جست‌وجوی استاد و پژوهشگر

Heiko Mantelمشاهده پروفایل

استاد

• Information Security
• Formal Methods
• Concurrency
• +۲ مورد دیگر

Heiko Mantel is Professor of Computer Science at TU Darmstadt, specializing in information security and formal methods. As spokesman for the LOEWE research focus Software-Factory 4.0, he coordinates interdisciplinary projects on reliable software systems. His research develops foundational and applied approaches to security challenges, including information-flow control, side-channel mitigation, and quantum cryptography. Current projects investigate rigorous cache side-channel defenses, decentralized mobile security enforcement, and quantum-secure communication systems. Professor Mantel leads several collaborative initiatives including the DFG-funded SeRCA project on cryptographic algorithm refinement and the ATHENE national research center's work on distributed workflow security. His group develops tools like RiCaSi for hardware-level security and CliSeAuDroid for mobile application protection.

Stephen Huangمشاهده پروفایل

استاد

• Cybersecurity
• Intrusion Detection
• Data Science
• +۳ مورد دیگر

Stephen Huang is Professor of Computer Science at the University of Houston's College of Natural Sciences and Mathematics. He directs the Center for Cybersecurity Research and has held administrative roles including Department Chairman and Director of Graduate Studies. He received his PhD in Computer Science from the University of Texas-Austin and served as National Research Council-NASA Senior Research Associate at NASA Goddard Space Flight Center. His 40+ year career encompasses cybersecurity research, algorithm design, and academic leadership. Research focuses on intrusion detection systems, malware analysis, network security, and applied algorithms. His work integrates machine learning with security applications, particularly in anomaly detection and behavioral analysis. Recent projects include NSA-funded research on automated intrusion detection through metadata traffic analysis. Publications demonstrate progression from foundational algorithms to advanced AI applications in security. Recent articles focus on VPN detection, Android malware analysis, and large language model interpretability, consistently applying computational theory to cybersecurity challenges. He leads the GAANN Fellowship Program in Cybersecurity and Research Experience for Undergraduates (REU) initiatives. His laboratory develops practical security solutions through collaborations with government agencies and industry partners.

Yutian Tangمشاهده پروفایل

استادیار

• AI+SE (Large-language Model+SE)
• Program Analysis
• Empirical Software Engineering
• +۴ مورد دیگر

Dr. Yutian Tang is an Assistant Professor at the University of Glasgow's School of Computing Science. He holds a Ph.D. from The Hong Kong Polytechnic University and a B.Sc. from Jilin University. His research focuses on AI-driven software engineering, program analysis, and mobile app security, with over 40 publications in top venues like ESEC/FSE and IEEE TSE. He has received awards including the ISSRE'18 Best Industry Paper and Shanghai Pujiang Talent Program. Current research emphasizes automated testing, bug localization, and LLM applications in software engineering. Education: Ph.D., Department of Computing, The Hong Kong Polytechnic University B.Sc., Computer Science, Jilin University Research Interests: His work spans AI+SE (Large Language Models in Software Engineering), automated testing, privacy protection, and malware detection. Notable contributions include XDebloat (app debloating) and tools for analyzing Android vulnerabilities. He actively explores LLM applications for code generation and test suite optimization. Grants & Funding: EPSRC Peer Review College member National Natural Science Foundation of China (NSFC) grant (2023-2025) OpenAI API Researcher Access Program (2024) Google Cloud Research Credits (2024) Service & Leadership: Editorial Board Member of Frontiers in Computer Science , PC member of ICSE, ESEC/FSE, ASE, and other top conferences. Active in reviewing for IEEE Transactions and ACM journals. Future Directions: Tool support for automated bug detection, LLM integration in software lifecycle, and large-scale binary code analysis.

• Cybersecurity
• Automotive Systems
• Formal Methods
• +۴ مورد دیگر

Dr Hoang Nga Nguyen is an Associate Professor in Cyber Security at Swansea University, UK. Affiliated with the School of Mathematics and Computer Science, his work focuses on cybersecurity for automotive and autonomous systems, formal verification, and embedded systems security. He leads research projects funded by EPSRC, RSSB, InnovateUK, and Digital Catapult, including AutoCHERI (2022-2024) and QRNG for CAV . Current research agenda: Cybersecurity in automotive systems Specialization: Model-based and simulation-based verification techniques Projects: VRBMAS, ACID, Ditto, Secure CAV His research contributions span: Cybersecurity frameworks for automotive systems Formal methods in railway safety Embedded systems threat landscapes Resource-bounded agent logic Android app collusion detection Scientific Awards and honors: None explicitly mentioned in the provided text. As a supervisor , he guides PhD students in topics like: Addressing Automotive User-Centric Privacy and Security Model-Based Security Testing Approaches for Hardware Security He also teaches modules including Software Security Engineering (CS-239) and Embedded Systems Security (CSCM68, CSCM868) . Nguyen works at the Computational Foundry on Bay Campus, Swansea, contributing to the Verification & Validation of Autonomous Systems network and the European Technical Working Group on Formal Methods in Railway Control.

