جست‌وجوی استاد و پژوهشگر

Anqi Liuمشاهده پروفایل

مدرس ارشد

• Financial Mathematics
• Quantitative Finance
• Computational Finance
• +۱۰ مورد دیگر

Dr Anqi Liu is a Senior Lecturer in Financial Mathematics at the School of Mathematics, Cardiff University. She specializes in market microstructure, trading behavior, time series models, Hawkes processes, and fractal activity time geometric Brownian motion (FATGBM) in finance, with a focus on FinTech applications including cryptocurrencies and blockchain technology. BSc in Mathematics and Applied Mathematics, Northwest University, China MSc and PhD in Financial Engineering, Stevens Institute of Technology, USA Her research integrates quantitative finance and computational finance methodologies to improve pricing and risk modeling frameworks for financial markets, emphasizing systemic perspectives. Recent work explores trading behavioral patterns in crypto markets and blockchain-based financial network reactions to systemic events. Key research trends include: Applications of Hawkes processes and entropy approaches to market dynamics Agent-based modeling of financial networks and behavioral patterns Machine learning integration for sentiment analysis and trading strategies Systemic risk evaluation in traditional and crypto markets Novel pricing models like FATGBM extensions Scientific contributions include: Stevens Innovation and Entrepreneurship Scholarship (4 years during PhD) She has published extensively in journals like Quantitative Finance , European Journal of Finance , and Entropy , with recent works analyzing SVB collapse contagion effects and cryptocurrency price bubbles using wavelet analysis. Her supervision areas include cryptocurrency market microstructure, Hawkes processes, and agent-based modeling in behavioral finance.

Shiva Houshmandمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Password Security
• +۵ مورد دیگر

Shiva Houshmand is an Associate Professor in the Department of Mathematics and Computer Science at Santa Clara University's College of Arts and Sciences. Their research focuses on cybersecurity, password security, and digital forensics. B.S. in Mathematics from the University of Tehran M.S. and Ph.D. in Computer Science from Florida State University Research interests include password cracking techniques, IoT security, probabilistic algorithms, and forensic analysis. Recent work explores smartphone-wearable interactions, homophone-based attacks, and vulnerabilities in smart home systems. 15 most recent publications (2011-2025) demonstrate expertise in probabilistic password cracking, IoT forensics, and mobile security systems. Articles span topics from dictionary-based Viterbi algorithms to forensic data extraction in consumer devices.

• Database Systems
• Cloud Computing
• Machine Learning Integration
• +۳ مورد دیگر

Carlo Curino is a researcher at Microsoft Research , focusing on database systems, cloud computing, and machine learning integration. He has collaborated extensively with institutions including MIT, Microsoft, and the University of Wisconsin-Madison. His research spans Geo-distributed data analytics Automated configuration tuning Tensor-based database systems Data lake optimization Spark performance engineering Recent publications highlight his work on AI-driven systems like MotherNet and Rockhopper , alongside contributions to query processing over compressed data and log-structured tables. Collaborators include prominent figures such as Raghu Ramakrishnan and Jesús Camacho-Rodríguez . Key projects involve LST-Bench (cloud storage benchmarking), AutoComp (data compaction), and PyFroid (commodity workstation analytics). His work bridges database optimization with modern machine learning demands in enterprise environments.

