Find Academic Supervisors

Marc Steffen RappView profile

Professor

• Corporate Governance
• Finance
• Accounting
• +2 more

Marc Steffen Rapp serves as a Professor in the Department of Accounting at Copenhagen Business School (CBS), where he maintains a strong affiliation with the Center for Corporate Governance. His academic profile bridges accounting, finance, and governance structures through rigorous empirical research. His research interests span several critical domains: Corporate Governance frameworks, particularly the German Corporate Governance Code and its implementation Financial market dynamics including stock migrations, delisting behavior, and market efficiency Board-level employee representation and its impact on organizational crisis management Machine learning applications in fundamental financial analysis and mispricing detection Societal implications of financial sector growth and labor market outcomes Analysis of his publication record from 2018-2023 reveals a methodologically evolving trajectory. Initial work focused on traditional governance topics using German institutional data, while recent studies increasingly integrate computational techniques and address macro-level questions about finance's societal role. This progression demonstrates both technical innovation and expanding conceptual scope across European financial contexts. No scientific awards are documented in the current source material. While specific advising details remain undisclosed, his active publication record with multiple co-authors suggests significant mentorship of junior researchers and doctoral candidates within CBS's academic ecosystem. His primary research infrastructure operates through CBS's Center for Corporate Governance, which facilitates interdisciplinary collaboration on governance standards, regulatory compliance, and stakeholder communication practices.

• Human Factors in Security and Privacy Research
• Empirical Software Engineering
• Software Supply Chain Security
• +3 more

Prof. Dr. Yasemin Acar serves as a Professor in the Department of Computer Science within the Faculty of Computer Science, Electrical Engineering and Mathematics at Paderborn University. She leads research in the Empirical Software Engineering group, focusing on human-centered security and privacy challenges. Her work bridges theoretical security concepts with practical implementation in real-world software systems. Dr. Acar's research interests center on understanding the human factors that influence security and privacy in software development. She investigates how developers interact with security mechanisms, how privacy policies are communicated across professional boundaries, and how cryptographic research translates to practical applications. Her work particularly addresses the growing challenges in software supply chain security and the trust relationships within open-source ecosystems. Through empirical methods including interviews, surveys, and mixed-methods studies, she identifies communication gaps between different stakeholders in the security ecosystem. Her recent publications reveal a strong focus on practical security challenges, particularly examining how geopolitical events impact security practices, how to measure trust in software dependencies, and the difficulties in implementing cryptographic solutions in real products. This research trajectory demonstrates her commitment to addressing security problems at the intersection of human behavior and technical systems. Dr. Acar actively mentors students through multiple courses including Seminar: Advances in Human Factors in Security and Privacy Research and two Proseminars introducing Human Factors in Security and Privacy Research. Her teaching directly reflects her research expertise, preparing the next generation of security researchers to consider human elements in technical security solutions. She leads research projects including Enabling a Secure and Trustworthy Software Supply Chain , demonstrating her leadership in addressing critical infrastructure challenges in modern software development. Her empirical approach to security problems provides valuable insights for both academic research and industry practice.

Sebastian FischmeisterView profile

Professor

• Embedded Systems
• Distributed Systems
• Formal Methods
• +8 more

Sebastian Fischmeister is a Professor and NSERC/Magna Industrial Research Chair in Automotive Software for Connected and Automated Vehicles at the Department of Electrical and Computer Engineering, University of Waterloo. His research focuses on systems at the intersection of software technology, distributed systems, and formal methods, with applications in automotive systems, avionics, and medical devices. He has pioneered frameworks for scalable location-based pervasive computing and verifiable real-time communication schedules, contributing to the ASTM F29.21 standard. Education: Dipl.-Ing. in Computer Science (Vienna University of Technology, 2000), Ph.D. in Computer Science (University of Salzburg, 2002) Research Themes: Real-time embedded systems, runtime monitoring, security analysis, data analytics for validation, and performance evaluation. Scientific Awards: APART Stipend (2005) Ontario Early Researcher Award (2014) Multiple best paper and tool awards He is an ACM Distinguished Speaker and actively participates in organizing conferences such as ESCAR, RTSS, DATE, and ICPE. His work includes significant contributions to anomaly detection, cybersecurity in automotive networks, and runtime verification techniques under unreliable conditions.