• Graph-based learning
• Adaptation and learning in non-stationary environments
• Intelligence for embedded systems
• +۵ مورد دیگر

Cesare Alippi is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), and also holds a professorship at Politecnico di Milano, Italy. He serves as a visiting Professor at Guangdong University of Technology (China) and Consultant Professor at Northwestern Polytechnic of Xi'an (China). His academic leadership extends to multiple international institutions where he has served as a visiting researcher including UCL (UK), MIT (USA), ESPCI (France), CASIA (China), A*STAR (Singapore), and University of Kobe (Japan). Professor Alippi's research interests center around graph-based learning, adaptation and learning in non-stationary environments, and intelligence for embedded, cyber-physical systems and IoT. His work bridges theoretical foundations with practical applications in sensor networks, environmental monitoring, and industrial processes. He has established significant research infrastructure including the Wireless Embedded Systems (WEmSy) Lab and the Internet of Things Lab, with notable deployments for marine environment monitoring in Queensland, Australia and the Fiji Islands, as well as rockfall and landslide monitoring systems across Italy and Switzerland. His research output shows a clear evolution toward graph-based deep learning approaches for time series analysis, anomaly detection, and spatiotemporal forecasting, reflecting the growing importance of graph neural networks in handling complex relational data in non-stationary environments. Major Awards: IEEE CIS Enrique Ruspini Meritorious Service Award (2024) IEEE CIS Outstanding Computational Intelligence Magazine Paper Award (2018) Gabor Award from International Neural Network Society (2016) IBM Faculty Award (2013) IEEE Instrumentation and Measurement Society Young Engineer Award (2004) Professor Alippi has held significant leadership roles including Past Board of Governors member of the International Neural Network Society, Past member of the Administrative Committee of the IEEE Computational Intelligence Society, and Past Vice-President for Education of the IEEE Computational Intelligence Society. He has served as Associate Editor for Proceedings of IEEE and several other prestigious journals. His research has been supported through numerous grants including an IBM Faculty Award in 2013 specifically for research on Intelligent Embedded Systems working in non-stationary environments. His research infrastructure includes the Wireless Embedded Systems (WEmSy) Lab and the Internet of Things Lab, with notable deployments including a sophisticated automatic, adaptive, sustainable and reliable wireless monitoring system for marine environments deployed in Queensland, Australia (2007) and under deployment at the Fiji Islands (2014-2015). He has also led several top-world deployments for rockfall and landslide monitoring across Italy and Switzerland since 2010, demonstrating the practical impact of his research in real-world harsh environments.

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۴ مورد دیگر

XIE Xiaofei is an Assistant Professor of Computer Science at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). He holds the Lee Kong Chian Fellowship and has a PhD from Tianjin University (2018). Previously, he was a postdoctoral researcher at Nanyang Technological University (NTU, 2018–2021). His research focuses on program analysis, software testing, vulnerability detection, and AI system quality assurance. Key areas include adversarial attacks on deep learning systems, autonomous driving testing, and secure software development. He actively advises PhD students and collaborates on projects like the GameRTS framework for video game testing and BehAVExplor for autonomous systems. Education : PhD, Tianjin University, 2018 Postdoctoral Research, NTU Singapore, 2018–2021 Research Interests : Dr. Xie explores cutting-edge topics such as neural network testing , AI security , and large language model (LLM) reliability . He develops tools like DeepHunter for DNN fuzz testing and CAShift for cloud attack detection. His work bridges theory and practice, addressing real-world challenges in software safety and AI robustness. Recent Contributions : His publications span top venues (ICSE, ASE, CVPR) and include innovations like behavior diversity testing for autonomous vehicles and multi-target backdoor attacks on code models. He also leads initiatives to enhance federated learning security and LLM vulnerability detection. Awards & Recognition : ACM Tianjin Doctoral Dissertation Award (2019) ACM SIGSOFT Distinguished Paper Award (ISSTA 2022) Best Paper Award, APSEC 2020 3 rd place in AI Singapore’s Trusted Media Challenge (2022) Advising & Grants : He mentors seven PhD/MSc students and leads research teams funded by initiatives like SMU’s Lee Kong Chian Fellowship. His labs focus on autonomous systems testing and AI-driven security tools .