• Cybersecurity
• Drone/UAV Security
• Wireless Network Security
• +۶ مورد دیگر

Ahmad Y. Javaid is an Assistant Professor in the Electrical Engineering and Computer Science Department within the College of Engineering at The University of Toledo. He serves as the founding director of the Paul A. Hotmer Cybersecurity and Teaming Research (CSTAR) lab and holds the position of Cyber Education and Cyber Threat Mitigation Faculty Fellow. Dr. Javaid received his B.Tech. (Hons.) Degree in Computer Engineering from Aligarh Muslim University, India in 2008 and his Ph.D. from The University of Toledo in 2015, where he was awarded the prestigious University Fellowship Award. Prior to joining the University of Toledo faculty, he worked for two years as a Scientist Fellow in the Ministry of Science & Technology, Government of India. Dr. Javaid's research spans multiple domains within cybersecurity and human-machine interaction. His primary expertise lies in cyber security of drone networks, smartphones, and wireless sensor networks. He has conducted extensive research on human-machine teams and applications of AI and machine learning to attack detection and mitigation. His work bridges theoretical security frameworks with practical implementations across various domains including UAV security, physical layer communications security, and multimodal human-computer interaction systems. His recent publications demonstrate a continued expansion into nuclear-renewable energy systems security and advanced cybersecurity education frameworks for K-12 students. Dr. Javaid has secured significant research funding, with collaborative proposals totaling $9.7M (including all partners along with UToledo), of which $1.4M has been allocated specifically to him. Approximately $4.1M has been allocated to the University of Toledo from these projects. His research has been funded by prestigious agencies including the NSF, AFRL, NASA-JPL, Department of Energy, and the State of Ohio. He has also played a critical role in cultivating private gifts to support the CSTAR lab. IEEE Graduate Student Member (2012) IEEE Member (2015) IEEE Senior Member (2019) University Fellowship Award As an educator, Dr. Javaid has developed innovative cybersecurity curriculum modules and educational tools. He has served as a reviewer for high-impact journals and as a member of technical program committees for reputed conferences. His work extends to cybersecurity education initiatives targeting K-12 students, with projects focused on developing interactive learning modules to improve cybersecurity awareness at the high school level. He has published more than 85 peer-reviewed publications across journals, conferences, and posters, demonstrating consistent scholarly productivity with significant output in recent years. Dr. Javaid leads the Paul A. Hotmer Cybersecurity and Teaming Research (CSTAR) lab, which focuses on cutting-edge research in cybersecurity, particularly in the areas of UAV security, physical layer security, and human-machine teaming. The lab has received support from both government agencies and private sources, enabling the development of novel security frameworks and educational tools. His interdisciplinary approach bridges computer science, electrical engineering, cybersecurity, and human factors research, making significant impacts in both academic and practical cybersecurity domains.

• Embedded Systems
• Fault Tolerance
• Precision Agriculture
• +۵ مورد دیگر

Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.

• Supply Chain Management
• Retail Operations
• Logistics
• +۳ مورد دیگر

Brent D Williams serves as the Dean and holds the Sam M. Walton Endowed Leadership Chair at the Sam M. Walton College of Business , University of Arkansas. Previously, he acted as Senior Associate Dean overseeing academic departments and strategic initiatives, including the McMillon Innovation Studio and Walton College at 2nd & Main. As Chair of the Department of Supply Chain Management, he shaped departmental direction. Williams earned his PhD in Business Administration (Supply Chain Management) from the University of Arkansas, following academic roles at Texas Christian University and Auburn University. Research focus: Williams specializes in retail supply chain optimization, exploring planning processes, execution strategies, and market-driven adaptations. His work addresses inventory control, transportation economics, and consumer behavior in digital and physical retail environments. He has published over 30 articles in journals like Journal of Operations Management and Production and Operations Management . Scientific contributions: His research spans supply chain resilience, pricing dynamics, and the impact of policy uncertainty on inventory management. Awards include the Sam M. Walton Endowed Leadership Chair, reflecting his academic leadership and scholarship. Williams' work bridges theoretical rigor with practical applications in logistics and operations.

