جستجوی استاد راهنمای دانشگاهی

Jean Mayoمشاهده پروفایل

دانشیار

• Distributed Systems
• Operating Systems
• Security
• +۳ مورد دیگر

Dr. Jean Mayo is an Associate Professor in the Department of Computer Science at Michigan Technological University (MTU), where she has served since 1997. She also serves as the Graduate Program Director for the Computer Science program. Her academic background includes a PhD and MS in Computer Science from the College of William and Mary, and undergraduate degrees in Physics (Longwood University) and Mechanical Engineering (Georgia Tech). Dr. Mayo's research focuses on distributed systems, operating systems security, and computer science education. She has developed multiple visualization tools for teaching concepts such as secure coding (e.g., SecureCvisual), cryptography (AESvisual, DESvisual), and access control (RBACvisual, MLSvisual). These tools emphasize hands-on learning for critical topics like concurrency, memory management, and system permissions. Her work in distributed computing includes algorithms for predicate detection, deadlock resolution, and termination detection in dynamic systems. Notable collaborations include grants from NSF for curriculum development in concurrent computing and distributed systems education. She has advised 18 MS students and 1 PhD student to date, with current advisees Lihui Hu and Paul Bonamy. Dr. Mayo has held leadership roles in integrating advanced systems laboratories into undergraduate education and has contributed to the design of fault-tolerant distributed computing curricula for software engineering programs.

Abdulrauf A. Gidadoمشاهده پروفایل

استادیار

• Database Systems
• Data Mining
• Artificial Intelligence
• +۳ مورد دیگر

Abdulrauf A. Gidado is an Assistant Professor in the School of Computer Science at the University of Windsor, affiliated with the Faculty of Science. A professional member of the Association for Computing Machinery (ACM), he holds a Ph.D. in Computer Science from the University of Windsor. His research encompasses database design, data warehousing, big data analytics, recommendation systems, database security, social network mining, and applied artificial intelligence. Additional interests include image processing and computer architecture.

• Cognitive Modelling & Computing
• Computational Intelligence
• Evolutionary Algorithms
• +۷ مورد دیگر

Dr. Aznam Yacoub is an Assistant Professor at the School of Computer Science, University of Windsor. His research focuses on cognitive modelling, computational intelligence, and formal methods in system engineering. He holds a Ph.D. in Computer Science from Aix-Marseille Université (2016). His work integrates simulation and formal verification techniques, particularly through extensions of PROMELA (DEv-PROMELA) for discrete-event systems. Key research areas include evolutionary algorithms, software/system engineering methodologies, and modelling complex systems such as mobile ad-hoc networks and virtual game architectures. He explores human-machine interaction, extended reality (metaverse), and computational philosophy. His educational interests span computer science pedagogy and the theory of computation. Dr. Yacoub's recent work emphasizes interdisciplinary applications like disaster response infrastructure simulation and adaptive storytelling in virtual environments. His technical contributions bridge formal verification with simulation frameworks, enhancing reliability in complex system design.

Brook Wuمشاهده پروفایل

دانشیار

• Text Mining
• Information Extraction
• Natural Language Processing
• +۵ مورد دیگر

Brook Wu is an Associate Professor in the Informatics Department at New Jersey Institute of Technology (NJIT) and serves as Associate Dean for Academic Affairs. She holds a Ph.D. in Information Science from SUNY Albany (2001), an M.S. in Information Resources Management from Syracuse University (1996), and a B.B.A. in Management Information Systems from Tamkang University (1993). Her research focuses on text mining, natural language processing, and information retrieval, with applications in fake news detection on social media and automated feedback systems for education. She developed systems like Fned for fake news detection and tools for writing-to-learn activities. Her work integrates machine learning, user behavior analysis, and educational technology to enhance learning outcomes and information access. Her research portfolio includes over 30 publications, spanning topics from conceptual term extraction in medical documents to personalized query refinement in digital libraries. She is also a proponent of leveraging computational methods for educational assessment, such as analyzing class discussion messages to evaluate student performance. Her contributions have been presented in venues like the International Conference on Data Mining and the Journal of the American Society for Information Science and Technology. She maintains an active research website at http://web.njit.edu/~wu . In academic leadership, she has championed initiatives like the NJIT ADVANCE program, applying social network analysis to support faculty mentoring. Her interdisciplinary approach bridges computer science, education, and information science, addressing challenges in both technological innovation and pedagogical practice.

