جستجوی استاد راهنمای دانشگاهی

• Human-Computer Interaction
• User Experience (UX)
• Human-Centered Artificial Intelligence
• +۴ مورد دیگر

Grazia Ragone is a Postdoctoral Researcher at the IVU Laboratory , Department of Computer Science, University of Bari Aldo Moro. Holding a PhD in Human-Computer Interaction from the University of Sussex and a Master's in Psychological Research Methods, she specializes in Usability, User Experience (UX), and Human-Centered AI , focusing on systems that integrate human factors for enhanced technology interaction. Academic Background: PhD in Human-Computer Interaction (University of Sussex, UK), Master’s in Psychological Research Methods (University of Bari) Key Research Areas: Social Motor Synchrony, Child-Computer Interaction, Trustworthy AI, Embodied Interaction, Autism Research, Usability Engineering Her recent work on the Future Artificial Intelligence Research (FAIR) project develops new metrics for human-AI symbiosis. She has presented at major conferences like Interaction Design and Children (IDC) and Advanced Visual Interfaces (AVI) , with publications in ACM Transactions and Springer LNCS. Scientific awards include the Microsoft Research Best Student Research Competition (2021) and IDC Conference Best Work in Progress (2020). Grazia actively contributes to academic governance as a member of ACM SIGCHI and SIGCHI Italy , and has organized international conferences like INTERACT 2021. She has delivered workshops on Child-Centered AI at institutions including the University of Delft and Sussex University.

Jinghai Raoمشاهده پروفایل

پژوهشگر

• Semantic Web Services
• Web Service Composition
• Security Policies
• +۳ مورد دیگر

Jinghai Rao is a Researcher at Carnegie Mellon University's School of Computer and Information Science within the Institute for Software Research International. His work focuses on semantic web services, security policies, and logic-based programming. He holds a PhD in Computer Science from the Norwegian University of Science and Technology (NTNU) and has Master's and Bachelor's degrees from Renmin University of China. His research emphasizes web service composition, policy enforcement, and automated reasoning. Notable contributions include the use of linear logic for service composition and frameworks for interleaving policy reasoning with service discovery. He has received a best paper runners-up award at ICWS 2004. Rao has been actively involved in professional activities, serving on committees for workshops like ECWS'06 and SOT'06, and as a reviewer for conferences such as IJCAI'05 and ISWC'05. His work bridges theoretical foundations of semantic web services with practical applications in security and collaborative systems.

Dipo Dunsinمشاهده پروفایل

مدرس

• Digital Forensics
• Cybersecurity
• Incident Response
• +۱ مورد دیگر

Dipo Dunsin serves as Lecturer in Computer Science & Applied Computing at London Metropolitan University, where he also manages the University's Digital Forensics Laboratory. His research develops innovative frameworks for malware investigation and cyber incident response. Dunsin's work applies reinforcement learning to automate threat analysis and evidence extraction, with recent focus on IoT forensics and dark web criminal activities. He creates specialized protocols like D2WFP for analyzing deep/dark web browsing and hybrid methods for detecting steganographic evidence in audio files.

Maurice E. Dawsonمشاهده پروفایل

دانشیار

• Cybersecurity
• Software Assurance
• Internet of Things (IoT)
• +۴ مورد دیگر

Maurice E. Dawson is an Associate Professor and Director of the Center for Cyber Security and Forensics Education (C²SAFE) at Illinois Institute of Technology's College of Computing. He holds multiple advanced degrees, including a Ph.D. in Cybersecurity from London Metropolitan University and a Postdoc in Information Science from Universidade Fernando Pessoa. His research focuses on software assurance, IoT security, and critical infrastructure protection, with over 150 peer-reviewed publications and book chapters. Affiliations: Illinois Tech, Fulbright Specialist Program, IEEE Senior Member Grants: Over $100K in grants from U.S. State Department, USAID, and others for cybersecurity initiatives in Africa and the Middle East. Research Interests: Explores hyperconnectivity risks, dark web extremism, and cross-border cybersecurity collaboration. His work bridges academic research with practical applications in developing nations, focusing on IT training and infrastructure resilience. Awards & Recognition: Recipient of Teaching Excellence Awards (2019, 2021), Fulbright Specialist grants (Botswana, Saudi Arabia), and volunteer service medals. Media engagements include ABC7 Chicago and Illinois Public Media for cybersecurity commentary. Advising & Grants: Supervised multiple USAID-funded ICT projects in Senegal and Guinea, training local agricultural and tech professionals. Served on advisory boards for CTU and VIU, and editorships for journals like International Journal of Hyperconnectivity and IoT . Labs & Teams: Leads C²SAFE lab at Illinois Tech, specializing in incident response, digital forensics, and AI-driven security solutions. Collaborates with international institutions on cybersecurity education frameworks.