Christos Drososمشاهده پروفایل

استادیار

• Industry 4.0
• Internet of Things (IoT)
• Industrial Supervisory Systems
• +۳ مورد دیگر

Christos Drosos is an Assistant Professor at the Department of Industrial Design and Production Engineering , School of Engineering , University of West Attica . His academic focus spans Industry 4.0 technologies , Internet of Things (IoT) , Industrial Supervisory Systems , Heuristic and MetaHeuristic Algorithms , Information Systems , and Embedded Systems . Education : BEng in Automation Engineering, Technological Educational Institute of Piraeus MSc (with distinction) in Informatics, University of Piraeus PhD in Computer Science, University of Piraeus (2016) Postdoctoral Research, University of Thessaly Research Interests center on advancing Industry 4.0 through technologies like IoT and Embedded Systems , with applications in automated manufacturing , environmental monitoring , and smart infrastructure . His work also explores heuristic algorithms for optimization and robotics in sustainable contexts. Recent Publications highlight trends in 3D printing , swarm robotics , and wireless sensor networks for cultural heritage preservation and agricultural modernization . These studies emphasize Industry 4.0 integration, sustainability , and smart system optimization . Laboratory Affiliation : Dr. Drosos is associated with the Electronic Automation, Telematics & Cyber-Physical Systems Research Laboratory at the University of West Attica, supporting his work in automation , IoT , and embedded systems .

• Big Data
• Machine Learning
• Cybersecurity
• +۵ مورد دیگر

Dr. Danilo Giordano is an Associate Professor at the Department of Control and Computer Science (DAUIN) within Polytechnic University of Turin. He actively contributes to the SmartData@PoliTO Center, focusing on big data and data science applications. Research Interests: Big data, machine learning, cybersecurity, predictive maintenance, smart cities Scientific Awards: Best Student Paper Award ITC (2015), IETF Applied Research Prize coauthor (2017) His academic work spans machine learning for network security , big data analytics in industrial contexts , and smart city infrastructure optimization . Notably, his recent publications examine satellite network performance, darknet visibility enhancement, and language model applications in cybersecurity. As an editorial board member of COMPUTER NETWORKS (since 2024), he has also organized multiple conferences including the Data Challenge sessions at PHME conferences and served as publication chair for ACM CoNEXT workshops.

卫强مشاهده پروفایل

استاد

• Big data analysis
• Information systems
• E-commerce
• +۴ مورد دیگر

Professor Qiang Wei is a faculty member at the Department of Management Science and Engineering, Tsinghua University School of Economics and Management. With a PhD in Management from Tsinghua (1999-2003), he has held academic positions including Department Head and Deputy Secretary of the Party Branch. His research focuses on big data analysis, information systems, e-commerce, business intelligence, data mining, and management simulation. Doctor of Management, Tsinghua School of Economics and Management (1999-2003) Master of Tsinghua School of Economics and Management (1997-1999) Bachelor of Science, Tsinghua School of Economics and Management (1992-1997) His recent research explores big data analysis , online review systems , and personalized recommendation through machine learning and neural network frameworks. Articles span topics including monetary incentives in crowdsourcing , temporal consistency in review ranking , and product relationship discovery via embeddings . He has published in top journals like Management World, INFORMS Journal on Computing, and Information Systems Research. Key awards include: 2021 Ten Best Papers Award, Management World 2020 Ministry of Education Second Prize in Philosophy and Social Sciences 2018 Theory Contribution Award, China Society for Information Economics He teaches courses such as Information Technology and Management , Big Data and Business Analysis , and Data Structure and Algorithm . His work bridges computational methods with business applications, including cybersecurity analysis, mobile technology impact studies, and competitive intelligence systems.

