Find Academic Supervisors

Lo’ay Abu SalahView profile

Clinical Professor

• wireless sensor networks
• network security
• computer networking
• +5 more

Lo’ay Abu Salah is a Clinical Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago (UIC), affiliated with the College of Engineering. His research focuses on wireless sensor networks, network security, computer networking, communications and signal processing, and interdisciplinary product development. He has contributed extensively to trust-aware routing protocols in mobile ad hoc networks and network security. PhD (2006), Electrical and Computer Engineering, University of Illinois at Chicago MSc (1999), Communication Engineering, University of Jordan BSc (1997), Electrical and Computer Engineering, Philadelphia University His work spans wireless network security, trust management, and simulation models, with a particular emphasis on adaptive protocols for dynamic environments. Recent publications analyze trust metrics, mobility impacts, and fuzzy logic applications in mobile ad hoc networks. He received the IDEAL Scholar award from the Institute for the Development of Excellence in Assessment Leadership in 2008. He is a member of IEEE since 1993 and served on technical program committees for network security symposia. He founded and directed the UIC Industry Training and Collaboration Center (ITCC) in 2009. His professional service includes technical program committee roles for IEEE and Globecom conferences.

Michael A. PalleyView profile

Professor

• Accounting Information Systems
• Management Information Systems
• IT and Organizational Strategy
• +5 more

Michael A. Palley is a Professor in the Paul H. Chook Department of Information Systems and Statistics at Zicklin School of Business, Baruch College (CUNY) . His expertise spans Accounting Information Systems , IT and Organizational Strategy , and Healthcare Information Systems . Education: PhD, MS, and MPhil in Information Systems from NYU Stern School of Business; BS in Finance & Multinational Enterprise from the Wharton School. His research focuses on information system security , statistical database confidentiality , and the intersection of IT with financial markets . He has contributed to journals such as Health Care Management Review and Journal of Official Statistics , with notable work on regression-based disclosure risks and IT diffusion in human services. Recent publications explore portfolio risk/return models for security and consequence frameworks for IT adoption . His work bridges theoretical rigor with practical applications, including user interface design and healthcare reimbursement systems . Scientific Awards: Zicklin Teaching Excellence Award (2001) Beta Gamma Sigma Honors (1986) IBM Fellowships (1983-1984) Invited Participant to ICIS Doctoral Consortium (1984) Paley has held leadership roles in academic governance, including Faculty Committee on Educational Technology and CUNY Baccalaureate Program Mentor . He has also served as a consultant for organizations like Citigroup and IBM.

Elena SitnikovaView profile

Associate Professor

• Critical Infrastructure Protection
• Cyber-Physical Systems (CPS)
• Intrusion Detection Systems (IDS)
• +3 more

Elena Sitnikova is an Associate Professor of Cybersecurity and Networking at Flinders University's College of Science and Engineering . As a Certified Secure Software Lifecycle Professional , she leads cutting-edge research in Critical Infrastructure protection, focusing on intrusion detection for SCADA systems and Industrial Internet of Things (IIoT). Her work explores system antifragility and AI-driven analysis of abnormal data in cyber-physical systems. Education : PhD in Computer Technology (Mathematical Modelling of Space Communication Systems), Bachelor of Electrical Engineering with Honours. Elena's research spans Cyber-Physical Systems Security , Critical Infrastructure Protection , and SCADA Systems Cybersecurity , with a focus on intrusion detection, antifragility, and AI applications. Her recent work includes datasets for IIoT intrusion detection and frameworks for cyberworthiness assessments. She has received numerous awards , including the Women in AI Cybersecurity Award , Senior Fellowship of the Higher Education Academy , and Australian Office for Learning and Teaching Citation award . Elena has secured over AU$1.5 million in research grants and supervised six PhD completions . Leadership : Academic Lead of the Australian Affiliate of Women in Cyber Security (WiCyS), Associate Editor for the Australian Journal of Multidisciplinary Engineering, and Chair/Editor for international conferences/journals. Teaching : Innovates in online cybersecurity education and research-led teaching, pioneering student engagement strategies.