Jennifer Fisherمشاهده پروفایل

استاد

• Contemporary Art
• Curatorial Studies
• Exhibition Practices
• +۴ مورد دیگر

Jennifer Fisher is a Professor in the Department of Visual Art and Art History at York University's School of the Arts, Media, Performance & Design (AMPD). She holds a BFA from NSCAD University, and MA and PhD degrees from Concordia University. Her academic work integrates curatorial practice with research in contemporary art, sensory aesthetics, and feminist theory. Research Focus Fisher's research explores interdisciplinary intersections including: Exhibition studies and archival reinterpretation Affect theory and non-visual sensory aesthetics Feminist performance and display practices Curatorial methodologies and artist archives Professional Recognition Contemporary Art Fellow at the National Gallery of Canada Research affiliations at Cornell University and NYU Tisch School of the Arts Co-founder of the Journal of Curatorial Studies Founding member of DisplayCult curatorial collective Notable Projects Fisher co-curated 'Archives by Artists' (2024) at the Archives of Ontario, featuring 18 international artists who reconceptualize archival practice through interactive multiples. The exhibition engaged AMPD students in hands-on curation and will travel to Québec in 2025. Her work frequently integrates academic research with public-facing curation.

Suzanna Schmeelkمشاهده پروفایل

دانشیار

• Cybersecurity
• Computational Thinking
• Mathematics Education
• +۴ مورد دیگر

Dr. Suzanna Schmeelk is an Associate Professor of Cybersecurity and Director of St. John's University's M.S. in Cyber and Information Security program. She holds nine degrees, including two doctorates in Computing and Mathematics Education. Her academic journey includes teaching and visiting research roles at institutions like Rutgers, Columbia, and NYU. She specializes in Cybersecurity, Mobile/Health Technology Security, Computational Thinking, and Social Justice. Dr. Schmeelk has contributed to over 80 publications, focusing on topics like Android malware analysis, blockchain in healthcare, and cybersecurity education methodologies. Education: D.P.S. in Computing (Mobile Security), Pace University Ed.D. in Mathematics Education, Rutgers University M.B.A. (Cybersecurity), University of Maryland Global Campus 5 M.S. Degrees: Health Informatics (Cornell), Cybersecurity (UMGC), Data Visualization (Parsons), Computer Science (College of William & Mary), Technology Management (NYU) B.S. in Computer Science & Mathematics, University of Richmond Research Interests: Cybersecurity, Machine Learning, Mathematics Education, Mobile/Health Tech Security, Risk Management, and Social Justice. She emphasizes practical applications of cybersecurity in healthcare, education, and ethical technology. Courses Taught: Over 20 courses including Foundations of Cybersecurity, Network Security, Penetration Testing, and Digital Forensics. She develops innovative curricula like the ABET-accredited Cybersecurity program. Labs/Teams: Director of St. John's Cyber Security Center of Excellence, collaborating on industry-driven research projects.

DING Xuhuaمشاهده پروفایل

استاد

• System/software security
• Applied cryptography
• Hardware-assisted secure systems
• +۴ مورد دیگر

DING Xuhua is a Professor of Computer Science at the School of Computing and Information Systems , Singapore Management University . He directs the Centre on Security, Mobile Applications & Cryptography (SMC) and leads research in system/software security and applied cryptography. PhD in Computer Science from the University of Southern California (2003) Prior degrees: B.Eng and M.Sc from Shanghai JiaoTong University His research focuses on trustworthy systems using hardware virtualization to counter kernel/user-space attacks, with emphasis on: Virtualization-based malware analysis Hybrid symbolic execution frameworks Secure forensics on compromised TrustZone/ARM devices Privacy-preserving cryptographic protocols Content-based video stream authentication His recent publications (2025-2021) span computer science , cybersecurity , and applied cryptography , with a trend toward hardware-assisted security and dynamic analysis tools. Notable awards include the Best student paper (ACISP 2012) and Best paper (IFIP CMS'12) . He mentors PhD students and leads two NRF research grants , with open positions for postdocs and engineers at OASIS and SMC labs.

