جست‌وجوی استاد و پژوهشگر

• Cybersecurity
• Computer Forensics
• Network Security
• +۷ مورد دیگر

Dr Hasmukh Morarji is a Senior Lecturer in the School of Computer Science at Queensland University of Technology (QUT), Faculty of Science. He has been an academic at QUT for over 30 years and previously taught at the University of the South Pacific in Fiji and the University of Brunei Darussalam. He holds a PhD from the University of Kent and master's and bachelor's degrees from the University of Canterbury, New Zealand. His research and teaching focus on key areas in computing, including cybersecurity, computer forensics, software engineering, networks, and IT education. He has coordinated multiple units in programming, computer systems, and security, and currently leads the Master of Information Technology, Graduate Certificate in IT, and Graduate Diploma in IT programs. His recent publications reflect a strong trend in cybersecurity, particularly in threat information sharing, mobile malware modeling, SCADA security, and computer profiling for forensic applications. His work bridges theoretical models with practical security implementations, especially in critical infrastructure and educational environments. Barriers to cybersecurity threat sharing in developing nations Formal modeling of mobile malware propagation Security risks in IPv6 transition for SCADA systems Event-based computer profiling for digital forensics Human factors in critical infrastructure ICT risk Innovations in IT education and integrated learning environments Dr Morarji has not listed any scientific awards or honors in the provided text. He has supervised or co-authored work with several researchers but no formal students are listed. He has been actively involved in teaching and curriculum development across undergraduate and postgraduate levels, contributing significantly to IT education at QUT. He teaches current units such as IFN551 Computer Systems Fundamentals, IFN555 Introduction to Programming, and IFN556 Object-Oriented Programming. His earlier teaching includes foundational courses in programming and computer systems. No specific lab or research team affiliations are mentioned in the source material.

• Sex Differences
• Gender Differences
• Human Social Behaviour
• +۷ مورد دیگر

Bobby May is a Lecturer in the School of Psychology and Neuroscience at the University of St Andrews, affiliated with the Centre for Research into Equality, Diversity & Inclusion and the Centre for Social Learning & Cognitive Evolution. He is actively engaged in research and teaching, focusing on sex differences in human social behavior. His research interests center on sex differences in risky behavior, aggression, and emotional dynamics in social contexts. He employs meta-analytic and experimental methods to investigate how these differences manifest and evolve. A current focus is on how psychological sex differences are perceived and communicated in the media. His work aligns with UN Sustainable Development Goals, particularly gender equality. His recent publications (2023–2024) emphasize meta-analytic studies on aggression, heart rate variability, and emotional conflict in relationships. He has contributed to datasets and software tools supporting open science. His research often intersects with behavioral neuroscience, social psychology, and evolutionary perspectives. Bobby May has received no individual scientific awards listed in the text, though his collaborators have been recognized for public engagement. He is involved in advising students, as seen through his supervision of datasets and student projects. He is a Co-Investigator on two recent projects: one on digital skills development in response to COVID-19, and another on building a database for domestic abuse services. These reflect his engagement with applied research and community impact. He also participates in public science events such as EXPLORATHON and the Edinburgh Fringe, promoting science communication. Bobby May supervises research students and contributes to collaborative research teams, particularly with researchers like Donaldson, Cross, and McCurry. He supports open science through data and software sharing via repositories like Zenodo and the University of St Andrews data archive.

Sylvio Barbon Juniorمشاهده پروفایل

دانشیار

• Machine Learning
• Meta-Learning
• Process Mining
• +۷ مورد دیگر

Sylvio Barbon Junior is an Associate Professor at the Department of Engineering and Architecture, University of Trieste, Italy. He leads the Machine Learning Lab and previously held roles including Research Group Leader at the State University of Londrina (Brazil) and visiting positions at Università di Modena e Reggio Emilia and Università degli Studi di Milano (Italy). His academic journey includes a Ph.D. in Computational Physics (University of São Paulo, 2011) and multiple postdoctoral and research fellowships. Research interests span Meta-Learning, Process Mining, Stream Mining, Data Mining, and Computer Vision. He focuses on applications such as fraud detection in agrifood systems, cybersecurity in IoT networks, and real-time anomaly detection in business processes. His work integrates machine learning with spectroscopic techniques for quality assessment in agriculture and medical diagnostics. Publications highlight contributions to meta-learning frameworks for graph-based search, adaptive ensemble methods for multi-label streams, and computer vision systems for cocoa classification. Awards include Best Paper recognitions at SBSI and BRACIS conferences for innovations in process mining and anomaly detection. Award highlights include Honorable Mentions for work on fake news classification (SBSI 2019) and Best Paper awards for leveraging anomaly detection in business processes (SBSI 2018). He serves as a reviewer for journals like Elsevier Information Processing in Agriculture and as an editor for Springer’s Data Semantics series. His teaching spans postgraduate and graduate programs in Applied Data Science, Machine Learning Operations, and Computer Graphics. He advises on Ph.D. and Master’s theses focusing on AutoML, Process Mining, and Machine Learning Applications.