J. Drew ProcaccinoView profile

Associate Professor

• Biometrics
• Smart-card Technology
• Information-seeking Behavior
• +2 more

J. Drew Procaccino serves as an Associate Professor in the Department of Information Systems, Analytics and Supply Chain Management at Rider University, with his office located in Sweigart Hall. His academic focus centers on practical applications of information systems in security and data management. Dr. Procaccino's educational foundation includes advanced degrees spanning software engineering and business administration: Ph.D. in Software Engineering from Drexel University (2003) M.B.A. in Business Administration from Rider University (1999) B.S. in Decision Sciences & Computers from Rider College (1991) B.A. in Economics and Business Administration from Ursinus College (1982) His research explores biometrics, smart-card technology, information-seeking behavior, software project management, and identity theft, with particular emphasis on real-world security vulnerabilities and protective strategies. This focus manifests in practical guidance for professionals and victims alike, bridging theoretical frameworks with actionable solutions in information security. Publications from 2016 demonstrate concentrated exploration of identity theft case studies, international financial comparisons across NAFTA and Latin American manufacturing sectors, and text-mining applications for competitive analysis of online reviews. Earlier works (2010) establish foundational research in identity theft protection protocols and examine social dynamics in e-commerce adoption, revealing consistent thematic threads in information security, behavioral analysis, and data-driven decision making across his scholarly output.

• Computer Graphics
• Human-Computer Interaction
• Game Design
• +6 more

Rui Rodrigues is an Associate Professor at the Department of Informatics Engineering within the Faculty of Engineering of the University of Porto (FEUP) . He joined FEUP in 2009 as an Invited Assistant Professor, transitioned to full-time Assistant Professor, and was promoted to Associate Professor in 2023. He also serves as a senior researcher at INESC TEC . Research Interests His research focuses on Computer Graphics , Human-Computer Interaction , and Game Design , with additional expertise in Machine Learning , Cybersecurity , and Energy Systems . His work explores trust models, IoT security, and adaptive energy management. Projects and Leadership He co-leads the GIG group at DEI/FEUP and its labs. As a senior researcher at INESC TEC, he contributes to diverse R&D initiatives. He directed the Multimedia Masters program (2015-2019) and currently directs the Masters in Informatics Engineering and Computing (M.EIC) since May 2023.

Bogdan VasilescuView profile

Associate Professor

• Software Engineering
• Malware Analysis and Detection
• Measurement and Analysis
• +3 more

Bogdan Vasilescu serves as an Associate Professor in Carnegie Mellon University's School of Computer Science within the Software and Societal Systems Department. He leads the Socio-Technical Research Using Data Excavation Lab (STRUDEL) and maintains active involvement in the software engineering research community through program committees and editorial roles. His academic credentials include: Ph.D. in Computer Science (cum laude) from Eindhoven University of Technology (2014), supervised by Alexander Serebrenik and Mark van den Brand Master's degree in Computer Science and Engineering from Eindhoven University of Technology (thesis advisor: Alexander Serebrenik) Engineer's degree in Systems and Computer Science from University of Ploieşti, Romania (thesis advisor: Gabriel Rădulescu) Research focuses on software engineering with specialized expertise in malware analysis , fraud measurement , and socio-technical system analysis . His work combines data excavation techniques to study human behavior in software development and security contexts, particularly examining spam, malware, and collaborative development patterns. This interdisciplinary approach bridges computer science with societal impact assessment. Recognition includes: Best Dissertation Award from the Institute for Programming Research and Algorithmics Distinguished Reviewer Award at ASE 2018 Distinguished Reviewer Award at ESEC/FSE 2021 Vasilescu advises graduate students in CMU's Software Engineering and Societal Computing programs while directing the Research Experiences for Undergraduates in Software Engineering (REUSE) initiative. This NSF-funded program supports undergraduate research, particularly for U.S. citizens/permanent residents, with past participants publishing papers and winning awards. His STRUDEL lab emphasizes interdisciplinary collaboration and real-world impact. The STRUDEL lab operates within CMU's School of Computer Science, conducting data-driven research on socio-technical aspects of software development. Current projects examine security vulnerabilities, collaborative patterns in open-source communities, and measurement methodologies for malicious software ecosystems.