Juan Carlos Vidal Aguiarمشاهده پروفایل

دانشیار

• Process Mining
• Business Intelligence
• Semantic Annotation
• +۵ مورد دیگر

Juan Carlos Vidal Aguiar serves as an Associate Professor in the Department of Electronics and Computer Science at the University of Santiago de Compostela, Spain. With extensive experience in academic research and teaching, he has established himself as a prominent figure in process mining and business intelligence applications. His work bridges theoretical computer science with practical implementations across healthcare and educational domains. Dr. Vidal Aguiar earned his Bachelor Engineering degree in Computer Science from the University of La Coruña in 2000, followed by several years working as a senior IT consultant. He completed his PhD at the University of Santiago de Compostela in 2010, where he has remained as faculty since. His academic journey reflects a trajectory from foundational computer science toward specialized applications in process analytics. His research interests focus on knowledge discovery, semantic annotation, semantic modeling of workflows and services, and the application of artificial intelligence for business intelligence . Recent work demonstrates significant evolution toward healthcare applications, particularly in cardiac rehabilitation and glucose monitoring, while maintaining strong foundations in process mining techniques. His publications reveal a clear progression from theoretical workflow modeling to practical AI-driven business process solutions with real-world impact. Analysis of his publication trends shows increasing specialization in predictive process monitoring with deep learning approaches, particularly evident in his 2023-2025 work. His research spans both theoretical contributions in kernel methods and biclustering algorithms, and practical implementations like the VERONA Python library for benchmarking. The interdisciplinary nature of his work is particularly notable in healthcare applications where process mining techniques are adapted for medical contexts. Dr. Vidal Aguiar leads multiple significant research initiatives including Predictive monitoring and causality for cardiac rehabilitation, Responsible AI for Process Mining 2.0, GAMification techniques for entrepreneurial teacher development, and Soft computing for gamification analytics in cardiac rehabilitation . These projects demonstrate his ability to secure research funding across diverse domains while maintaining a cohesive research vision centered on process analytics. His research ecosystem includes collaborations with numerous colleagues including Manuel Lama, Pedro Gamallo-Fernandez, and Marcos Matabuena across various projects. The SoftLearn platform represents one of his notable contributions to educational technology, applying soft computing techniques to process mining in e-learning contexts. His work consistently bridges academic research with practical implementations that address real organizational challenges.

Anita Torabiمشاهده پروفایل

استاد

• Structural Geology
• Fault Mechanics
• Fluid Flow in Deformed Reservoirs
• +۶ مورد دیگر

Anita Torabi is a Professor in Structural Geology at the University of Oslo , affiliated with the Department of Geosciences. Her research focuses on structural geology, fault mechanics, fluid flow in deformed reservoirs, CO2 storage, geothermal reservoirs, and seismicity. She employs advanced methods such as 3D seismic analysis, fault asperity studies, and machine learning for geological applications. Key affiliations: University of Oslo, NORCE (2015-2018), Uni Research CIPR (2008-2018) Education: PhD in Geosciences (2008) - University of Bergen Research Interests include: Fault mechanics and deformation processes Fluid flow in faulted reservoirs CO2 storage and green energy solutions Geomechanics and seismic risk assessment Machine learning in structural geology Basement rock fracture analysis Recent Publications highlight trends in: 3D fault characterization using deep learning Fluid dynamics in siliciclastic-carbonate systems Seismic attribute analysis for fault geometry Compaction bands in Tertiary-Quaternary sequences Ontology-driven geological modeling Machine learning applications for CO2 storage Research Leadership includes projects such as: CO2 Seal and Bypass – COPASS CO2SafeQuest (fault behavior for CO2 storage) gigaCCS@UiO (Center of Excellence in Carbon Capture) VICCO (volcanic-sedimentary CO2 storage) Pool Studies CO2 Storage research group

Martin Frandsenمشاهده پروفایل

پژوهشگر

• Energy-efficient building design
• Indoor environment
• Domestic hot water systems
• +۵ مورد دیگر

Martin Frandsen is a Researcher at Aalborg University 's Department of the Built Environment , within the Faculty of Engineering and Science. His work focuses on energy-efficient building design , indoor environment , domestic hot water systems , and building performance simulations , combining laboratory/field measurements with computational methods. Education: Civil Engineer, MSc in Indoor Climate and Energy (2016-2021) Key Collaborations: Project PRELUDE (2020-2024), ORCID holder His research in building energy systems and hydraulic network optimization is reflected in 13 publications (2022-2025), with 5 in 2024 alone. He specializes in smart meter data analysis and district heating integration , producing datasets with sub-hourly monitoring of office buildings. Frandsen's teaching involves laboratory experiments on indoor environments and building energy simulation , mentoring bachelor/master groups. He has contributed to 10 research datasets and collaborated with 12+ peers on energy informatics and NZEB buildings.