Miltos Petridisمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Case-Based Reasoning (CBR)
• +۷ مورد دیگر

Professor Miltos Petridis is the Head of the Department of Computer Science at Middlesex University. His research focuses on artificial intelligence, with particular emphasis on case-based reasoning (CBR), machine learning, and their applications in cybersecurity, recommendation systems, healthcare analytics, and business process optimization. He leads projects involving CBR integration with deep learning models for tasks like fraud detection, medical diagnosis, and network intrusion prediction. His work spans theoretical advancements in temporal reasoning and practical implementations in domains such as computational fluid dynamics and mobile network optimization. He has contributed to frameworks like CBR-WIMS for intelligent business process monitoring and collaborative reasoning systems. Professor Petridis collaborates extensively on interdisciplinary projects, including crime prevention via mobile apps and big data analysis, and has published widely in top-tier AI and computer science venues. His research trends highlight a blend of foundational AI methodologies with real-world applications, emphasizing hybrid approaches that combine CBR with neural networks, clustering, and ensemble techniques to address complex problems in diverse sectors. While no specific awards are listed, his contributions reflect sustained innovation in AI-driven solutions for industry and academia.

Hoda Khalilمشاهده پروفایل

استاد مدعو

• Software Engineering
• Modeling and Simulation
• Data Science
• +۷ مورد دیگر

Dr. Hoda Khalil is an Adjunct Research Professor and Contract Instructor in the Department of Systems and Computer Engineering at Carleton University, where she holds a Ph.D. Her research focuses on software engineering, modeling and simulation, and data science. She actively contributes to interdisciplinary projects, including environmental monitoring via Cell-DEVS models, pandemic-related indoor CO2 dispersion studies, and public transit data analysis. Dr. Khalil also explores pedagogical frameworks to bridge academic, industrial, and governmental needs in data science education. Education: Ph.D. in Systems and Computer Engineering, Carleton University Research Interests: Software Engineering methodologies Simulation frameworks for environmental and social systems Data-driven approaches in public policy and industry Machine learning for dynamic knowledge graphs Publications: Her recent work spans cloud-edge provisioning for IoT, CO2 dispersion modeling using Cell-DEVS and deep learning, and pandemic-era labor market analysis. She has developed automation tools like CD2 for CO2 diffusion modeling and contributed to finite state machine testing methodologies. Awards: None explicitly listed. Advising & Grants: No student advisees or grant information provided. Engages in curriculum development and industry collaboration through her teaching and research roles. Labs/Teams: Collaborates with interdisciplinary teams focused on environmental systems modeling, data science education, and pandemic response technologies.

• Health IT Systems Design
• Human-Computer Interaction
• Human Factors Engineering
• +۵ مورد دیگر

Akanksha Singh is an Assistant Professor and Assistant Professor (P) at the School of Health Professions, Health Services Administration, University of Alabama at Birmingham since August 2023. She holds a PhD in Informatics from the University of South Carolina (2023) and has extensive experience in health information systems design, human-computer interaction, and applied artificial intelligence techniques in healthcare. Her research focuses on human factors in health IT systems, including patient preferences in clinical decision support, health recommender systems (HRS), and community health information networks (CHINs). Education includes a Master of Science in Computer Science (2017) and Bachelor of Technology in Computer Science (2012) from the University of South Carolina and Jaypee Institute of Information Technology. She has held roles as a Research Scientist at the Center for Effectiveness Research in Orthopedics and served as a Graduate Research Assistant and IT Research Manager. Research interests span Health IT systems design, human factors, data analytics, and AI applications in healthcare. Notable projects include the CHIPSS information system for substance use recovery, I-C-IT orthopedic treatment recommender, and the STORY+ app for breast cancer adherence. Awards include the AMIA 2020 Distinguished Poster Award and multiple graduate fellowships. Her work integrates Design Science Research (DSR) methodologies, emphasizing iterative software artifact development. Active in teaching, she has instructed courses on health information systems management and HCI at both UAB and USC. Technical expertise includes programming in Python, PHP, JavaScript, and platforms like MS SQL Server and PowerBI.