LIANG Zhenkaiمشاهده پروفایل

دانشیار

• system and software security
• Web security
• mobile security
• +۶ مورد دیگر

Dr. LIANG Zhenkai is an Associate Professor and Chairman of the Department of Computer Science at the National University of Singapore's School of Computing. He also serves as the Lead Principal Investigator for the National Cybersecurity R&D Lab (NCL). With extensive experience in academic leadership and cybersecurity research, Dr. Liang has established himself as a prominent figure in the field of system and software security. Dr. Liang received his Ph.D. in Computer Science from Stony Brook University in 2006 and his B.S. degrees in Computer Science and Economics from Peking University in 1999. His dual background provides a unique perspective on security challenges that bridges technical expertise with economic understanding. Dr. Liang's research focuses on system and software security , with particular emphasis on security in emerging platforms including Web, mobile, and Internet-of-Things (IoT) systems. His specific research interests include program analysis, Web and IoT system security, and virtualization. As the leader of the Curiosity Research Group, his team pursues missions centered around "Understanding systems (理解系统), abstracting knowledge (提炼知识), and connecting facts (参悟规律)". This philosophical approach to security research has yielded numerous significant contributions to the field. Dr. Liang's recent publications demonstrate a strong evolution from fundamental security mechanisms to sophisticated solutions addressing AI security, blockchain, and advanced vulnerability analysis. His work increasingly integrates machine learning techniques with traditional security approaches, focusing on developing robust defenses against sophisticated attacks while maintaining system usability. The trend shows a progression toward addressing contemporary challenges in large language models, secure system observability, and vulnerability propagation analysis. Dr. Liang has received numerous prestigious awards recognizing his research excellence: Outstanding Paper Award at ACSAC (2003) Best Paper Award at USENIX Security Symposium (2007) ACM SIGSOFT Distinguished Paper at ESEC-FSE (2009) Best Paper Award at W2SP Workshop (2014) Annual Teaching Excellence Award at NUS (2014, 2015) As an educator, Dr. Liang has taught various undergraduate and graduate courses including CS3235 Computer Security, CS5231 Systems Security, and CS5321 Network Security. His teaching philosophy, which he has published on in "Tool, Technique, and Tao in Computer Security Education," emphasizes both technical expertise and philosophical understanding of security principles. He has successfully mentored numerous students and researchers in the cybersecurity field. Dr. Liang leads the Curiosity Research Group, which actively seeks curious minds to join their exploration of security systems. The group maintains strong connections with industry and government cybersecurity initiatives, particularly through the National Cybersecurity R&D Lab (NCL). Their research environment encourages innovative thinking with the requirement that "Curiosity is required, while mentality for repairing things (such as bicycles) is a plus."

• Data mining
• Reverse engineering
• Machine learning
• +۱ مورد دیگر

Mohammadhossein Amouei is a researcher and lecturer affiliated with McGill University's School of Information Studies. He holds the role of Course Lecturer for INFS 691: Computer Programming for Information Professionals. His primary research interests span data mining, reverse engineering, machine learning, and cybersecurity. He is affiliated with research labs including the Data Mining & Security Lab and the Accessible Computing Technology Research Group Lab. His educational background includes PhD candidacy at McGill University. Recent research focuses on reinforcement learning-driven vulnerability discovery in cybersecurity and natural language generation for assembly code documentation. He has contributed to federated learning security through game-theoretic frameworks. Advising and grants information is not explicitly detailed in available texts. He maintains an active presence on LinkedIn and GitHub, and his work bridges theoretical computer science with practical security applications.