Judy JenkinsView profile

Senior Lecturer

• Health Informatics
• Qualitative Research Methods
• Leadership
• +5 more

Judy Jenkins is a Senior Lecturer and Program Director for the MSc in Health Informatics at Swansea University's School of Medicine. Since joining in 1999, she has combined academic leadership with NHS experience and industry work at Virgin Media. She serves as Senior Academic Mentor, Academic Misconduct Officer, and Admissions tutor for the program. Specializes in qualitative research methods Focus areas: clinical coding, health data governance, and digital health systems Active in postgraduate supervision and curriculum development Her research examines privacy concerns in health technology, digital health adoption in diverse populations, and the implementation of electronic health records. Recent work includes studies on menstrual cycle tracking apps (2025), mHealth in India (2024), and telehealth during the pandemic. Awarded as a Fellow of the Higher Education Academy, she contributes to academic governance and mentorship programs. Her teaching spans modules on data modeling, secondary health data usage, and digital healthcare systems implementation.

• Cybersecurity
• Digital Signal Processing
• Machine Learning
• +5 more

Dr Xiyu Shi serves as Senior Lecturer and Programme Director for MSc Digital Innovation Management at Loughborough University London's Institute for Digital Technologies. With over two decades of academic experience, he joined the university as a Research Fellow in 2014 before becoming Lecturer (2017) and Senior Lecturer, significantly shaping curriculum development for multiple MSc programs including Cyber Security and Data Analytics. His academic foundation includes a BEng in Radio Engineering from Southeast University (1984), MSc in Communication and Electronic Systems from Beijing University of Aeronautics and Astronautics (1989), and PhD in Computer Science from Cranfield University (2002). Prior to the UK, he accumulated 10+ years teaching experience at China's University of Petroleum. BEng, Radio Engineering, Southeast University (1984) MSc, Communication and Electronic Systems, Beijing University of Aeronautics and Astronautics (1989) PhD, Computer Science, Cranfield University (2002) Dr Shi's research focuses on cybersecurity, explainable AI, deep learning, and digital signal processing , with applications in communication security and audio systems. His work bridges theoretical algorithm development with practical implementation through EU-funded projects like CLOUDSCREEN and industry collaborations for 5G audio coding, emphasizing post-quantum privacy and robust deepfake detection. Analysis of his recent publications reveals a cohesive trajectory toward secure and interpretable AI systems , particularly in audio deepfake detection under communication degradations, IoT security via federated learning, and brain-computer interfaces for autonomous vehicles. These works consistently integrate signal processing fundamentals with cutting-edge machine learning to solve real-world engineering challenges. Scientific recognition includes: Fellow of the Higher Education Academy As Co-Investigator, Dr Shi secured an EPSRC grant on post-quantum privacy for digital healthcare and an industry grant for 5G immersive audio coding. He actively supervises PGR students developing deep learning solutions for cybersecurity and autonomous systems, while directing multiple MSc programs and delivering guest lectures at institutions including Nanjing University. Research activities are conducted within the Institute for Digital Technologies framework, leveraging close industry partnerships to translate theoretical advances into practical applications for communication systems and security infrastructure.

• Network Security
• Privacy Enhancing Technologies
• Digital Identity
• +4 more

René Mayrhofer is a full Professor at the Institute of Networks and Security, Johannes Kepler University Linz, leading the LIT Secure and Correct Systems Lab. With over 137 research outputs and active leadership in projects like the Christian Doppler Laboratory for Private Digital Authentication (Digidow), he is a key figure in network security and privacy research. His research focuses on practical security solutions for real-world systems, particularly in digital identity management , Tor network security , and mobile device authentication . Recent work addresses critical challenges in Android security states, biometric systems, and trusted execution environments, emphasizing deployable privacy-preserving architectures for physical-world applications. Analysis of his 15 most recent publications reveals strong trends in empirical security evaluation (e.g., Android device security studies) and system hardening (e.g., attested builds and backdoor mitigation), with growing emphasis on supply chain security and decentralized identity frameworks. Professor Mayrhofer has supervised 12 students and currently manages 6 research projects, including the active Digital Shadows initiative (funded until 2025) and the Digidow laboratory (running through 2026). His grants include significant support from federal authorities and the Austrian Research Promotion Agency. As principal investigator of the LIT Secure and Correct Systems Lab, he drives interdisciplinary research in secure communication protocols, privacy-aware authentication, and verifiable computing systems, collaborating with industry partners on real-world deployment challenges.

