Find Academic Supervisors

Daniel Rodríguez GarcíaView profile

Associate Professor

• Data Mining
• Software Engineering
• Machine Learning
• +3 more

Daniel Rodríguez García is an Associate Professor (tenured) at the Department of Computer Science, University of Alcalá, Madrid, Spain. He also serves as a visiting researcher at Oxford Brookes University, UK, and previously held roles as an online tutor at the Universitat Oberta de Catalunya (UOC) and lecturer at the University of Reading (2001–2010). His academic credentials include a Computer Science degree from the University of the Basque Country and a PhD from the University of Reading (2003), complemented by a Postgraduate Certificate in Academic Practice (2005). His research focuses on data mining and software engineering , particularly applying machine learning techniques to software engineering challenges like defect prediction, classifier optimization, and cybersecurity. He leads the PROGRESSUS (Programming & Sustainability) and TIFyC (Information Technologies for Training & Knowledge) research groups, emphasizing sustainable software practices and educational technology innovation. His work spans topics such as DevOps monitoring, inclusive e-learning platforms, and AI-driven threat analysis in manufacturing industries. Notable contributions include the POEMA personal cloud system for education and studies on ransomware patterns in the Dark Web. His articles reflect trends in multi-objective optimization, imbalanced data handling, and ethical AI integration. He actively participates in workshops like RAISE (Realizing AI Synergies in Software Engineering), fostering cross-disciplinary collaboration.

Ali SunyaevView profile

Professor

• Health Information Technology
• Cloud Computing
• Distributed Ledger Technologies
• +3 more

Prof. Dr. Ali Sunyaev is a Professor of Computer Science at the Technical University of Munich (TUM), serving as Vice President of TUM Campus Heilbronn. He holds dual affiliations with the TUM School of Computation, Information and Technology and the TUM School of Management. His academic career includes roles as Director of the Institute for Applied Informatics and Formal Description Methods at the Karlsruhe Institute of Technology (KIT) and professorships at the Universities of Cologne and Kassel. Education: Studied Computer Science at TUM (2000–2005), earned a PhD in Computer Science and Information Systems focused on healthcare telematics security analysis. Research Interests: Interdisciplinary work on digital systems' societal impacts, health IT, cloud computing, blockchain, trustworthy AI, and information security. Notable Projects: Funded by DFG, Helmholtz Association, and Russian Science Foundation, exploring topics like federated learning, AI accountability, and decentralized systems. Awards: AIS Distinguished Member (Cum Laude), KIT Faculty Teaching Award (2020) Labs/Teams: Leader of the Karlsruhe Decision & Design Lab (KD²Lab), part of DFG Review Board and German Informatics Society (GI) Board. Grants: Multiple projects on health AI, blockchain in mobility, and cloud security certifications. Future Focus: Developing AI accountability frameworks, advancing federated learning applications in healthcare, and addressing ethical challenges in decentralized technologies.

Philip MenardView profile

Associate Professor

• Cybersecurity
• Information Security
• Security Education and Training
• +4 more

Philip Menard serves as Associate Professor of Information Systems and Cybersecurity at The University of Texas at San Antonio within the College of AI, Cyber and Computing. He holds a Ph.D. in Management and Information Systems from Mississippi State University and a B.S. from Nicholls State University, and functions as a Ph.D. Advisor for doctoral candidates in cybersecurity. His research centers on human-centric cybersecurity challenges, with three core thrusts: organizational impacts of security measures on end users, design and effectiveness of Security Education, Training, and Awareness (SETA) programs, and cultural influences on secure behaviors. He integrates psychological frameworks like Protection Motivation Theory and Self-Determination Theory to explain security compliance, emphasizing how linguistic fluency, curiosity, and personality traits shape responses to threats. Recent publications reveal expanding focus on AI privacy concerns, disinformation dynamics on social media, and blockchain adoption patterns, while maintaining foundational work in security training. His interdisciplinary approach bridges information systems theory with practical organizational security challenges across government, healthcare, and consumer technology domains. Scientific recognition includes: CyberCorps Scholarship for Service (SFS) Information Assurance Professional certification As a Ph.D. Advisor, Menard mentors doctoral researchers in cybersecurity human factors. His work has been supported by federal workforce development grants including CyberCorps SFS, which funds cybersecurity education and creates service obligations for scholarship recipients. He actively contributes to academic discourse through journal reviews for JMIS, JAIS, and Computers & Security. His research aligns with UTSA's cybersecurity initiatives through the College of AI, Cyber and Computing, contributing to national workforce development goals while addressing emerging threats in AI, blockchain, and social media ecosystems.

Xi Jessie YangView profile

Associate Professor

• Human-Robot Interaction
• Human Factors Engineering
• Autonomous Systems Trust
• +4 more

Xi Jessie Yang is an Associate Professor in Industrial and Operations Engineering and Robotics at the University of Michigan. Her research focuses on human-autonomy interaction, human factors in high-risk industries, and user experience design. She leads the Interaction & Collaboration Research Lab (ICRL), which develops design solutions for effective human-robot collaboration. Her research spans critical areas including trust dynamics in automation, explainable AI, and safety-critical systems. Key themes include understanding how users perceive and interact with autonomous systems in transportation, healthcare, and robotics contexts. Recent work emphasizes real-time trust modeling, adaptive human-robot teamwork, and mitigating risks through transparent AI interfaces. Publications highlight advancements in automated driving systems, pharmacy automation trust calibration, and social navigation for robots. Her team employs mixed-methods approaches combining experimental studies, computational models, and machine learning to address challenges in human-AI collaboration. Notable contributions include the TIP model for trust inference in multi-agent systems, context-aware trust profiles for automated vehicles, and frameworks for explaining AI decisions to non-experts. Her work bridges engineering, cognitive science, and social sciences to create human-centered technologies.