Akos Ledecziمشاهده پروفایل

استاد

• Computer Science Education
• Wireless Sensor Networks
• Model Integrated Computing
• +۳ مورد دیگر

Akos Ledeczi is a Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on computer science education and wireless sensor networks (WSN) , with notable contributions to visual programming tools like NetsBlox and anti-poaching systems like WIPER. He holds a Ph.D. from Vanderbilt University and a Diploma from the Technical University of Budapest. His education initiatives include the NetsBlox platform for K-12 STEM education and a popular Coursera MOOC on introductory programming. In WSN, his team developed a countersniper system with real-time shooter localization and a wearable system for military applications. He is also a leader in Model Integrated Computing , creating tools like the Web-based Generic Modeling Environment. Recent work includes NSF-funded projects on cybersecurity education in middle schools and animal-borne acoustic monitoring. His awards include the ACM SenSys Test of Time Award (2014) and the Best Showpiece Award at IEEE VL/HCC (2021). Key grants and collaborations span NSF projects, Vodafone innovation programs, and the Cyber Makerspace initiative. His lab develops tools like DeepForge and RoboScape Online , emphasizing open-source and collaborative platforms. Students supervised include Devin Jean (K-12 tools), Gordon Stein (robotics simulations), and Brian Broll (NetsBlox extensions).

• Artificial Intelligence and Law
• Legal Compliance Systems
• Semantic Web Technologies
• +۲ مورد دیگر

Pompeu Casanovas Romeu serves as Adjunct Professor at La Trobe University and Research Professor at Autonomous University of Barcelona. His research bridges law, artificial intelligence, and cybersecurity, with extensive EU-funded projects including LYNX, SPIRIT, and OPTIMAI. He holds a Doctorate in Philosophy and Law degrees from Autonomous University of Barcelona, with postdoctoral research at University of California San Diego and Stanford. His research explores AI-driven legal compliance, semantic web applications for law, cybersecurity frameworks, and democratic governance models for digital technologies. Publications demonstrate sustained focus on regulatory models for emerging technologies, with recent work examining AI governance, blockchain privacy solutions, and Industry 4.0 legal frameworks. His research has secured significant funding, including multiple EU Horizon 2020 grants and Australian government CRC projects. Professor Casanovas directs the UAB Institute of Law and Technology and edits several academic journals including the Law, Governance and Technology Series (Springer) and Journal of Open Access to Law.

Juliana Freireمشاهده پروفایل

استاد

• Data Science
• Provenance Management
• Data Visualization
• +۲ مورد دیگر

Juliana Freire is an Institute Professor at NYU Tandon School of Engineering and Professor of Computer Science and Data Science. She co-directs the VIDA Center and leads research in data science, provenance management, and computational reproducibility. Her research develops methods for trustworthy data insight generation spanning large-scale data analysis, visualization, machine learning, and web information discovery. Applications include urban analytics and wildlife trafficking disruption. Publications demonstrate innovations in data exploration tools, provenance systems, and machine learning pipelines, with work appearing in SIGMOD, VLDB, and IEEE Transactions. ACM Fellow AAAS Fellow NSF CAREER Award IBM Faculty Award (2) Google Faculty Research Award ACM SIGMOD Contributions Award Advises graduate researchers and has secured funding from NSF, DARPA, Moore Foundation, and Sloan Foundation for data science infrastructure development. Leads the Moore-Sloan Data Science Environment at NYU and co-directs the Visualization Imaging and Data Analysis Center (VIDA).

• Artificial Intelligence
• Machine Vision
• Distributed Computing
• +۱۱ مورد دیگر

Dr. Dan Ionescu is a Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, Department of Electrical and Computer Engineering. He has been affiliated with the university since 1985, contributing extensively to teaching and research. His career includes visiting professorships at École Nationale Supérieure de Télécommunications (Paris) and Universitat Politècnica de Catalunya (Barcelona). He founded the Machine Intelligence Research Laboratory (1988) and the Network Computing and Control Research Laboratory (NCCT, 1999), which he currently directs. His research spans Artificial Intelligence, Machine Vision, Distributed Computing, Network Control, and Formal Methods. Notable contributions include methodologies in Expert Systems, Image Processing, Temporal Logic, and Network Management. His work has received industrial and governmental grants from CITO, Nortel, NSERC, and others. Recent research focuses on Web-based collaborative platforms (e.g., UC-IC, Watch-Together), Autonomic Computing, and AI applications in gesture control and 3D IR camera systems. Dr. Ionescu’s technical leadership includes pioneering the first distributed network management platform with industry partners and designing the NCIT*net 2 network architecture. His current interests include AI-driven solutions for cybersecurity, medical imaging, and IoT-enabled disaster response systems. He has advised numerous projects in AI ethics, quantum computing, and real-time control systems. His research trends emphasize interdisciplinary innovation, combining AI with healthcare (e.g., MRI analysis, deepfake detection), cybersecurity (GAN-based intrusion detection), and IoT (Salv AIoT platform). Collaborations with IBM CAS and Diatem Networks highlight his industry-academia integration. His legacy includes over 40 years of impactful contributions to computing and engineering education.