• Social Epidemiology
• Neighborhood Effects on Health
• Statistical Methods for Spatial Data
• +3 more

Odile Sauzet is an Adjunct Professor at Universität Bielefeld , affiliated with the Faculty of Health Sciences and the Working Group 3 Epidemiology & International Public Health . She also holds positions in the Faculty of Economics (Chair of Statistics and Data Analysis) and the Faculty of Business Administration and Economics (Department of Empirical Methods).

• Information Security
• Software Vulnerability Analysis
• Digital Forensics
• +3 more

Hanno Langweg serves as Associate Professor in the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), based at the Gjøvik campus. His academic activities are deeply integrated with the COINS Research School of Computer and Information Security, a national consortium led by NTNU that unites Norway's major universities in cybersecurity research and doctoral training. Langweg's research centers on practical security vulnerabilities and compliance frameworks. His work extensively analyzes difficult-to-detect code patterns for SQL injection and cross-site scripting, develops forensic readiness methodologies, and bridges legal requirements like GDPR with technical security implementations. Recent publications demonstrate consistent focus on automated vulnerability injection, stakeholder-driven security requirements, and forensic evidence collection systems. His publication trends reveal sustained contributions across three interconnected domains: vulnerability pattern analysis (particularly in PHP and browser contexts), forensic readiness tooling (including kernel tracing and event reconstruction), and regulatory compliance engineering (GDPR, Common Criteria). This triad reflects both technical depth in code-level security and strategic understanding of legal-technical intersections. Langweg actively contributes to the academic community through conference organization (Sicherheit series) and teaching courses including Software Security (IIKG2001) and Information Security Summer School (IMT6003). His collaborations span multiple institutions with frequent co-authorship patterns involving Schuckert, Katt, and Liao. Within the COINS Research School framework, Langweg supports Norway's cybersecurity research ecosystem that now exceeds 100 doctoral students. His work directly enables the school's mission of integrating national research groups, enhancing student mobility, and establishing international recognition in information security.

Wenchao GuView profile

Research Fellow

• Artificial Intelligence
• Software Engineering
• Computational Linguistics
• +5 more

Dr. Wenchao GU is a Postdoctoral Researcher at the Chair of Software Engineering & AI at the Technical University of Munich (TUM) , working under the supervision of Prof. Chunyang Chen. His academic journey includes a PhD in Computer Science and Engineering from The Chinese University of Hong Kong (CUHK) (2024), an MSc in Information Science from Tohoku University (2017), and a B.Eng in Mechanical and Aerospace Engineering from Tohoku University (2015). Research Interests: Dr. GU's work focuses on Artificial Intelligence for Software Engineering (AI4SE) , leveraging Large Language Models (LLMs) to advance source code understanding, analysis, and generation. Key areas include code optimization , vulnerability detection , and UI code generation . His research bridges theoretical innovations with practical tools for automated code efficiency improvement, semantic code retrieval, and natural language generation in software development workflows. Publication Trends : His recent work emphasizes iterative LLM refinement via evolutionary search (2025), segmented deep hashing for scalable code retrieval (2025), and contrastive learning in code search (2023). Earlier studies explored AST-guided transformers for code summarization (2022) and semantic dependency learning in code retrieval (2021). Scientific Awards: Distinguished Paper Award, ICSE 2025 The Aoba Foundation Scholarship (2015) JASSO Scholarship (2012) Tohoku University President Fellowship (2012) Mentorship: Dr. GU supervises 11 current students (including 1 PhD) and has advised 5 graduated Master's students. He actively seeks candidates with web/Android development expertise for UI code generation projects.

Yuetian MaoView profile

Researcher

• Intelligent Software Engineering
• Query Refinement
• Code Search
• +3 more

Yuetian Mao is a Doctoral Candidate and Research Associate at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology (CIT). He holds a Master's degree in Software Engineering from Shanghai Jiao Tong University (2020-2023) and a Bachelor's degree in the same field from the same institution (2016-2020). His research focuses on Intelligent Software Engineering and Query Refinement , particularly in the application of large language models (LLMs) to code search and optimization tasks. His work addresses challenges in Code Vulnerability Detection , GUI Testing Simulation , and LLM-based Tool Use for software development. Recent publications analyzed include topics in Code Search , Query Reformulation , HiveQL Anti-patterns , and LLM-enhanced Software Engineering . His research also intersects with Human-Centric AI , Accessibility Testing , and Automated GUI Repair . Scientific Awards : Hypergryph Scholarship (2021.11) The First Prize Graduate Study Scholarship (2020.9, 2021.9, 2022.9) Yuetian is part of the Chair of Software Engineering & AI at TUM's Heilbronn campus, contributing to projects in Model Context Protocols , Generative Engine Optimization , and EU AI Act Compliance research.