Marco PeressottiView profile

Associate Professor

• Choreographic Programming
• Concurrent Systems
• Formal Methods
• +5 more

Marco Peressotti is an Associate Professor of Computer Science at the University of Southern Denmark, where he is a member of the Department of Mathematics and Computer Science and the Section of Artificial Intelligence, Cybersecurity, and Programming Languages. He also serves on the Communication Group of the Microservices Community, an international research network. His academic career focuses on making concurrent and distributed systems more effective and robust through formal methods and programming language techniques. Dr. Peressotti received his Ph.D. in Computer Science from the University of Udine in 2017. His educational background forms the foundation for his current research in formal methods and distributed systems. Peressotti's research centers on choreographic programming, formal methods, and concurrency theory, with a unifying mathematical perspective rooted in Logic and Category Theory. His work aims to make programming and analysis of concurrent systems more effective and robust. He has made significant contributions to the development of choreographic programming languages, particularly through the Choral language, which integrates object-oriented programming with choreographic abstractions. His research spans theoretical foundations to practical implementations, with applications in microservices, cybersecurity, and distributed systems. His recent publications demonstrate a strong focus on advancing choreographic programming, with particular attention to handling communication failures, out-of-order execution, and practical applications in microservices architectures. His work increasingly intersects with cybersecurity concerns, particularly in supply chain security for small and medium enterprises. The trend shows growing engagement with practical policy implications of his theoretical work, as evidenced by numerous opinion pieces in Danish media outlets. Dr. Peressotti actively supervises students, with Valentino Picotti recently defending a PhD thesis on "Language Support for Microservices Development" under his co-supervision. His research has practical applications in software verification, as demonstrated by his introduction to Software Verification with TLA+ for participants of the Danish Cyber Championships. He collaborates extensively with researchers including Fabrizio Montesi and Jan Stentoft on cybersecurity awareness and supply chain risk management. As a member of the Section of Artificial Intelligence, Cybersecurity, and Programming Languages, Peressotti contributes to research groups focused on formal methods for distributed systems. His work with the Microservices Community connects him to an international network of researchers advancing service-oriented computing paradigms.

Botezatu Mihai AlexandruView profile

Professor

• Project Management
• IT Project Management
• Sustainable Development
• +4 more

Prof. Mihai Alexandru Botezatu serves as Dean of the Faculty of European Economic Studies and Full Professor in the Department of Informatics, Statistics, Mathematics at the Faculty of Managerial Informatics, Romanian-American University (URA). With 17 years of prior experience in public administration (Labor Inspectorate, Ministry of Labor, AMPOSDRU) and private sector project management (S&T Romania, Romanian Employers' Association), he brings practitioner expertise to academia since joining URA in 2015. His educational background includes a PhD in Cybernetics and Economic Statistics from Bucharest Academy of Economic Studies (2011) and undergraduate studies at URA's Faculty of European Integration Studies (2004). Professional development encompasses advanced training in project management, IT systems, and European funding mechanisms. Research focuses on interdisciplinary connections between IT systems and socio-economic policy, particularly AI/NLP applications in software development , sustainable development modeling , and European project management . Recent work analyzes Java code generation with AI tools, regional sustainable development metrics, and renewable energy drivers in Central/Eastern Europe, emphasizing practical implementation for labor market transitions. His 15 most recent publications (2019-2025) reveal an accelerating convergence of artificial intelligence with socio-economic analysis , shifting from traditional project management toward NLP-driven coding solutions and big data analytics for sustainable development indicators. This evolution reflects growing emphasis on generative AI tools while maintaining core focus on EU funding mechanisms and regional policy impacts. Prof. Botezatu has managed or monitored approximately 14 European-funded projects (2010-2019) and participated in three competitively funded research contracts (one international). His consulting firm specializes in European project management, complementing academic work through practical implementation of social responsibility measures and organizational management solutions. Professional engagement includes membership in Danube Adria Association for Automation & Manufacturing (DAAAM), Computer Science Teachers Association, and World Academy of Science, Engineering and Technology (WASET), supporting knowledge exchange in AI applications and sustainable development metrics.

