جست‌وجوی استاد و پژوهشگر

Xiangyu Zhangمشاهده پروفایل

استاد

• AI Security
• Software Engineering
• Programming Languages and Compilers
• +۵ مورد دیگر

Xiangyu Zhang is the Samuel D. Conte Professor of Computer Science at Purdue University. He specializes in AI security, software analysis, and cyber forensics, with a focus on detecting vulnerabilities in traditional software and AI systems. His research includes dynamic slicing, program profiling, and securing AI models against backdoors. He has led projects funded by DARPA, IARPA, NSF, and industry, securing over $13 million in grants. He has mentored 30+ PhD students and postdocs, many of whom hold academic positions or industry roles. His work has been recognized with awards like the ACM SIGPLAN Distinguished Dissertation Award and NSF Career Award. Education: PhD, Computer Science, University of Arizona (2006) MS & BS, Computer Science, University of Science and Technology of China (2000 & 1998) Research Interests: AI Security: backdoor detection, adversarial attacks, model integrity Program Analysis: dynamic slicing, static/dynamic debugging Cyber Forensics: log analysis, attack investigation Software Reliability: fault localization, vulnerability detection Key Projects: DARPA V-SPELLS: domain-specific program analysis IARPA TrojAI: AI backdoor detection competitions NSF-funded research on model debugging and co-reasoning of software/NL artifacts Awards & Recognition: Top performer in IARPA TrojAI competitions (13/18 rounds) ACM SIGPLAN Distinguished Dissertation Award (2006) NSF Career Award (2009) Ranked 8th globally in systems research productivity (2024) Career Contributions: Secured over $13M in research funding Guided 25 PhDs and 8 postdocs Published 89+ top-tier papers (2014–2024)

• Cybersecurity
• Maritime Sector
• Human Error Probability
• +۳ مورد دیگر

Gizem Kayişoğlu is an Assistant Professor in the Department of Maritime Transportation and Management Engineering at Istanbul Technical University. Her research focuses on cybersecurity challenges in maritime systems, human error probability, and risk assessment methodologies. She actively explores vulnerabilities in shipboard systems such as ECDIS, VDR, and radar while emphasizing regulatory compliance and maritime safety standards. Her work integrates frameworks like CORAS, Fuzzy FUCOM, and SLIM to address cybersecurity dynamics and human factors in maritime operations. Key collaborations involve analyzing ransomware threats, AIS system vulnerabilities, and port infrastructure protection through interdisciplinary approaches. Her articles highlight trends in maritime cybersecurity, including ransomware mitigation, cyber hygiene practices, and critical infrastructure protection. She has contributed to developing risk assessment tools and checklists tailored for maritime environments, emphasizing both technological and human aspects of safety. No scientific awards have been explicitly mentioned. She has not listed formal advisees, and her professional activities focus on advancing maritime cybersecurity through academic and applied research.

Ping Yangمشاهده پروفایل

استاد

• Cybersecurity
• Information Security
• AI-Based Security
• +۷ مورد دیگر

Ping Yang is a Professor and Associate Director for Research and Graduate Programs in the School of Computing at Binghamton University (SUNY). She holds a Ph.D. in Computer Science from Stony Brook University, an ME from the Chinese Academy of Sciences, and a BS from Zhongshan University. Her research focuses on cybersecurity, AI-based security, virtual machine security, privacy policy analysis, and formal methods. She directs the Center for Information Assurance and Cybersecurity and coordinates cybersecurity programs at both undergraduate and graduate levels. Education: BS in Computer Science, Zhongshan University ME in Computer Science, Chinese Academy of Sciences MS and PhD in Computer Science, State University of New York at Stony Brook Research Interests: Dr. Yang's work spans information and systems security, security in virtualized computing, access control mechanisms, privacy policies, and formal methods for security verification. Her projects include blockchain-based provenance storage, real-time anomaly detection in workflows, and privacy-preserving virtual machine migration. She has led NSF-funded initiatives on security in cloud environments and scientific workflows. Awards: Not explicitly listed in the provided materials. Advising & Grants: Advised over 30 PhD/Master’s students and contributed to grants including NSF Scholarship for Service and GenCyber programs. Her team develops tools like RBAC-PAT for access control analysis. Labs/Teams: Leads the Center for Information Assurance and Cybersecurity and collaborates on projects involving secure data workflows and blockchain applications in scientific research.