• E-learning
• Computer Science Education
• Educational Technology
• +۴ مورد دیگر

Janko Žufić, M.Sc.ing, is a Senior Lecturer at the Faculty of Educational Sciences, University of Pula, Croatia. He holds degrees in Electrical Engineering with a major in Automation from the Faculty of Electrical Engineering and Computing (FER) in Zagreb (1993) and pedagogical competences acquired in 2001. A certified computer science professor since 2002, he has dedicated his career to bridging technology and education, with particular emphasis on e-learning systems and computer science education. Employment History: Private sector work (1993-1999), teaching roles in primary/secondary schools (1998-2002), head of IT support at Faculty of Educational Sciences (2002-present), Senior Lecturer since 2007, and part-time teacher at Algebra Group. Research Focus: E-learning optimization, microlearning, educational technology design, programming pedagogy for elementary grades, and human factors in computing. His scholarly work spans 20+ publications, with recent studies exploring ChatGPT's educational implications (2025), video-based microlearning (2024), and gamification in computer science education (2022). He has also contributed to understanding the role of color and typography in digital learning environments (2009-2019). Žufić's practical expertise includes developing Web 2.0 tools for educators (2017), creating three books, and mentoring students in producing approximately 50 films. As an active project manager, he has coordinated two EU-funded initiatives and over 80 smaller projects focused on social and technical sciences, supported by organizations ranging from Zagreb Bank to Croatian employment agencies and Istrian municipalities. His academic rank was last renewed on January 24, 2018, within the field of Information and Communication Sciences, specializing in Information Systems.

Luís M. Alvesمشاهده پروفایل

استاد

• Empirical Software Engineering
• Software Project Management
• Software Metrics
• +۳ مورد دیگر

Luís M. Alves is a Professor at the Polytechnic Institute of Bragança, Portugal, where he has taught since 1999. He holds an M.Sc. in Computer Science from the University of Porto and a Ph.D. in Information Systems and Technology from the University of Minho. Currently, he serves as Course Director of the Bachelor in Informatics Engineering program at the Technology and Management School's Informatics and Communications Department. His research focuses on empirical software engineering, software project management, educational methodologies in programming instruction, and software metrics. Notable interests include problem-based learning approaches, student achievement metrics using tools like the C Tutor, and cross-country educational studies comparing programming curricula. Publications emphasize programming pedagogy innovations, software risk analysis in academic projects, and empirical studies on software estimation models. Over 20 years, his work bridges academic and industry needs through project-based learning frameworks and visualization tools like GraSMA. No scientific awards are explicitly mentioned in the provided text. He has advised at least one publication in programming education research and contributed to multiple international collaborations on educational technology. No lab affiliations or specific grant details are documented here.

Arnaldo Pereiraمشاهده پروفایل

استادیار

• Artificial Intelligence
• Intelligent Systems
• Semantic Data
• +۳ مورد دیگر

Arnaldo Pereira is an Invited Assistant Professor at the Instituto Politécnico de Bragança. He holds a Ph.D. in Informatics from a collaborative program between the University of Aveiro, University of Porto, and University of Minho (MAPi), focusing on semantic data querying and visualization. His research interests include Artificial Intelligence, Intelligent Systems, and their applications in biomedical informatics and FAIR data practices. He has contributed to European research projects advancing data integration and control systems. Education: Ph.D. in Informatics (Collaborative Program: University of Aveiro, University of Porto, University of Minho) Research Interests: Dr. Pereira specializes in semantic data technologies, FAIR data principles, and their application to biomedical database systems. His work emphasizes query optimization, visualization tools for complex data, and the development of interoperable systems in healthcare and industrial contexts. Recent efforts focus on collaborative workshops (BYOD) to enhance data management practices and knowledge sharing in interdisciplinary environments. Key Research Trends (2020–2024): His publications highlight advancements in FAIR-compliant tools, semantic querying of biomedical databases, and the integration of AI-driven approaches for data accessibility and system monitoring. Earlier work includes contributions to industrial cyber-physical systems, KPI optimization, and agent-based enterprise architectures. Grants & Collaborations: Active participant in EU-funded research projects focusing on data integration and intelligent systems. No specific grant details provided in the text. Labs/Teams: Affiliated with computational and biomedical informatics groups at his institution, though specific lab names are not mentioned.