Srikanth Mudigondaمشاهده پروفایل

دانشیار

• Machine Learning
• Agent-Based Modeling
• Computer Science Education
• +۳ مورد دیگر

Srikanth Mudigonda, Ph.D., serves as Associate Dean of Academic Affairs and Director of Analytics at the School for Professional Studies (SPS) at Saint Louis University. He holds an Associate Professor position in the Computer Information Systems department. His academic background includes a Ph.D. in Business Administration with an emphasis in Information Systems from the University of Missouri-Saint Louis, an M.S. in Information Systems (Data Management specialization) from Dakota State University, and dual degrees from Birla Institute of Technology and Science in India. His research focuses on modeling social phenomena emergence and innovative education methodologies in computing. Key areas include agent-based modeling, machine learning applications, and data science pedagogy. He has published extensively in computational social sciences, educational technology, and information systems journals. Dr. Mudigonda has received multiple recognitions including three Faculty Excellence Awards from SPS (2020, 2017, 2013) and the SLU Student Government Award. His professional affiliations include the ACM SIGSIM and Computational Social Science Society of the Americas. His recent work emphasizes interdisciplinary applications of analytics, particularly in health insurance disparities modeling and geospatial data analysis. Collaborative projects include developing simulation platforms for social processes and enhancing educational technology adoption in higher education environments.

Georgia Kapitsakiمشاهده پروفایل

دانشیار

• Software Engineering
• Open Source Software
• Context-aware Systems
• +۲ مورد دیگر

Georgia Kapitsaki is an Associate Professor in the Department of Computer Science at the University of Cyprus. She holds a PhD from the National Technical University of Athens (2009) and has extensive experience in both academia and industry. Her research focuses on Software Engineering, particularly Open Source Software Reuse, Context-aware Applications, and Privacy Enhancing Technologies. Recent work examines GDPR compliance in software systems, open source ecosystems, and human aspects of software development. Awards received: Best Paper Award, ICSR 2015 Best Paper Award, MODELS 2008 Doctoral Symposium She has organized international conferences (ICSME 2022, SAC 2019, ICSR 2016), serves on program committees, and contributes to open source projects. She represents the University of Cyprus at GFOSS Open Technologies Alliance and has secured EU funding for research projects.

• Semantic Computing
• Text Mining
• Artificial Intelligence
• +۴ مورد دیگر

Dr. René Witte is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on semantic computing, text mining, artificial intelligence, and data science, with applications in knowledge graphs, semantic publishing, and intelligent information systems. He leads the Semantic Software Lab, developing tools like ScholarLens and OpenTrace to enhance semantic analysis and knowledge integration. Key research areas include semantic user profiles, automated knowledge base construction, and natural language processing (NLP) for scientific literature. His work bridges NLP, semantic web technologies, and software engineering, addressing challenges in data interoperability and user-centric systems. Publications highlight advancements in semantic search, Linked Open Data frameworks, and tools for text mining in biomedical and software engineering contexts. His contributions span academic conferences and journals, emphasizing practical applications of semantic technologies.

Marija Bezbradicaمشاهده پروفایل

دانشیار

• Educational Analytics
• Computational Finance
• Complex Systems
• +۲ مورد دیگر

Dr. Marija Bezbradica serves as Associate Professor and COMBUS Programme Board Chair at Dublin City University's School of Computing. Her research bridges computational finance, educational analytics, and complex systems modeling. Key research areas include financial risk modeling using Bayesian methods, educational data mining for programming courses, and healthcare analytics for infection control. She holds affiliations with ADAPT (FinTech research), ARC-SYM (complex systems modeling), and Lero (software engineering). Recent publications demonstrate cross-disciplinary applications, spanning cryptocurrency market analysis, hospital readmission prediction, and synthetic data generation for medical conditions. Work frequently employs machine learning, graph-based methods, and advanced statistical modeling. No information is available regarding awards, supervised students, or specific laboratory facilities.