• Software Engineering
• Software Security
• Artificial Intelligence in Software Engineering
• +2 more

Professor Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and maintains extensive industry experience from global corporations including IBM and DNV Research and Innovation. She currently serves on the EASE steering committee and holds the position of General Chair for FSE 2025. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans empirical software engineering with core focus areas in software security, AI integration in software development, and blockchain technologies. Her methodological approach emphasizes design science to create innovative tools and frameworks, particularly for security-critical systems and decentralized applications. Recent projects demonstrate strong industry collaboration in supply chain management, smart city infrastructure, and healthcare technology. Analysis of her 2023-2025 publications reveals dominant themes in blockchain governance (40%), security vulnerability detection/repair (35%), and AI-enhanced software engineering (25%). Key trends include empirical studies of Bitcoin consensus evolution, development of decision support systems for blockchain design patterns, and novel techniques for detecting unexploited smart contract vulnerabilities. Her work consistently bridges theoretical advances with practical industrial applications. Professor Li actively contributes to the research community through leadership roles including General Chair for FSE 2025 and EASE steering committee membership. Her grant portfolio features significant projects such as PaaSforChain (2020-2023, PI), CyberSmart (2017-2020, PI), and TRACE4EU (2023-2025, Key Scientist), demonstrating sustained funding success across blockchain, security, and AI domains. International collaborations include research visits to University College London, University of Washington, Hiroshima University, and Peking University. Her research is conducted within NTNU's Department of Computer Science, where she integrates cutting-edge industry experience with academic rigor to advance software engineering practices in security-critical and blockchain-based systems.

• Hardware Security
• Secure Processors and Systems Design
• Post-Quantum Cryptography
• +4 more

Michel Kinsy is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence and Director of the Secure, Trusted, and Assured Microelectronics (STAM) Center. His work bridges hardware security, cryptographic systems, and efficient computing architectures. Education: PhD in Computer Science from Massachusetts Institute of Technology His research focuses on hardware security , including secure architectures, trusted execution environments, quantum-proof cryptography, polymorphous architectures, and zero-trust computing systems. Recent projects explore privacy-preserving machine learning, zero-knowledge proofs, and homomorphic encryption acceleration. Key publication trends include: Hardware security for post-quantum cryptography (2020-2025) Secure distributed systems (2021-2025) Privacy-preserving machine learning implementations (2018-2025) Root-of-trust mechanisms in edge devices (2019-2023) Cryptographic protocol acceleration (2020-2024) Scientific Recognition: MIT Presidential Fellow CRA-WP Inaugural Skip Ellis Career Award He teaches graduate-level courses in computer architecture, research methodology, and thesis/dissertation advising, with recent offerings including CSE 792 Research , EEE 599 Thesis , and CEN 799 Dissertation . As STAM Center director, Kinsy leads initiatives in secure microelectronics and collaborates with hardware/software co-design teams. His research website provides detailed project information: https://stamcenter.asu.edu

Matthew WeberView profile

Professor

• Organizational Change
• Communication Technology
• Network Science
• +7 more

Matthew Weber is Professor of Communication at Rutgers University’s School of Communication and Information, where he also participates in the NetSCI Network Science lab and leads the Active Surveillance of Policy Ecosystems and Networks (ASPEN) Lab. His work is supported by the NSF, William T. Grant Foundation, Democracy Fund, and others. Education Ph.D., Communication – University of Southern California M.A., Communication – University of Southern California M.S., Journalism and Media Management – Northwestern University B.S., Industrial Engineering and Economics – Northwestern University Weber’s research interrogates how organizations adapt to new information and communication technologies. He combines macro- and micro-level perspectives to study digital disruption in news ecosystems, technology adoption in multinational firms, and the emergence of new organizational forms such as social networking sites. Methodologically, he integrates social-network analysis, archival research, interviews, and large-scale web-archived data to trace organizational processes over time. His recent articles converge on three themes: (1) algorithmic gatekeeping and code’s role in news distribution, (2) longitudinal network studies of journalism and NGO ecosystems, and (3) theoretical development around organizational speciation and disruptive innovation. Awards & Honors Rutgers Department of Communication Annual Research Award (2014) Web Science Top Paper Finalist (2012) Redding Dissertation Award, Dissertation of the Year (2012) ICA Organizational Communication Division Top Paper (2011) Industry Studies Association Dissertation of the Year Finalist (2011) Weber has served as Principal Investigator or Co-PI on grants totaling over $1.5 million since 2012, including NSF-funded web-archiving infrastructure projects, the Democracy Fund’s study of local news ecosystems, and the William T. Grant Foundation’s examination of policymakers’ use of research evidence. He teaches doctoral seminars in communication theory and research methods, and his labs provide training in computational social science and big-data approaches to organizational communication. Active research groups: ASPEN Lab, Computational Social Science Lab, NetSci Lab, Social Media & Society Cluster.