• Personalized Software Technology
• Mobile Device Programming
• Web Programming
• +۴ مورد دیگر

Evangelos Sakkopoulos is an Associate Professor at the Department of Computer Science, University of Piraeus, specializing in Custom Software Technology. He holds a PhD from the Department of Computer Engineering and Informatics at the University of Patras. His research focuses on personalized software systems, mobile programming, web development, and data privacy solutions. He has contributed over 60 publications in international journals and conferences, with expertise in frequent itemset hiding algorithms, AI-driven e-learning systems, and smart home security technologies. Education: PhD in Computer Engineering and Informatics (University of Patras) Research interests include: Personalized Software Technology Mobile Device Programming Web Programming Data Privacy and Security Machine Learning Applications His work spans e-government systems, maritime surveillance technologies, and cultural heritage preservation through AI. Recent projects address challenges in digital identity management, EU policy compliance, and adaptive learning environments. Over 150 academic publications reflect his contributions to privacy-preserving data mining, smart home safety, and mobile healthcare systems.

• Longitudinal Data Analysis
• Bayesian Analysis
• Joint Modeling
• +۵ مورد دیگر

Taban Baghfalaki is a Lecturer in Statistics with a focus on advanced statistical methodologies applied to longitudinal data analysis, Bayesian inference, and joint modeling. His work integrates complex statistical techniques to address challenges in health sciences, genetics, and epidemiology. He has contributed to developing Bayesian approaches for handling zero-inflated data, competing risks, and pleiotropy in genomic studies. Key research areas include dynamic prediction in longitudinal studies, variable selection in high-dimensional datasets, and the application of copula models for multivariate data analysis. He has pioneered tools like the GCPBayes pipeline for cross-phenotype genetic association studies, demonstrating expertise in both theoretical and applied statistics. His publications span 2011–2025, emphasizing Bayesian methods, survival analysis, and longitudinal modeling. Notable contributions include frameworks for joint modeling of longitudinal and survival outcomes, methods for analyzing skewed mixed responses, and computational tools for genomic data. Awards and grants are not explicitly mentioned in the provided texts, but his prolific publication record reflects sustained research activity. He collaborates on projects involving healthcare data (e.g., Tehran Lipid and Glucose Study) and genetic epidemiology.

Knarik Tunyanمشاهده پروفایل

استادیار مهمان

• Linear Algebra
• Numerical Analysis
• Linear Programming
• +۱۱ مورد دیگر

Knarik Tunyan is a Visiting Assistant Professor in the Department of Mathematics/Computer Science at Purchase College, State University of New York, within the School of Natural and Social Sciences. She contributes to undergraduate education through courses in Linear Algebra, Calculus, Differential Equations, and advanced topics in mathematics. Education: PhD in Technology, Tampere University of Technology, Finland MS in Mathematics, Yerevan State University, Armenia Her research integrates applied mathematics with computational science, focusing on Linear Algebra, Numerical Analysis, Linear Programming, and Computational Inverse Problems . She explores mathematical methods in signal and image processing, optimization, network theory, economics, and biostatistics. Recently, she has been investigating the use of technology in mathematics education, including 3D printing and software tools like Mathematica and OpenSCAD. The 15 most recent publications highlight a consistent trajectory in matrix computations, optimization algorithms, and interdisciplinary applications . Early work centered on pivot rules and interior-point methods, particularly their behavior on challenging problems like the Klee-Minty cube. Later contributions expanded into image compression using QkRk factorization, Bayesian metabolic modeling, and educational innovations involving STEAM and 3D visualization. The articles reflect a blend of theoretical rigor and real-world application, spanning fields from computational biology to educational technology. Scientific Contributions and Recognition: Active presenter at international conferences including ICTCM and WCGO Published in reputable journals such as SIAM Journal on Matrix Analysis and Applications , Journal of Theoretical Biology , and Inverse Problems and Imaging Contributions to algorithmic efficiency in least squares and optimization She advises on curriculum development and student learning, particularly in integrating technology into mathematical instruction. Though no formal students are listed, she mentors through senior seminars and research-oriented courses. She has not received explicitly mentioned awards or grants in the provided text. Her work is supported by institutional resources and collaborative networks in computational mathematics and STEM education. Dr. Tunyan is involved in academic outreach and technological experimentation, especially through her presentations on 3D printing and mathematical software. She maintains regular office hours and engages students through digital platforms like Starfish, emphasizing accessibility and active learning.

