد

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۴ مورد دیگر

Jiebo Luo is a Professor of Computer Science at the University of Rochester, where he has held this position since 2014. He earned his BS and MS in Electrical Engineering from the University of Science and Technology of China (1989 and 1992) and a PhD in Electrical Engineering from the University of Rochester (1995). Prior to academia, he spent 15+ years at Kodak Research Laboratories as a Senior Principal Scientist. His research focuses on computational social science, natural language processing, digital health, computer vision, data mining, and multimedia. Dr. Luo’s work has been recognized through numerous awards, including the ACM SIGMM Technical Achievement Award (2021), Fellowships from ACM, AAAI, IEEE, IAPR, and SPIE. He has authored over 500 peer-reviewed papers, holds 90+ patents, and serves as Editor-in-Chief of the IEEE Transactions on Multimedia. He actively contributes to conference organization (e.g., ACM Multimedia, CVPR) and editorial roles for top journals. Key contributions include pioneering work in social media analytics, sentiment analysis, and digital health, as well as foundational research in multi-label classification and action recognition datasets like UCF 101. His labs and collaborations span the Goergen Institute for Data Science and the Greater Rochester Data Science Industry Consortium.

Srirangaraj Setlurمشاهده پروفایل

پژوهشگر

• AI
• Machine Learning
• Pattern Recognition
• +۶ مورد دیگر

Srirangaraj (Ranga) Setlur is a Principal Research Scientist and Co-Director of the Center for Unified Biometrics and Sensors (CUBS) at the University at Buffalo. He also serves as the Associate Director of Community Engagement at the Institute for Artificial Intelligence and Data Science. His research focuses on AI, Machine Learning, Pattern Recognition, Computer Vision, and Information Retrieval with applications in biometrics, document analysis, and healthcare. Education: MS in Industrial Engineering, University at Buffalo (1995) Research Interests: Development of AI-driven systems for biometric authentication (e.g., fingerprint, facial recognition) Design of datasets for chart analysis (CHART-Info), gait recognition (DIOR), and cross-domain fingerprint analysis Applications in healthcare diagnostics (e.g., dyslexia screening via handwriting analysis) Advancements in multimodal fusion (e.g., audio-visual, physiological signals) Recent Research Trends: His recent work emphasizes cross-domain learning (e.g., Ridgeformer), sparse feature aggregation (Proxyfusion), and AI applications in social robotics (AutoMisty). He consistently addresses challenges in unconstrained environments and under-represented data scenarios. Awards: Senior Member, IEEE 2019 ICDAR Best Student Paper Award (F. Xu) 2010 IBM Best Student Paper Award (X. Peng) UB Visionary Innovator Award Labs/Teams: Leads research teams in CUBS and the Institute for AI & Data Science, focusing on biometric systems, surveillance optimization, and multimodal AI applications.

Ge Jinمشاهده پروفایل

استاد

• Computer Graphics
• Virtual Reality
• Computer Animation
• +۶ مورد دیگر

Ge Jin is an Associate Dean of Graduate Studies and Professor of Computer Information Technology and Graphics at Purdue University Northwest's College of Technology. His research focuses on computer graphics, virtual reality, medical visualization, and serious games. He has led federally funded projects including NSA/NSF grants and industry-sponsored initiatives. Education: D.Sc. in Computer Science (George Washington University) M.S. in Computer Science (Seoul National University) B.S. in Computer Science (Peking University) Research Interests: Jin’s work spans virtual reality applications in education and healthcare , cybersecurity training through games , and medical visualization systems . His projects integrate technologies like VR, game engines, and machine learning for practical solutions in safety education, digital manufacturing, and disaster management. He emphasizes experiential learning through immersive environments and interdisciplinary collaboration. Recent Trends in Publications: His recent work (2018-2020) highlights cybersecurity education via games, VR-based training modules, and NLP-driven health informatics. Earlier research includes medical visualization tools for surgery and disaster management systems leveraging 3D modeling and cluster computing. Awards & Recognition: Teaching Incentive Program Award (Purdue University Northwest) Chanute Prize (Society of Innovators of Northwest Indiana) Outstanding Faculty for Undergraduate Education (College of Technology) Grants & Advising: Jin has secured over $2M in grants including NSF SFS Expanding the Pipeline and NSA Curriculum Development grants. He advises teams on cybersecurity game development and VR lab projects, fostering collaborations across departments and industries. Labs & Teams: His work involves interdisciplinary teams working on VR safety simulations, medical visualization platforms, and cybersecurity education tools. Current efforts focus on scaling VR training modules for K-12 and higher education audiences.