• Machine Learning
• Deep Learning
• Bioinformatics
• +6 more

Wolf Beat is an Associate Professor at the Fribourg School of Engineering and Architecture, part of the University of Applied Sciences of Western Switzerland (HES-SO). He is affiliated with the Institute of Complex Systems (iCoSys) where he conducts interdisciplinary research at the intersection of machine learning, bioinformatics, and document analysis. His educational background includes: BA HES-SO in Architecture from Fribourg School of Engineering and Architecture MSc HES-SO in Business Administration MSc HES-SO in Engineering PhD in "Reducing the complexity of OMICS data analysis" from University of Würzburg (2017) Dr. Beat's research spans multiple disciplines with a focus on applying machine learning techniques to solve complex problems. His work in bioinformatics has contributed to advancements in DNA sequencing analysis and genomic research, while his more recent work explores time series forecasting, document analysis, and anomaly detection. He has developed innovative approaches for handling historical manuscripts through computer vision techniques and has applied machine learning to geotechnical engineering problems. His research often bridges theoretical machine learning concepts with practical industrial applications. An analysis of his recent publications reveals a strong trend toward foundation models and diffusion models for time series analysis, alongside continued work in bioinformatics and document analysis. His research demonstrates a consistent pattern of applying cutting-edge AI techniques to domain-specific problems across diverse fields including healthcare, engineering, and digital humanities. Dr. Beat is actively involved in multiple research projects including ModIA (2024-2025, 15,000 CHF) and as principal investigator for the Foundation model for time series forecasting project (2024-2025, 100,000 CHF). His past projects include Monitoring des Transformateurs de Puissance (2023-2024, 220,000 CHF) and GREENum (2022, 24,700 CHF), demonstrating his ability to secure funding for interdisciplinary research. He collaborates extensively within the HES-SO network and with external partners, often serving as a co-researcher or principal investigator on projects that combine expertise from engineering, computer science, and domain-specific applications. His research team at iCoSys Institute includes multiple researchers working on AI and complex systems, and he has been involved in numerous projects with colleagues including Montet Frédéric, Pasquier Benjamin, Von Barnekow Alec, and Maillard Philippe. His work demonstrates a consistent commitment to developing practical AI solutions that address real-world challenges across multiple domains.

Neil KlingensmithView profile

Assistant Professor

• Cyber-physical systems
• Internet of Things (IoT)
• Embedded systems
• +4 more

Neil Klingensmith is an Assistant Professor of Computer Science at Loyola University Chicago, specializing in hardware-software co-design for cyber-physical systems. His research focuses on making IoT systems more efficient, reliable, and secure while maintaining strong educational leadership in operating systems and embedded systems courses. PhD in Computer Engineering from University of Wisconsin (2019) MS in Computer Engineering from University of Wisconsin (2016) BS in Electrical Engineering from University of Wisconsin (2010) Klingensmith's research spans three major areas: IoT Security : Innovating secure device authentication through environmental signals (power line noise, electromagnetic radiation) and analyzing vulnerabilities in automotive and conferencing systems Low-power Embedded Systems : Developing energy-efficient sampling techniques and hypervisor-based privacy agents for mobile/IoT devices Operating System Design : Exploring userland containers, real-time hypervisors, and memory management frameworks His recent publications demonstrate focus areas in authentication mechanisms , secure device pairing , and mobile virtualization . With 15+ years of academic and industry experience, he has secured significant funding including: $500k NSA NCAE grant (2023-2024) $250k NSF OAC grant for low-power computer vision (2021-2024) $110k US Department of Energy Fellowship (2013-2015) His students have successfully placed at major companies including Amazon, Google, and Boeing while advancing research in: Secure firmware development Real-time OS implementation Hardware authentication techniques Memory management optimization Embedded system design As co-founder of Emonix, he bridges academic research with commercial applications in HVAC automation. His patents in context-based device pairing demonstrate practical impact of his theoretical work.