Haipeng Caiمشاهده پروفایل

دانشیار

• Software Security
• Software Engineering
• Program Analysis
• +۴ مورد دیگر

Haipeng Cai is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. Previously, he served as an Assistant Professor (2016–2022) and tenured Associate Professor (2022–2024) at Washington State University. His research focuses on software engineering and security, particularly program analysis, machine learning for security applications, and multilingual software systems. He holds a PhD in Computer Science and Engineering from the University of Notre Dame (2015). Education: PhD in Computer Science & Engineering (University of Notre Dame, 2015). Research interests include: Software security and reliability of distributed systems Machine learning-driven vulnerability detection and patching Analysis of multilingual software and cross-language bugs Tools like VGX (vulnerability data generation), PyRTFuzz (Python runtime fuzzing), and PolyFuzz (multi-language system fuzzing) Notable awards include the 2025 TOSEM Outstanding Paper Award for malware detection sustainability, multiple Distinguished Reviewer Awards, and the 2022 Junior Faculty Research Award. His work has led to over 50 publications, with a focus on practical security solutions. Advising: Mentor to students like Wen (PhD 2024, now at Utah State), Xiaoqin (first PhD graduate from his lab), and current advisees Haoran, Jiawei, and Yu. Projects include grants from NSF, ONR, and the Open Technology Fund. Key contributions include tools like VulGen (vulnerability dataset generation) and FlowDist (distributed system analysis), and labs focused on AI-driven security and multilingual software engineering.

Ryan Bentonمشاهده پروفایل

دانشیار

• Data Mining
• Machine Learning
• Big Data
• +۴ مورد دیگر

Dr. Ryan Benton is an Associate Professor and Chair of the Department of Computer Science at the University of South Alabama. He holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette (2001). His research focuses on Data Mining, Machine Learning, and their applications in Cyber-Security, Digital Forensics, and Biomedicine. He has advised numerous graduate students and published extensively on topics like blockchain security, malware detection, and medical data analysis. Education: Ph.D. Computer Science, University of Louisiana at Lafayette (2001) M.S. Computer Science, University of Louisiana at Lafayette (1997) B.S. Computer Information Systems, Loyola University New Orleans (1995) Research Interests: Advanced Pattern Mining, Graph Algorithms, Cyber-Security, and Health Informatics. Recent work includes detecting Ethereum blockchain attacks and developing AI-driven healthcare solutions. Key Contributions: Developed methods for detecting Android ransomware and cryptocurrency attacks Advanced anomaly detection in medical data and network traffic Contributed to containerized workload analysis and forensic data carving Grants & Teams: Active in the Data Science Ensemble at USA. Collaborates on projects like Data Predictive Maintenance and Big Data for Personalized Healthcare .

Stefan Lindskogمشاهده پروفایل

استاد

• Cybersecurity
• Network Security
• Intrusion Detection Systems
• +۷ مورد دیگر

Stefan Lindskog is a full Professor at the Department of Computer Science, Karlstad University, Sweden. His research focuses on tunable security services, network security protocols, intrusion detection systems, and encryption methodologies. He has held academic positions at Karlstad University since 1990 and holds a PhD in Computer Engineering from Chalmers University (2005) and a Docent degree in Computer Science from Karlstad University (2008). His work emphasizes practical cybersecurity solutions, including firewall usability, multipath TCP security, and privacy-preserving technologies. Lindskog has authored over 60 peer-reviewed publications, including studies on encrypted network traffic analysis, Tor anonymity vulnerabilities, and firewall rule optimization. He collaborates extensively with industry partners and academic networks, contributing to projects like the EU-funded NEWCOM++ initiative. Teaching: Real-Time Systems (7.5 ECTS) Key Research Themes: Security service tunability, adaptive intrusion detection, and secure communication protocols Collaborations: HITS project (High Quality Networked Services in a Mobile World) Publications span topics from malware detection in encrypted traffic to systematic reviews of firewall usability. Lindskog’s work bridges theoretical security models and operational system implementation, with a focus on real-world applicability in industries like offshore energy and mobile communications.