• Blockchain Technology
• Smart Contract Security
• Renewable Energy Systems
• +3 more

Sundas Munir is a Lecturer at the School of Information Technology, Halmstad University. Her research focuses on blockchain technology, smart contract security, and renewable energy systems. University: Halmstad University School: School of Information Technology Rank: Lecturer Email: sundas.munir@hh.se Her recent publications highlight expertise in: Static analysis of smart contracts Transaction ordering dependencies in Ethereum Blockchain-based energy marketplaces Security validation frameworks Formal verification techniques Her work bridges theoretical research with practical applications in decentralized systems and cybersecurity. She is active in publishing conference papers and technical surveys related to blockchain integrity and energy innovation.

Andrii ShalaginovView profile

Professor

• Internet of things (IoT)
• Machine learning
• Smart cities
• +4 more

Andrii Shalaginov is a Professor in Cyber Security at Kristiania University of Applied Sciences, School of Economics, Innovation and Technology. He leads the Smart Security Lab with a research focus on applying artificial intelligence for cybersecurity, detection of computer viruses, network attacks and protection of Internet of Things devices. Dr. Shalaginov holds a PhD in Information Security from the Norwegian University of Science and Technology (NTNU), where he worked with digital forensics at the Center for Cyber and Information Security (CCIS). His research spans multiple critical areas of modern cybersecurity with a particular emphasis on Internet of Things security , machine learning applications for threat detection, and digital forensics . He has developed expertise in intelligent malware detection systems, network security for smart environments, and forensic analysis of IoT devices. His work bridges theoretical computer science with practical security implementations for real-world systems. Analysis of his recent publication trends (2022-2025) reveals a strong focus on AI-enabled security solutions for IoT ecosystems, vulnerability detection frameworks, and resource-efficient security mechanisms for constrained devices. His research increasingly addresses the intersection of machine learning and practical security implementations, with growing attention to energy efficiency in security protocols and international data space security frameworks. Dr. Shalaginov has received professional recognition through: Nomination as Norwegian representative in EU COST Action CA17124 "DigForAsp" Nomination as Norwegian representative in EU COST Action CA22104 "BEiNG-WISE" Membership in the "Impact of Technology" Expert Group at the European Union Intellectual Property Office Observatory As head of the Smart Security Lab, Dr. Shalaginov oversees research projects focused on developing practical security solutions for emerging technologies. His GitHub activity demonstrates active development of open-source tools for malware analysis across multiple platforms (Linux, Windows, IoT) and implementation of machine learning approaches for security applications. His research group appears to focus on bridging the gap between theoretical security models and practical implementations for real-world systems.

Tianxing HeView profile

Assistant Professor

• AI Safety
• AI-driven Simulation
• Large Language Models
• +5 more

Tianxing He is an Assistant Professor at Tsinghua University's Institute for Interdisciplinary Information Sciences (IIIS), also known as the Yao Class, which he joined in September 2024. He also works part-time at Shanghai Qi Zhi Institute where he recruits for research-oriented positions and video game development roles. His academic journey includes a postdoc at the University of Washington under Yulia Tsvetkov, a PhD at MIT supervised by James Glass, and bachelor's and master's degrees at Shanghai Jiao Tong University in the ACM honored class under Prof. Kai Yu. Dr. He's research spans AI safety and AI-driven simulation with particular focus on large language models. His work examines LLM capabilities in cryptography (AICrypto benchmark), security vulnerabilities (jailbreaking techniques), multi-agent system integrity, and socially impactful applications like vaccine hesitancy simulation (VACSIM framework). He has developed visualization tools like MiniAgents-Pro using Unity for generative agent simulation and created watermarking techniques such as SemStamp and k-SemStamp for detecting machine-generated text. His publication record shows consistent contributions to top-tier conferences including ACL, EMNLP, NeurIPS, and ICLR, with recent work focusing on evaluating LLM capabilities across diverse domains. The research demonstrates sophisticated understanding of both the technical aspects of language models and their broader societal implications, particularly in security and ethical considerations. Scientific Awards: The Best Paper Award at the Efficient Natural Language and Speech Processing Workshop (NeurIPS ENLSP 2022) for "PCFG-based Natural Language Interface Improves Generalization for Controlled Text Generation" Dr. He actively mentors students and recruits research interns, PhD candidates, and post-bachelor researchers. He plans to teach an undergraduate NLP course in Fall 2025 and organizes the IIIS AI Safety Lunch, a monthly gathering in Beijing for those working on AI safety. His recruitment efforts target students interested in LLM social simulation, AI+game development, and AI safety research, emphasizing the need for strong self-motivation and research passion. He leads research initiatives including the IIIS AI Safety Lunch series and has developed multiple visualization and simulation frameworks. His work sits at the intersection of AI safety, language modeling, and practical applications, with team collaborations spanning multiple institutions including MIT, University of Washington, and Shanghai Jiao Tong University.