• Software Engineering
• Artificial Intelligence
• Chatbots
• +۳ مورد دیگر

Dr. Ahmad Abdel Latif is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary. Previously, he served as a postdoctoral researcher at DASLab, Concordia University, and earned his Ph.D. in Software Engineering from Concordia under Dr. Emad Shihab. His master’s degree was obtained from King Fahd University of Petroleum and Minerals (KFUPM). His research focuses on software engineering advancements in artificial intelligence, including chatbots, software quality, and mining software repositories. Notable projects include analyzing dependency ecosystems (e.g., NPM, Maven) for security risks, developing AI-driven chatbots for code repositories, and exploring machine learning model management challenges. He also investigates ethical implications of AI-generated code and open-source collaboration dynamics. Dr. Latif teaches ENSF 381: Full Stack Web Development and actively publishes on topics such as vulnerability mitigation, LLM-based chatbots, and software bot detection. His work bridges technical innovation with practical applications in cybersecurity, open-source ecosystems, and AI integration.

• Network Engineering
• Internet Infrastructure
• Data Analysis
• +۳ مورد دیگر

Zachary Bischof is a Researcher at Georgia Tech's School of Computer Science within the College of Computing. His work focuses on internet infrastructure, network reliability, and broadband analysis. He investigates topics such as outage detection, submarine cable networks, and the geographic and technical aspects of internet systems. His research spans from foundational studies on IPv4 utilization to applied projects like the iGDB platform integrating physical/logical network layers. Key areas of interest include internet measurement methodologies, infrastructure resilience, and the societal impact of telecommunications policies. He has contributed to improving outage detection algorithms, analyzing AS relationships, and evaluating consumer broadband experiences across diverse regions. His work often bridges technical and policy dimensions, emphasizing real-world applications. Notably, his publications explore undersea cable criticality, Google's AMP project's impact, and the utility of service-level agreements (SLAs) for broadband providers. While no formal awards are listed, his consistent output reflects sustained engagement with high-impact networking challenges. Zachary collaborates on projects like the Dasu platform for edge-based ISP measurements and has advised on submarine cable vulnerability assessments. His research integrates machine learning (e.g., hostname geolocation extraction) with traditional networking analysis, demonstrating interdisciplinary strengths. Future directions include expanding measurement frameworks and addressing emerging infrastructure challenges.

• Serious Games
• Game Design
• Virtual Reality
• +۳ مورد دیگر

Helmut Hlavacs is a Professor at the Faculty of Computer Science, leading the Research Group on Education, Didactics, and Entertainment Computing. His expertise spans serious games, game design, virtual reality, and health informatics. He has contributed to over 218 publications since 2005, focusing on topics like hedonic experiences in gaming, VR applications in therapy, and AI-driven behavior trees. His work intersects technology, education, and healthcare, with notable projects such as Conquer Catharsis (VR anxiety treatment) and PhyLab (VR physics experiments). Hlavacs has secured research funding for initiatives like Programmieren lernen durch Computerspielentwicklung and Dig-Equality FF , emphasizing digital equity and education. In 2019, he won the Best Poster Award at IFIP for his work on health data from serious games. Research Interests: Serious Games for health and education Virtual Reality applications in therapy and learning Game design methodologies and AI-driven NPC behavior Psychological impacts of gaming and digital consumption Procedural content generation for games Key Projects: Programmieren lernen durch Computerspielentwicklung (2008): Game-based learning for programming skills Dig-Equality FF (2020-2021): Digital competence promotion for equity TP1 PRECIOUS (2013-2016): VR conferencing and stress management Grants and Advising: Hlavacs has advised on projects involving AI in military command systems, VR therapy for anxiety disorders, and participatory design of social media literacy tools. He collaborates internationally on topics like gamification for behavior change and multicultural health interventions. Labs/Teams: His research group focuses on Serious Storytelling and Entertainment Computing , developing tools like the Prototypical game framework and InvisibleSound for blind musicians. Current work includes FiGHT (a web-based tool for eating disorder communication) and OutSmart! (a serious game for social media literacy).