Rob PasseyView profile

Research Fellow

• Energy Policy
• Renewable Energy
• Distributed Generation
• +3 more

Rob Passey is a Senior Research Fellow at the School of Photovoltaic and Renewable Energy Engineering, University of New South Wales (UNSW), with concurrent roles as Senior Manager at ITP Renewables and Policy Analyst/Treasurer at the Australian PV Institute (APVI). His work spans policy and regulatory analysis, technical assessments, business development, and project management in renewable energy systems, distributed generation, electric vehicles, and energy market design. His research interests focus on: Mechanisms for reducing greenhouse gas emissions and accelerating low-emission technology adoption Electricity tariff design and incentive structures Integration of distributed generation into electricity networks (including smart grids) Electric vehicle-grid interactions and network impacts Technical assessments of low-emission technologies End-user decision-making in distributed energy adoption Analysis of his 15 most recent publications (2019-2025) reveals dominant themes in battery storage economics, EV charging infrastructure, and cost-reflective tariff design. His work consistently addresses Australian market contexts, emphasizing community-scale energy systems, network integration challenges, and policy frameworks for decarbonization. Scientific Awards: No awards were documented in the provided materials. Advising and Grants: While no formal advisees or specific grant awards are listed, his extensive publication record (30 journal papers, 43 conference papers, 33 research reports, and 2 book chapters at UNSW, plus 64 consultancy reports at ITP Renewables) indicates significant leadership in research projects and policy initiatives across government and industry sectors. Labs and Teams: Passey operates within UNSW's globally recognized School of Photovoltaic and Renewable Energy Engineering while collaborating with ITP Renewables and the Australian PV Institute. These affiliations position him at the nexus of academic research, industry consultancy, and national policy development in renewable energy transition.

Cerian WebbView profile

Research Fellow

• Mathematical Epidemiology
• Plant Disease Modelling
• Animal Disease Modelling
• +3 more

Dr. Cerian Webb serves as a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge and an Associate Lecturer in Mathematical Biology at Newnham College. Her expertise bridges mathematical epidemiology across plant and animal systems, with particular focus on tree biosecurity, invasive species modeling, and pandemic response strategies. Her educational background includes: PhD in Mathematical Epidemiology from the University of Cambridge MSc in Mathematical Biology from the University of Dundee BSc (Hons) in Mathematics from the University of York Webb's research integrates network analysis, climate modeling, and policy evaluation to address critical challenges in agricultural and forest ecosystems. She has pioneered approaches for predicting invasive pest spread under climate change and developed frameworks for evaluating disease control policies in livestock systems. Her work consistently emphasizes translating complex models into actionable biosecurity measures. Analysis of her recent publications reveals three dominant research streams: climate-driven expansion of forest pests (accounting for 40% of recent output), pandemic modeling (30%), and computational biology education (30%). The pest modeling work demonstrates sophisticated integration of spatial data and climate projections, while her pandemic contributions focus on policy-relevant uncertainty quantification. Her scientific recognition includes: Kirsten Rausing Research Fellowship Isaac Newton Trust Fellowship Dr. Webb has supervised PhD, MSc, and undergraduate projects across mathematical biology and epidemiology. Her research has been funded through competitive fellowships from the Kirsten Rausing Foundation and Isaac Newton Trust, supplemented by Defra grants during her early career. Notably, during a childcare-related career break (2010-2016), she successfully secured funding for primary school music programs. She leads the Epidemiology and Modelling research group within the Department of Plant Sciences and co-founded the international '100 Plant Science Questions' initiative, which has engaged over 200 scientists worldwide to identify critical research priorities in plant science.