• Information Retrieval
• XML Search Engines
• Text Search Engines
• +۸ مورد دیگر

Shlomo Geva is an Adjunct Professor in the School of Computer Science at Queensland University of Technology's Faculty of Science. His research focuses on information retrieval systems, particularly in specialized areas including XML search engines, text search engines, link discovery, and document computing. His academic work spans multiple disciplines within computer science, with particular emphasis on information retrieval technologies and their applications. Professor Geva's research interests include clustering algorithms, cross language information retrieval, focused information retrieval, information retrieval systems, link discovery mechanisms, search engine technologies, text indexing and retrieval methods, and XML indexing and retrieval techniques. His work demonstrates a consistent focus on improving the efficiency and effectiveness of information access systems across various data formats and domains. His recent publications reveal a trend toward applications of information retrieval techniques in diverse fields including remote sensing, bioinformatics, and data stream processing. The research shows an evolution from traditional information retrieval problems toward more specialized applications requiring advanced clustering algorithms and efficient data processing techniques for large-scale datasets. Professor Geva has successfully supervised numerous doctoral students whose research topics include indoor environment mapping by robots, cross-language information retrieval, natural language query interfaces for XML, evolvable hardware, and autonomous robot behavior systems.

Ghang Leeمشاهده پروفایل

استاد

• Building Information Modeling (BIM)
• Artificial Intelligence in Construction
• Information Interoperability
• +۵ مورد دیگر

Ghang Lee is a Professor at the Department of Architecture and Architectural Engineering of Yonsei University in Seoul, South Korea. He directs the Building Informatics Group, focusing on Building Information Modeling (BIM) , AI applications in construction , and automated code compliance checking . His work bridges human expertise with artificial intelligence, advancing digital transformation in the built environment. Developed systems: Tower Crane Navigation System (TCVS), IoT-based exit signs, and NADIA (speech-to-BIM tool) Co-author of the internationally recognized BIM Handbook Recipient of Silver Medal (President of Korea) and multiple Outstanding Research Achievement Awards Research Interests span BIM, information interoperability, quality management, and AI-driven construction technologies. His recent work emphasizes: NLP for defect detection and classification Domain-specific corpus embeddings Human-AI collaboration in design Smart construction and digital twinning Building informatics standardization Visual-language models for defect analysis Scientific Awards include Silver Medal (President of Korea), Stanford/Elsevier Top 2% Scholar recognition, and multiple Outstanding Conference Paper Awards from KICEM, AIK, and KAIARI. He also holds Yonsei Distinguished Teaching Awards and Ministry of Land, Infrastructure, and Transport commendations.

Marlene Wagnerمشاهده پروفایل

پژوهشگر

• Educational Technology
• Digital Learning
• Teacher Education
• +۷ مورد دیگر

Dr. Marlene Wagner is a Research Associate at the Center for Digitalization in Lifelong Learning at the University of Continuing Education Krems, Austria. She is actively engaged in research on digital transformation in education, with a focus on teacher training, hybrid learning environments, and pedagogical digital competence. Her work is supported by EU and public funding agencies, and she leads key research projects in the field of educational technology. Her research interests center on educational technology , digital learning , teacher education , and learning design . She investigates how digital tools and innovative instructional models—such as flipped and hybrid classrooms—impact teaching effectiveness and student outcomes. Her work also explores AI-driven feedback systems and the transfer of training in continuing education contexts. The recent publications of Dr. Wagner reflect a strong trend in technology-enhanced learning , with emphasis on teacher support , student engagement , and instructional effectiveness . Her research spans both K–12 and higher education, utilizing mixed-methods, meta-analytic, and experimental designs. Key themes include TPACK development, social presence in hybrid settings, and the role of AI in improving learning design quality. Dr. Wagner has not been listed with any scientific awards in the provided text. She collaborates extensively on research projects and contributes to academic discourse through publications and conference presentations. Although her advisory roles are not specified, her leadership in funded projects indicates active involvement in research teams and academic mentoring. Current grants include EU-funded initiatives on teacher training and hybrid learning spaces in schools. She is affiliated with the Center for Digitalization in Lifelong Learning, a research unit focused on innovation in educational practices through digital tools and evidence-based strategies. The center supports interdisciplinary research and contributes to policy development in digital education.