• Cybersecurity
• Healthcare IT Security
• Machine Learning
• +۴ مورد دیگر

Carlos Cilleruelo Rodríguez is an Associate Professor in the Department of Computer Science at Universidad de Alcalá. He is affiliated with the TIFyC research group ("Information Technologies for Training and Knowledge") and specializes in cybersecurity, healthcare IT security, and authentication systems. His research focuses on dark web analysis, malware detection, and adaptive security frameworks. He earned his Doctorate from Universidad de Alcalá in 2023 with the thesis "A cybersecurity review of healthcare industry 2023" , supervised by Dr. José Javier Martínez Herráiz and Dr. Luis de Marcos Ortega. His work spans ransomware mitigation in manufacturing, continuous authentication architectures (JBCA), and privacy issues in IoT healthcare devices. Recent projects include the ProTego initiative for mobile authentication in eHealth environments. Publications highlight trends in machine learning for behavioral authentication, darknet interconnections, and security in Bring-Your-Own-Device (BYOD) healthcare settings. No scientific awards explicitly mentioned. Labs/teams: Active contributor to the TIFyC group, focusing on cybersecurity education and applied research in critical infrastructure protection.

Ganeshsree Selvachandranمشاهده پروفایل

استاد

• Artificial Intelligence
• Fuzzy Mathematics
• Deep Learning
• +۱۲ مورد دیگر

Ganeshsree Selvachandran is a Professor at the School of Business, Monash University Malaysia (MUM), where she conducts cutting-edge research in artificial intelligence, fuzzy mathematics, deep learning, and computational intelligence. She is actively involved in PhD supervision and leads significant research projects in biomedical imaging and forecasting. PhD in Pure Mathematics, Universiti Kebangsaan Malaysia (UKM), 2013 MSc in Pure Mathematics, Universiti Kebangsaan Malaysia (UKM), 2010 BSc (Hons) in Mathematics, Universiti Kebangsaan Malaysia (UKM), 2009 Her research focuses on fuzzy mathematics , deep learning , computational intelligence , and hybrid AI models , with applications in biomedical imaging (e.g., lung cancer detection), financial and environmental forecasting, and emotion recognition. She develops advanced fuzzy logic systems integrated with neural networks for real-world diagnostic solutions. The recent publications highlight a strong trend in applying deep convolutional neural networks and fuzzy logic to medical diagnostics, particularly in lung cancer and diabetic retinopathy detection. Her work increasingly combines generative models and hybrid AI for data augmentation and improved accuracy in healthcare applications. She also contributes comprehensive reviews in AI subfields, establishing foundational knowledge in reinforcement learning and medical AI. Scientific Awards and Recognitions: Ranked No. 6 globally in fuzzy sets/systems research by Scopus (2019) Member, Special Interest Group on Blue Economy, Malaysian Academy of Sciences (2020) Contributor to the Position Paper on Blue Economy (2022) Recipient of multiple national and international research awards Dr. Selvachandran has secured over MYR880,000 in research funding, including four Fundamental Research Grant Scheme (FRGS) grants, an industry grant from MTSFB, and a professorial chair grant from PNB. She mentors PhD students and collaborates on interdisciplinary projects. She serves as an editor for top journals like Engineering Applications of Artificial Intelligence and Computers and Electrical Engineering , and has reviewed over 150 papers for Web of Science/Scopus-indexed journals. She is involved in active research projects such as Advancing Lung Cancer Detection through Deep Fuzzy Convolutional Neural Networks and Sustainability Impact: Case Studies of UNGCMYB Member Companies . She also holds an adjunct professorship at Symbiosis International University (2023–2025), contributing to international academic collaboration.