Adam A. Porterمشاهده پروفایل

استاد

• Software Engineering
• Mobile Application Development
• Software Testing and Quality Assurance
• +۳ مورد دیگر

Adam A. Porter is a Professor in the Department of Computer Science at the University of Maryland, affiliated with the University of Maryland Institute for Advanced Computing Studies (UMIACS). He holds a Ph.D. from the University of California at Irvine (1991). His research focuses on software engineering, mobile application development, and empirical studies of software processes. Notable contributions include work on metamorphic testing, software quality assurance, and educational initiatives like the first MOOC on Android development. Education: Ph.D., Computer Science, University of California at Irvine, 1991 Research Interests: Dr. Porter's work spans software testing (e.g., metamorphic testing), mobile application frameworks (Android), and empirical methods to improve software development practices. He emphasizes practical applications, such as improving static analysis tools and exploring human-AI collaboration in intelligence analysis. His research often bridges theory and practice, with contributions to tools like Skoll for distributed quality assurance. Publications: His recent work includes advancements in AI-driven materials modeling, software defect triaging, and metagenomic assembly algorithms. The articles reflect his interdisciplinary approach, combining machine learning with domain-specific challenges in materials science and bioinformatics. Awards: NSF Early Career Award (1995) Dean's Teaching Excellence Award (1995) Senior Member IEEE/ACM (2003/2006) Mobile Learning Fellow (2010) Grants/Advising: He has led projects funded by NSF and industry collaborations, focusing on software testing, mobile systems, and educational platforms. His mentoring includes community outreach programs for underrepresented students. Labs/Teams: Leads research efforts in software engineering methodologies and collaborates on initiatives like the ATAACK Android testbed for cloud-based emulation of mobile systems.

• Security
• Cybercrime
• Ethics
• +۳ مورد دیگر

Dr. Daniel Thomas is a Senior Lecturer in Computer and Information Sciences at the University of Strathclyde, where he serves as Director of the Academic Centre of Excellence in Cyber Security Research. His research focuses on the ethical measurement of security and cybercrime, aiming to improve regulatory frameworks and economic incentives. He holds a PhD from the University of Cambridge (2015) and an MA in Computer Science from the same institution (2011). Research Interests: Security metrics, cybercrime economics, infrastructure security, and ethical research practices. He collaborates across disciplines to address systemic issues in cybersecurity and policy. Key Projects: Principal Investigator for 'Influence policing' (2022–2025) and co-investigator on 'Robustness-as-Traceability: Secure and Legal Calibration Workflows in IoT' (2022–2023). His work contributes to UN Sustainable Development Goals related to education and security. Publications: Over 37 articles, including influential works on DDoS attack analysis, cybercrime infrastructure, and ethical AI. Recent focus areas include Russia-Ukraine cyber conflict dynamics and UK government use of targeted advertising. Prizes: CDCD Digital Research Prize (2024), Longlisted for Teaching Excellence Award (2024) Teaching: Courses on cybersecurity, ethics, and security engineering at Strathclyde and Cambridge Grants: EPSRC funding for cybercrime research, industry collaborations on IoT security Labs/Teams: Active in StrathCyber initiatives and collaborates with global networks like the Cambridge Cybercrime Centre. Supervises PhD students exploring topics such as security metrics and adversarial AI.

• Digital Anthropology
• Human-Robot Interaction
• Affect Theory
• +۷ مورد دیگر

Kristian Hoeck is a Postdoc at the Department of Anthropology, University of Copenhagen, under the Faculty of Social Sciences. He is actively engaged in research at the intersection of anthropology and artificial intelligence, with a particular focus on human-robot interaction and affective dimensions of humanoid robots. His research interests include: Digital Anthropology Human-Robot Interaction Affect Theory Science and Technology Studies (STS) Embodied Cognition Posthumanism His work critically examines how humanoid robots are socially and affectively calibrated in human environments, exploring the boundaries between human and machine, and questioning normative standards in AI embodiment. His recent publications, such as 'Android existence: The affect of artificial vitality' (2024) and 'Android Expression: The female form as problematic standard for embodied AI existence' (2022), reflect a consistent thematic trajectory centered on the phenomenology of artificial beings, gendered design in robotics, and the affective labor involved in human-robot coexistence. These works span ethnographic, philosophical, and technical domains, indicating interdisciplinary depth. Kristian Hoeck has not received any publicly listed scientific awards in the provided text. He has held external research positions, including as a Postdoc at SUMO, The National Museum of Denmark, and has participated in academic activities such as organizing the 16th EASA Biennial Conference (2020) and co-leading the workshop 'The Nonhuman that therefore I am (not)' (2020). There is no mention of student supervision or grant funding in the available information. He is affiliated with research teams exploring nonhuman agency and human-technology entanglements, particularly through collaborative projects with scholars like Morten A. Pedersen, Signe Gerd Kieffer-Døssing, and others in the Department of Anthropology.