Gunes Acarمشاهده پروفایل

استادیار

• Web Security
• Privacy
• Online Tracking
• +۳ مورد دیگر

Güneş Acar is a tenured Assistant Professor in the Digital Security group at Radboud University's Faculty of Science. He is also affiliated with iHub, Radboud's interdisciplinary research hub on digitalization and society. His research focuses on security and privacy threats from websites, mobile apps, and IoT devices, with special emphasis on online tracking mechanisms, anonymous communication networks like Tor, and deceptive design patterns. Dr. Acar completed his PhD at KU Leuven under the supervision of Claudia Diaz and Bart Preneel. Prior to joining Radboud University, he was a Postdoctoral Research Fellow at KU Leuven's COSIC group and a Postdoctoral Research Associate at Princeton University's Center for Information Technology Policy. His research spans web security, privacy, online tracking, IoT security, Tor network analysis, and dark patterns. He investigates how websites, mobile apps, and IoT devices compromise user privacy through various tracking mechanisms and deceptive interface designs. His work combines large-scale measurements with user studies to understand both technical vulnerabilities and their real-world impact on users. Dr. Acar's publications reveal an evolving research trajectory from foundational web tracking mechanisms to increasingly sophisticated privacy threats. His work has expanded from browser fingerprinting to IoT privacy, children's online safety, and manipulative design patterns in subscription interfaces. A consistent theme across his research is the examination of how third-party trackers operate and circumvent privacy protections. 2022 CNIL-Inria Award for Privacy Protection (for Leaky Forms paper) Top Reviewer Award, Privacy Enhancing Technologies Symposium (2022) Future of Privacy Forum's Annual Privacy Papers for Policymakers Award (2020) Runner-up for multiple Caspar Bowden Awards for Outstanding Research in Privacy Enhancing Technologies Dutch Research Council (NWO) Vidi Grant (2025-2030) for "A Web Security and Privacy Observatory" Dr. Acar actively supervises PhD students including Zahra Moti, Tim Vlummens, and Luqman Zagi, with Asuman Senol recently completing her PhD in 2024. He has secured significant research funding including the NWO Vidi Grant and a project grant from armasuisse for the Mobile Web Inspector project. His research has influenced policy discussions with organizations including the OECD, US Federal Trade Commission, and European consumer protection authorities. As part of the Digital Security group at Radboud University, Dr. Acar contributes to a vibrant research ecosystem focused on practical security and privacy solutions. His work bridges technical security research with human-centered perspectives, often collaborating across disciplines to address complex privacy challenges in real-world contexts.

• Cybersecurity
• Blockchain
• Machine Learning
• +۱۲ مورد دیگر

Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications

• Business Process Management
• Process Mining
• Complex Event Processing
• +۵ مورد دیگر

Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data

• Cybersecurity
• Cyber-Physical Systems
• Industrial Control Systems
• +۴ مورد دیگر

Andreas Ekelhart is a Researcher at TU Wien's Department of Information and Software Engineering. His work focuses on cybersecurity, cyber-physical systems, and industrial control systems. He specializes in developing frameworks like SLOGERT for automated log analysis and Kyrstal for attack discovery using knowledge graphs. His research also explores digital twin technology for threat detection and semantic web applications in machine learning systems. Key contributions include the VloGraph framework for distributed security log analysis and the QualSec approach for automated security risk identification in production systems. He collaborates on standards like AutomationML and emphasizes privacy-preserving data analysis through semantic architectures.

Ferreira Joao Carlosمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Energy and Transportation
• +۶ مورد دیگر

Joao Carlos Amaro Ferreira is a Professor at the Faculty of Logistics, Molde University College (HiMolde), Norway. He holds PhDs in Computer Engineering and Industrial Engineering from the Technical University of Lisbon and the University of Minho, respectively. His research focuses on Artificial Intelligence (AI) applications in healthcare, energy, transportation, IoT, blockchain, and smart cities. He has led over 40 projects, including 6 as Principal Investigator, and contributed to international conferences like OAIR and INTSYS. He served as IEEE CIS President (2016-2018) and is an IEEE Senior Member since 2015. His academic contributions span AI-driven solutions for public sector informatics, healthcare data quality, and cybersecurity. He actively participates in European projects such as e-Hospital4Future and explores blockchain applications in supply chains and medical records. Ferreira leads the ABC-AI research group, emphasizing ethical and applied AI. His work bridges academia and industry through projects like gamification systems for eco-driving and AI in fisheries traceability. Recent publications highlight AI's role in cardiovascular disease detection, emergency department optimization, and blockchain-enhanced healthcare interoperability. He collaborates internationally, co-editing journals like Applied Sciences , and has authored patents in edge computing for maritime monitoring.