Amin KaramiView profile

Associate Professor

• Artificial Intelligence and Data Science
• Big Data Technologies
• Blockchain and Cryptocurrencies
• +4 more

Dr Amin Karami is an Associate Professor in the School of Computer Science and Digital Technologies (CDT) at the University of East London, within the School of Architecture, Computing and Engineering. He serves as course leader for MSc Big Data Technologies and leads postgraduate programs, having secured £1.23 million in funding from the Office for Students to develop inclusive AI and Data Science courses for non-STEM and far-STEM graduates. His research spans Artificial Intelligence, Big Data Analytics, Blockchain, and Optimization, with focus on Industry 5.0 applications. Current work addresses federated learning heterogeneity, smart contract security, healthcare fraud detection, and ethical AI implementation. He develops cloud-based platforms for large-scale data processing and computational intelligence solutions for real-world industry challenges. Recent publications demonstrate strong trends in federated learning techniques, blockchain vulnerability mitigation, and big data applications across healthcare, finance, and social media. His work consistently bridges academic research with industry needs through partnerships with Multiverse and Cambridge Spark, emphasizing practical solutions for credit risk assessment, satellite telemetry, and personalized marketing. Scientific recognition includes: UEL Vice-Chancellor & President Impact & Innovation Award for Industry 4.0 readiness (2023) Fellow of the Higher Education Academy (FHEA) Dr Karami actively supervises UG/PG/PhD students while leading curriculum innovation through externally funded projects. His Chainlink Bootcamp initiative connects academia with industry practitioners, and he serves as external examiner and conference program chair. Significant grant achievements include developing diversity-focused STEM pathways that enhance graduate employability through industry-aligned training in AI and Data Science.

Umar Mukhtar IsmailView profile

Senior Lecturer

• Cyber Threat Intelligence
• Security and Privacy Requirement Engineering
• AI-enabled Cyber Security
• +9 more

Dr. Umar Mukhtar Ismail serves as a Senior Lecturer in the Department of Computer Science and Digital Technologies at the University of East London's School of Architecture, Computing and Engineering. He leads the BSc (Hons) Cyber Security Networks and BSc (Hons) Cloud Computing programmes while teaching core modules including Cyber Security, Security Management, and Advanced Topics in Cyber Security. His research spans critical cybersecurity domains including AI-enabled threat intelligence, security requirement engineering, incident response frameworks, and cloud security management. He specializes in developing security solutions for critical infrastructure, healthcare systems, and supply chains using standards like ISO27001 and NIST frameworks, with particular focus on cyber resilience and threat modeling methodologies. Analysis of his 12 recent publications reveals consistent emphasis on creating structured security frameworks for cloud transparency, incident handling, and supply chain protection. His work increasingly integrates machine learning for malware detection and vulnerability prediction, demonstrating evolving expertise in adversarial AI analysis and ontology-based threat representation across healthcare and critical infrastructure contexts. Scientific recognition includes: Fellow of the Higher Education Academy Dr. Ismail actively contributes to European Union-funded research projects enhancing security in cyber-physical systems and healthcare infrastructure. He currently supervises MSc dissertations and PhD candidates while developing novel approaches to security transparency and audit frameworks, maintaining active collaborations through IEEE, BCS, and ISACA memberships.