Wenting Zouمشاهده پروفایل

استادیار

• Educational Technology
• Learning Analytics
• Social Media Literacy
• +۴ مورد دیگر

Dr. Wenting Zou is an Assistant Professor in the Department of Educational Psychology, Counseling, and Special Education at Penn State University's College of Education. Her research focuses on educational technology, learning analytics, and digital literacy education. She investigates how interactive tools like chatbots, MOOC platforms, and augmented reality can enhance learning outcomes and address challenges such as cyberbullying and dark pattern awareness. Her work emphasizes cross-cultural studies, teacher professional development, and at-risk student engagement. Notable projects include developing social media literacy inventories, analyzing MOOC participant dynamics via social network analysis, and designing problem-based learning environments with multimedia integration. Dr. Zou collaborates with educators and youth to co-create solutions for real-world educational challenges. Her publications span topics from chatbot-assisted cyberbullying prevention to the effectiveness of wikis in project-based learning. While no scientific awards are listed here, her contributions reflect a commitment to bridging technology and pedagogy for equitable education access. Advising and grant activities are not explicitly detailed in the provided text, though her CV indicates involvement with longitudinal studies and collaborative design projects. Dr. Zou's work often intersects with global educational initiatives, particularly in the global South.

Huei-Yen (Winnie) Chenمشاهده پروفایل

دانشیار

• Human-Machine Interactions
• Cognitive Engineering
• Driver Behavior and Safety
• +۴ مورد دیگر

Huei-Yen (Winnie) Chen is an Associate Professor in the Department of Industrial and Systems Engineering at the University at Buffalo, within the School of Engineering and Applied Sciences. Her research focuses on Human-Machine Interactions, Cognitive Engineering, Driver Behavior and Safety, and Human Factors in Healthcare. She leads the Applied Cognitive Engineering Lab, exploring how to improve safety through better understanding of human behavior in complex systems like automated vehicles and healthcare settings. Dr. Chen's work integrates naturalistic driving data, simulation studies, and interdisciplinary approaches to address issues such as driver distraction, automation reliability, and decision-making under uncertainty. Her recent studies include manipulating auditory feedback in automated driving systems and analyzing crash severity using large-scale driving datasets. Her research has been published in journals such as Transportation Research Part F , IEEE Transactions on Human-Machine Systems , and Applied Network Science . She collaborates with experts in signal processing, psychology, and healthcare to advance safety and efficiency in socio-technical systems.

Le Gruenwaldمشاهده پروفایل

استاد

• Database Management
• Information Privacy and Security
• Mobile and Distributed Databases
• +۹ مورد دیگر

Dr. Le Gruenwald is the David W. Franke Professor and Samuel Roberts Noble Foundation Presidential Professor at the School of Computer Science, University of Oklahoma. She also served as Program Director for Data Management Systems at the National Science Foundation (NSF) and held roles including Director of the University of Oklahoma's School of Computer Science. Her academic journey includes a PhD from Southern Methodist University (1990), an M.S. from the University of Houston, and a B.S. in Physics from the University of Saigon, Vietnam. Research Interests: Her work focuses on Database Management Information Privacy & Security Mobile/Distributed Databases Data Mining Quantum Computing Applications in Databases Outlier Detection in Data Streams Key Projects: Includes NSF-funded research on GPU-accelerated spatial data processing, cloud query optimization, and big data hubs. Notable projects: "Spatial Data Management on GPUs" (2013), "Big Data Innovation Hub for the South" (2015), and quantum data science initiatives (2023). Awards: 2012 NSF Directorate Recognition 2007 Distinguished Alumnus Award (SMU) 2009 ACM Recognition Award 2016-2017 Semantic Big Data Workshop Leadership Advising & Grants: Oversees NSF grants totaling millions, focusing on cyberinfrastructure, ecological forecasting, and medical data analytics. No formal student advisees listed but collaborates extensively with researchers globally. Labs & Teams: Leads initiatives in quantum database optimization, mobile-cloud systems, and GPU-accelerated spatial analytics within OU's School of Computer Science.