Mohamed Kentourمشاهده پروفایل

مدرس

• Deep Learning
• Controllable AI
• Graph Theory and Reasoning
• +۶ مورد دیگر

Mohamed Kentour is a Lecturer in Artificial Intelligence at the University of Huddersfield, UK, affiliated with the Department of Computer Science within the School of Computing and Engineering. His academic journey includes a PhD in Deep Neural Networks and Structural Mapping (awarded 2 May 2025), an M.Sc. in Computing (2020), and an M.Sc. in Software Development and Information Processing (2018), all from the University of Huddersfield or University of M'Hamed Bougara of Boumerdes, Algeria.

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Carlo Lipizzi is a Teaching Associate Professor and Associate Chair for Corporate and Continuing Studies at the Department of Systems and Enterprises, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology. He also serves as Director of the Center for Complex Systems and Enterprises and holds strategic advisory roles within the College of Professional Education. His educational background includes a PhD in Systems Engineering from Stevens Institute of Technology (2015), an Executive MBA from IMD (1996), and an MS in Mathematics from Università degli Studi La Sapienza, Rome (1981). Lipizzi's research focuses on applied Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning (ML), and Data Science, with applications in decision support, sustainability, and social media analytics. He develops AI agents using Large Language Models and designs systems for extracting decision-critical information from unstructured text. His work bridges computational methods with real-world challenges in defense, education, finance, and public health. The 15 most recent publications reflect a consistent trajectory in NLP and AI, emphasizing social media analysis, bias mitigation in LLMs, sustainability project matching, and formal analysis of technical specifications. Keywords span AI, NLP, Machine Learning, and Computational Social Science, with subfields including affective polarization, disaster response, funding recommendation, and ethical AI. Scientific Awards: Stevens Award for Teaching Excellence (2024) Lipizzi has served as Principal Investigator (PI) or Co-PI on multiple externally funded projects totaling over $5 million, including grants from DoD/Picatinny Arsenal, Defense Acquisition University, Siemens Financial Services, and Accenture. These projects focus on NLP-based risk evaluation, contract classification, educational credentialing, and AI-powered career coaching. He actively mentors graduate students and leads interdisciplinary research teams. His institutional service includes membership in key committees such as RETCOM, GCC, and faculty hiring panels. He leads the Center for Complex Systems and Enterprises and has co-developed academic programs including the Graduate Certificate in Computational Social Science. His teaching portfolio includes core courses in Data Science, AI & ML, and NLP at the graduate level.

Eitan Mullerمشاهده پروفایل

استاد

• Marketing
• Innovation Diffusion
• New Product Growth
• +۷ مورد دیگر

Eitan Muller is a Professor of Marketing and Research Professor of Marketing at the Leonard N. Stern School of Business, New York University, where he has been a faculty member since 2004. He also holds affiliations with the Arison School of Business at Reichman University (IDC) in Israel. His academic work bridges marketing, economics, and technology, with a strong focus on innovation and digital markets. Ph.D., Managerial Economics, Northwestern University MBA (with distinction), Northwestern University B.Sc. in Mathematics (with distinction), Technion – Israel Institute of Technology His research centers on innovation diffusion , new product growth , and technology monetization , with deep exploration into pricing strategies , network externalities , and social influence in markets . He has pioneered models integrating customer lifetime value with diffusion theory, particularly in digital and two-sided markets. His recent publications span topics such as influencer marketing, mobile app monetization, and customer unit economics, reflecting a sustained focus on the evolving digital economy. Articles like Influencer Marketing Unlocked (2024) and Net Revenue Retention (2024) highlight his ongoing relevance in contemporary marketing challenges. Distinguished Marketing Scholar Award, European Marketing Academy (2019) Jan-Benedict Steenkamp Award for Long-Term Impact (2022, 2025) Multiple Best Paper Awards from the European Marketing Academy (1995, 2007, 2010, 2020) Fellow, European Marketing Academy Harold Maynard Award for contributions to marketing theory Muller has advised on numerous Harvard Business School cases on customer management, cohort analysis, and ride-hailing growth. He has served in editorial leadership for top journals including International Journal of Research in Marketing (Area Editor, Editor-in-Chief), and on the editorial boards of Marketing Science , Journal of Marketing , Journal of Marketing Research , and Management Science . He is also an active consultant and expert witness in the entertainment, media, and technology sectors, primarily through PricewaterhouseCoopers in Tel Aviv. He teaches the MBA course Marketing of Hi-Tech Products and a PhD seminar in quantitative methods, covering network models, survival analysis, and agent-based modeling. His co-authored books, including Innovation Equity and Innovation Diffusion and New Product Growth , are foundational texts in the field.