• Process Mining
• Process Modelling
• Conceptual Modelling
• +۵ مورد دیگر

Jan Martijn van der Werf serves as Associate Professor in Process Science at Utrecht University's Faculty of Science, Department of Information and Computer Science. Since September 2022, he has held the position of Programme Director for the Bachelor Information Sciences, overseeing curriculum development and academic operations for both Business Informatics and Information Sciences programs. Education: Dual PhD in Computer Science from Eindhoven University of Technology and Humboldt Universität zu Berlin (Thesis: 'Compositional Design and Verification of Component-based Information Systems') Research Focus: Van der Werf's work centers on process mining and behavioral modeling in software architectures, with emphasis on the interplay between data and processes. His expertise spans Conceptual Modelling of Information Systems , Enterprise Architecture , and Service-Oriented Architecture , addressing challenges in process discovery, verification, and practical implementation within complex organizational contexts. Current research explores the human dimensions of process mining adoption and AI-driven event log extraction. Publication Trends: Recent work (2023-2024) reveals increasing focus on methodological rigor in process discovery, human factors in process mining initiatives, and formal verification techniques for Petri nets. His publications bridge theoretical foundations with practical applications, particularly in event log extraction using large language models and visualization of complex process chronologies from heterogeneous data sources. Academic Contributions: Van der Werf teaches core courses in Process Modelling and Software Architecture , actively participates in academic workshops (including the 2020 'Information System Modeling' workshop), and supervises graduate research. His Scopus profile indicates 77 research outputs and supervision of 3 students, reflecting sustained scholarly engagement in process science and information systems.

• Data Analytics
• Energy Security
• Reliability and Risk Analysis
• +۳ مورد دیگر

Ričardas Krikštolaitis is a Professor at Vytautas Magnus University's Faculty of Informatics, Department of Mathematics and Statistics, where he has served since 2012. He earned his Doctor of Physical Sciences degree in 2001 and was appointed as Chief Researcher in 2023. Research Interests Data Analytics Energy Security Reliability and Risk Analysis Mathematical Statistics Applied Mathematics Panel Data Analysis Student Advisees Asad, Daiva (2024): A prototype for learning data analysis and prediction Jokšaitė, Deimantė (2022): Statistical investigation of factors determining inflation Servaitė, Dovilė (2022): Identification of anomalies in system log data Targonskytė, Monika (2018): Statistical analysis of employment rate dependence from socio-economic indicators Micikevičiūtė, Agnė (2017): Statistical investigation of company’s X activity data

Özkan CANAYمشاهده پروفایل

استادیار

• Information Systems
• Web Mining
• Data Analytics
• +۶ مورد دیگر

Dr. Özkan CANAY serves as an Assistant Professor in the Department of Information Systems and Technologies at Sakarya University's Faculty of Computer and Information Sciences. With a career spanning nearly 30 years at the university, he progressed from technical roles to his current academic position, which he assumed in 2025 following completion of his doctorate. His educational credentials include: Industrial Engineering B.S. from Sakarya University (2002) Industrial Engineering M.S. from Sakarya University (2005) Computer and Information Engineering Ph.D. from Sakarya University (2024) Dr. CANAY's research centers on web analytics, user behavior prediction, and data governance frameworks. His expertise spans web usage mining (WUM), application logging, anomaly detection, and machine learning applications for enriched analytics. He has developed specialized frameworks like CAWAL for comprehensive web analytics. His scholarly output includes two academic books published in 2016 and the BIDAM scientific journal search engine. His Web of Science profile shows an h-index of 2 with 11 total citations, indicating a developing research trajectory. Administratively, he served as Deputy Director (2005-2008, 2009-2011) and Director (2011-2012) of the Computer Research and Application Center. He has taught informatics courses for 16 years, primarily through distance education, and currently instructs courses in information systems analysis, Python programming, and project management.