• Maturity Models
• Information Systems Quality
• Online Service Quality
• +۵ مورد دیگر

Álvaro Rocha is an Honorary Professor at the University of Lisbon's ISEG (Lisbon School of Economics & Management), where he holds a D.Sc. in Information Science and teaches Information Systems. His research focuses on maturity models, e-Government, e-Health, and IT in education. He leads the ADVANCE research center and collaborates with LIACC and CINTESIS. Key roles include Vice-Chair of the IEEE Portugal Section and Editor-in-Chief of JISEM and RISTI journals. He advises international bodies like the European Commission and multiple governments. His educational background includes degrees in Computer Science, Mathematics, and Information Management. Recent work spans AI applications in healthcare, blockchain, and digital learning environments. Education: Aggregation in Information Systems (2011, Universidade Fernando Pessoa), Ph.D. in Information Systems (2001, Universidade do Minho), M.Sc. in Information Management (1995, Universidade Católica Portuguesa), and B.Sc. in Applied Mathematics (1990, Universidade Lusíada). Research highlights include developing maturity models for higher education institutions and health systems, AI-driven diagnostics, and metaverse-based learning frameworks. He has published extensively in journals like Neural Computing and Applications, and Springer book series. His grants include leadership in EU-funded projects and international advisory roles. Professional contributions include founding two Scopus-indexed journals and managing Springer's Information Systems Engineering & Management book series. He actively participates in conferences and collaborates globally on cybersecurity, IoT, and educational innovation.

Daniel Chazanمشاهده پروفایل

استاد

• Mathematics Education
• Teacher Education
• Student-Centered Teaching
• +۳ مورد دیگر

Dr. Daniel Chazan is a Professor in the Department of Teaching and Learning, Policy and Leadership at the University of Maryland, College Park, and holds roles as Director of the Center for Mathematics Education and co-Director of Terrapin Teachers. He earned his Ed.D. from Harvard Graduate School of Education (1989). His research focuses on mathematics teaching as a societal endeavor, student-centered pedagogy, technology-supported teacher education, and the history of mathematics curriculum in the U.S. He has pioneered the use of multimedia tools like LessonSketch for teacher training. Chazan’s work emphasizes bridging educational scholarship with classroom practice, particularly through his collaborations on projects such as the ThEMaT initiative and the LR+D network. Notable awards include the 2023-2024 Distinguished Scholar Teacher title and the 2023 AMTE Excellence in Scholarship Award. His publications explore the dynamics of algebra classrooms, teacher decision-making, and the role of representations of practice in education. His teaching includes courses like TLPL 712 (History of Mathematics Curriculum) and TLPL 788Y (Mathematics Research for Educators). Chazan’s career spans roles at Michigan State University (1990-2002), where he contributed to foundational works like Beyond Formulas in Mathematics and Teaching (2000) and Embracing Reason (2007). Key Contributions: Development of animated classroom scenarios for teacher education, integration of technology in formative assessment, and advocacy for equitable mathematics instruction. Grants & Initiatives: Supported by NSF and Spencer Foundation funding for projects on teacher education and curriculum design.

Onur İŞBULANمشاهده پروفایل

دانشیار

• Educational Technology
• Distance Education
• Open and Distance Learning
• +۱۵ مورد دیگر

Assoc. Prof. Dr. Onur İŞBULAN is a faculty member in the Department of Educational Sciences at the Faculty of Education, Sakarya University. He holds the academic rank of Associate Professor and is actively involved in teaching, research, and academic service. His academic contributions span undergraduate and graduate levels, with a strong focus on educational technologies and instructional design. His research interests include Educational Technology , Distance and Open Learning , Multimedia Learning , Instructional Design , Web 2.0 and Social Media in Education , Virtual Reality Applications , Teacher Education , and Educational Data Mining . His work emphasizes the integration of digital tools into pedagogical practices and the psychological aspects of technology use among educators and students. The recent publications highlight a consistent research trajectory in understanding social media behavior among pre-service teachers , online learning readiness , academic procrastination , and trends in educational technology using big data. His work bridges theoretical foundations with practical applications in Turkish and international educational contexts. Scientific Awards: Sakarya University 2011 Publication Award Dr. İŞBULAN has supervised numerous master’s theses in the field of Computer and Instructional Technologies Education and has served on external thesis committees. He has secured and led research projects, including industry collaborations (e.g., Turkcell) and European Union-funded initiatives. He has also contributed to academic service through editorial and peer-review roles in journals such as Malaysian Online Journal of Educational Technology and BMC Psychology . He has played a key role in establishing the Faculty of Education Distance Education Studio and has been actively involved in organizing and moderating international academic conferences such as the International Educational Technology Conference and International Conference on New Horizons in Education.