Nate Apathyمشاهده پروفایل

استادیار

• Health Policy
• Health Services Research
• Health Informatics
• +۳ مورد دیگر

Nate Apathy is an Assistant Professor of Health Policy & Management at the University of Maryland School of Public Health and an Affiliated Research Scientist at the Regenstrief Institute. He holds a PhD in Health Policy & Management from Indiana University (2020) and completed a postdoctoral fellowship in health services research at the University of Pennsylvania (2022). His research focuses on health information technology's role in healthcare delivery reform, regulatory impacts on health IT innovation, and the use of EHR metadata to assess care quality. He examines organizational strategies to reduce IT-based burdens, particularly in primary care and specialty settings. His work bridges health policy, services research, and informatics, with emphasis on EHR documentation dynamics, clinician workflows, and interoperability challenges. Notable studies include analyses of physician EHR time allocation, telemedicine integration, and the impact of team-based documentation tools. He has contributed to national discussions on electronic health record legal settlements, opioid prescribing guidelines, and nursing home post-acute care specialization. Nate’s research has been published in journals such as Health Affairs , Annals of Internal Medicine , and Journal of the American Medical Informatics Association . He collaborates with institutions like the Leonard Davis Institute of Health Economics and focuses on translating informatics insights into actionable policy recommendations.

Wajih Ul Hassanمشاهده پروفایل

استادیار

• Cybersecurity
• System Intrusion Detection
• Data Provenance Techniques
• +۴ مورد دیگر

Wajih Ul Hassan is an Assistant Professor of Computer Science at the University of Virginia (UVA), affiliated with the School of Data Science. He leads the DART Lab, focusing on system intrusion detection, forensic investigation, and cybersecurity through machine learning and data provenance techniques. His research has earned prestigious awards including the NSF CAREER Award (2024) and Symantec Research Labs Graduate Fellowship. Dr. Hassan holds a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign (2021). He has collaborated with NEC Labs and Symantec Research Labs to integrate defensive strategies into commercial security products. His work emphasizes practical solutions for networked systems and scalable security mechanisms. He teaches courses such as CS 6501: Machine Learning in Systems Security, CS 4630: Defense Against the Dark Arts, and DS 6559: Machine Learning in Systems and Network Security. His research interests span intrusion detection, provenance analytics, and automated threat response, with over 20 peer-reviewed publications since 2017. Award Highlights: NSF CAREER Award (2024) ACM SIGSOFT Distinguished Paper Award Young Researcher at Heidelberg Laureate Forum Service Activities: He has served on program committees for top-tier conferences (e.g., IEEE S&P, ACM CCS) since 2018 and reviewed grants for the NSF and Commonwealth Cyber Initiative. Labs & Teams: The DART Lab at UVA focuses on advancing enterprise security through data-driven approaches. Dr. Hassan actively recruits students for research projects in cybersecurity and systems security.

• Digital Trust
• Cybersecurity
• Blockchain
• +۱۲ مورد دیگر

Dr. Felix Härer is a Lecturer and researcher at the University of Applied Sciences FHNW, School of Business, Basel, Switzerland, and also teaches externally at the University of Fribourg. He is affiliated with the Digital Trust Competence Center, where he conducts research and teaching in IT Security, Cybersecurity, Digital Trust, Blockchain, AI, Cloud Computing, and Systems Modeling. His research interests span a broad and interdisciplinary range, including: Digital Trust and Cybersecurity Blockchain and Decentralized Systems AI and Knowledge-based Systems (including LLMs and RAG) Software and Systems Modeling (BPMN, ArchiMate) Data Science and ETL-based Analytics Zero Trust and Secure Architectures His recent publications (2020–2023) demonstrate a strong focus on blockchain interoperability, model-driven engineering, decentralized applications, and the integration of AI with conceptual modeling. He explores scalable architectures, cross-chain query languages, and secure attestation mechanisms, often combining modeling approaches with emerging technologies. His work bridges academic rigor with practical implementation in distributed and cloud environments. Scientific awards include: Best Paper Award at IEEE PKIA 2023 He actively supervises bachelor’s and master’s theses and student projects in digital trust and related domains. He has served on PhD committees externally and is a reviewer and program committee member for journals and conferences such as IEEE Transactions, WWW, CAiSE, and EMISAJ. His professional experience includes industry work at Siemens Healthineers in software engineering. He is a member of the IEEE Blockchain Group (Switzerland) and contributes to UN/CEFACT standards for e-commerce and supply chain data. He is involved in organizing workshops and conferences, including B4ISE 2025, B4TDS 2023–2024, and DESRIST 2023, and has delivered keynotes on Computational Trust and Blockchain Interoperability.