Kelsey Fultonمشاهده پروفایل

استادیار

• Secure Software Development
• Human-Computer Interaction
• Cybersecurity
• +۴ مورد دیگر

Kelsey Fulton is an Assistant Professor in the Department of Computer Science at the Colorado School of Mines. Their research focuses on human-centric approaches to secure software development, emphasizing developer mental models, tool usability, and organizational processes. They hold a PhD and M.S. in Computer Science from the University of Maryland and a B.S. in Computer Science and Mathematics from Millersville University. Education : Ph.D., Computer Science, University of Maryland (2023) M.S., Computer Science, University of Maryland (2019) B.S., Computer Science and Mathematics, Millersville University (2017) Research Interests : Fulton’s work bridges human factors and technical security, investigating how developers reason about security, the usability of secure tools, and systemic barriers in secure development. Their goal is to provide evidence-based recommendations for improving policies, education, and tools. Notable Achievements : Recipient of the 2023 John Karat Usable Security and Privacy Student Research Award Best Paper Award at USENIX Security Symposium Advising & Community : Fulton mentors undergraduate and Master’s students, emphasizing work-life balance and community engagement. They prioritize fostering a supportive environment for researchers in cybersecurity and advocate for inclusivity in the field.

• E-Learning
• Virtual Worlds
• Information Systems
• +۳ مورد دیگر

Frank Kappe is a Professor at Graz University of Technology's Institute of Human-Centred Computing, specializing in e-learning systems, virtual environments, and web technologies. His research integrates educational innovation with computational solutions, focusing on scalable learning architectures and interactive platforms. His work spans digital manufacturing platforms, visual document exploration systems, and adaptive content delivery frameworks. Recent studies examine blockchain applications in education, flipped classroom models, and security vulnerabilities in learning management systems. Kappe maintains an extensive publication record exploring human-computer interaction paradigms, collaborative learning tools, and real-time communication systems for education. His technical innovations include mentoring session architectures using Reverse AJAX and intelligent curriculum assistants.

Muhammad Azeem Abbasمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۸ مورد دیگر

Dr. Muhammad Azeem Abbas is a Lecturer in Information Systems & ICT at Aston University's Aston Business School (College of Business and Social Sciences). He specializes in Artificial Intelligence, Machine Learning, and Semantic Web technologies with applications in education, construction, and agriculture. His teaching spans Information Systems, Machine Learning, and Web Development. He has held roles at multiple institutions including the University of Wales Trinity Saint David and Leeds Beckett University. Abbas holds a PhD in Information Technology from Universiti Teknologi Petronas and an MSc in Computer Science from Mohammad Ali Jinnah University. His research focuses on AI-driven solutions for educational systems (e.g., intelligent tutoring, EAL writing support), construction automation (BIM execution plans), and healthcare (CVD prediction). He has co-authored over 30 peer-reviewed articles and serves on the editorial board of Computers and Education: Artificial Intelligence . His work emphasizes bridging technological gaps in education and urban infrastructure through innovative systems like the Adapt-ABLE smart housing adaptation framework. Abbas actively supervises graduate students and oversees the MSc Digital & Technology Solutions Specialist Apprenticeship program. His professional service includes roles on academic misconduct committees and global software development research. His recent publications (2020–2023) reflect interdisciplinary themes in AI applications, smart city frameworks, and mobile learning innovations.

Nikola Nikolovمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Graph Drawing
• +۵ مورد دیگر

Nikola Nikolov is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. He holds memberships in the Centre for Research Training in Foundations of Data Science, the Data-Driven Computer Engineering Research Centre, and Lero – the Irish Research Centre for Software, reflecting his deep integration into Ireland's national research infrastructure. His research spans Machine Learning, Natural Language Processing, and Graph Drawing, with specialized expertise in deep learning architectures, matrix factorization techniques, and feature extraction methodologies. Current work focuses on multilingual NLP applications for social media analysis, convolutional neural network optimizations, and collaborative filtering systems, demonstrating consistent innovation across computational linguistics and graph theory domains. Analysis of his 2023-2025 publications reveals a dominant focus on combating online toxicity through advanced NLP systems for racism and hate speech detection across multiple languages, alongside significant contributions to computer vision efficiency and recommendation system architectures. His work bridges theoretical advancements with real-world applications in healthcare analytics and autonomous systems. Prof. Nikolov actively contributes to UN Sustainable Development Goals through data science applications while maintaining strong industry connections via research centres focused on software innovation and data-driven engineering solutions.