• Cyber-physical system security
• Threat modelling
• Critical infrastructure resilience
• +۳ مورد دیگر

Dr. Carmen Cheh is a Research Scientist in the Department of Computer Science at the University of Illinois at Urbana-Champaign. She holds a Ph.D. in Computer Science from UIUC and a Bachelor of Computing (Hons) from the National University of Singapore. Her research focuses on cyber-physical system security, threat modeling, and critical infrastructure resilience. She has served as Co-Principal Investigator on two major grants: the 2023-2024 project on threat modeling for government systems and the 2022-2025 initiative on real-time fraud detection in e-commerce platforms. Her work bridges theoretical computer security with practical applications in critical infrastructure protection. Dr. Cheh has contributed to tools like CyberSAGE, which aids in automated security argument evaluation, and frameworks for detecting business logic flaws in software systems. She collaborates extensively with industry and government entities to advance cybersecurity practices in both digital and physical domains. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign Bachelor of Computing (Hons), National University of Singapore Her research interests emphasize real-world security challenges in interconnected systems, including automated threat modeling, vulnerability discovery in business logic, and compliance frameworks for financial services. She has pioneered constraint-based methodologies for identifying security flaws in complex systems and developed novel approaches to insider threat detection using physical access data. Recent work explores the intersection of machine learning and cybersecurity in fraud detection systems. Her publications span top venues like ACM Transactions on Modeling and Computer Simulation, IEEE Secure Development Conference, and the IEEE International Conference on Computer Communications. Collaborations include projects with institutions like Argonne National Laboratory and the National Science Foundation.

Andrea Morichettaمشاهده پروفایل

دانشیار

• Blockchain Technology
• Smart Contracts
• Business Process Management
• +۴ مورد دیگر

Andrea Morichetta is an Associate Professor at the University of Camerino (UNICAM). His research focuses on blockchain technology, smart contracts, and business process management. He explores the integration of blockchain with choreography-based systems, model-driven engineering, and process mining. His work addresses challenges in smart contract testing, distributed systems coordination, and auditability in decentralized applications. Key research areas include: Blockchain-based execution frameworks for BPMN choreographies Mutation testing strategies for Solidity smart contracts Decentralized identity systems using blockchain Event log analysis for Ethereum applications His publications highlight advancements in: Smart contract security and testing methodologies Choreography-driven architectures for IoT and MLOps Formal analysis of business process collaborations He contributes to international conferences and workshops on blockchain, enterprise modeling, and business informatics research. His work bridges theoretical foundations with practical implementations in distributed systems and process automation.

Kevin W. Hamlenمشاهده پروفایل

استاد

• Cybersecurity
• Software Security
• Formal Methods
• +۶ مورد دیگر

Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.

Kanika Goelمشاهده پروفایل

مدرس

• Process-Oriented Data Analytics
• Data Governance
• Data Quality
• +۳ مورد دیگر

Dr. Kanika Goel is a Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in Business Process Management (BPM), Data Governance, and Process Analytics. She holds a PhD from QUT and has over 9 years of teaching experience, coordinating programs such as BIT Honours (IN10) and Masters of Philosophy (IN80). Her research focuses on process-oriented data analytics, data quality, and process mining, with industry collaborations spanning health, retail, and asset management sectors. She is a Lean Six Sigma Green Belt certified trainer and a Fellow of the Higher Education Academy (FHEA). Dr. Goel has led several industry-funded projects, emphasizing applied research in data governance, process mining, and process improvement. Notably, she received the Vice-Chancellor's Award for Excellence (2019) for innovative BPM integration in research management systems. Her work bridges academic research and real-world applications, contributing to journals like Business and Information Systems Engineering and IEEE Access . She teaches courses on Business Process Technologies, Modern Data Management, and BPM units in QUT's continuing professional education programs. Her articles explore topics like data imperfections in healthcare systems, process standardization strategies, and privacy risks in NoSQL databases. She advocates for digital literacy and has published on initiatives to build tech-savvy communities. Dr. Goel is also involved in supervising research topics such as prescriptive process analytics and process-data governance patterns.