Amir Shayan AhmadianView profile

Researcher

• Software Engineering
• Privacy-Preserving Technologies
• Data Spaces
• +4 more

Dr. Amir Shayan Ahmadian is a Researcher at the Institute of Software Engineering within Department 4 at the University of Koblenz-Landau. His primary role involves software engineering research and teaching responsibilities. He has been actively involved in academic activities since at least 2015, with notable contributions to privacy-preserving technologies, model-based analysis, and industrial data ecosystems. His work emphasizes ethical AI, algorithmic fairness, and privacy-by-design frameworks. Research Interests: His core research focuses on privacy engineering , data space architectures , algorithmic fairness , and model-driven software development . He explores practical solutions for integrating privacy into system design, developing methodologies for detecting biases in AI, and creating scalable frameworks for secure industrial data sharing. His work often bridges theoretical computer science with real-world applications in healthcare, logistics, and manufacturing. Teaching Highlights: He has taught Web Engineering (2015-2019) and supervised seminars on Engineering Responsible Information Systems (2018). These courses emphasize ethical technology development and responsible innovation. Publications Overview: Ahmadian's recent work (2018-2024) reflects a strong focus on privacy-preserving systems and fairness in AI. Key themes include health data spaces, model-based verification for discrimination analysis, and industrial 4.0 platforms. His publications often propose novel architectures, methodologies, and tools to address emerging challenges in privacy, security, and algorithmic ethics. Labs/Teams: He contributes to the development of the VisiOn Privacy Platform , a tool for visual privacy management, and collaborates on projects like MBFair (model-based fairness verification). His work integrates closely with interdisciplinary teams focusing on healthcare IT, industrial automation, and cybersecurity.

Moritz von ZahnView profile

Researcher

• Artificial Intelligence
• Machine Learning
• Causal Inference
• +4 more

Dr. Moritz von Zahn is a Researcher at the Institute for Information Systems and Information Management, Goethe University Frankfurt, where he joined in February 2021. His research employs quantitative methods to investigate artificial intelligence applications, development, and societal impact, with current projects focusing on causal machine learning and explainable AI for economic problem-solving. He earned a doctorate in business informatics summa cum laude in 2024 under Prof. Oliver Hinz at Goethe University. Prior to this, he completed Bachelor's and Master's degrees in industrial engineering with distinction from Karlsruhe Institute of Technology (KIT), including visiting research periods at UNAM Mexico City, IST Lisbon, ETH Zurich, and Boston University. Von Zahn's work spans AI-driven solutions in e-commerce, mobile marketing, and sustainability. Key themes include causal targeting for mobile push notifications, fairness-explainability-performance trade-offs in AI systems, and 'smart green nudging' to reduce product returns. His methodology emphasizes causal inference to move beyond predictive correlations toward actionable insights. Analysis of his 15 most recent publications reveals a consistent trajectory toward integrating causal machine learning with explainable AI frameworks, particularly addressing ethical dimensions in recommendation systems and digital marketing. Recent work increasingly incorporates human factors, examining how AI explanations affect user trust and decision-making in commercial contexts. His research excellence is recognized through multiple awards: WISE Best Paper Award Dissertation Prize of the Faculty (Foit Foundation) INFORMS Best Paper Award in Information Systems Research AIS Best Information Systems Publication Award Finalist, INFORMS Gary Lilien Practice Prize Competition With industry experience at Robert Bosch, Swisscom, Payback, and McKinsey, von Zahn bridges academic rigor and practical implementation. He operates within Prof. Hinz's research team at Goethe University's Business Informatics Professorship, contributing to the institute's focus on information systems innovation while maintaining active industry collaborations.

• Artificial Intelligence
• Explainable AI
• Machine Learning
• +5 more

Inga Strumke is an Associate Professor at the Department of Computer Technology and Informatics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). Her work focuses on Artificial Intelligence , particularly in Explainable AI and Human-AI Collaboration , with applications in Healthcare and Ethics . She has published extensively on topics like algorithmic transparency, model interpretability, and societal impacts of AI. University: Norwegian University of Science and Technology Faculty: Faculty of Information Technology and Electrical Engineering Email: contact-ailab@ntnu.no Her research spans Machine Learning , Deep Learning , and Data Privacy , often addressing Algorithmic Ethics and Technological Governance . Recent publications focus on explainable methods for medical diagnostics, ethical AI deployment, and societal implications of automation. She actively engages in public discourse through op-eds in major outlets like Aftenposten, advocating for responsible AI development and education. Her work includes collaborations with interdisciplinary teams in Biomedical Engineering and Policy Analysis .

• Artificial Intelligence
• Data Science
• Information Systems
• +5 more

Patrick Mikalef is a Professor in Data Science and Information Systems at the Department of Computer Science, Norwegian University of Science and Technology (NTNU). His research focuses on the strategic use of information systems and IT-business value in turbulent environments, with particular emphasis on artificial intelligence, big data analytics, and digital transformation. B.Sc. in Informatics from Ionian University M.Sc. in Business Informatics from Utrecht University Ph.D. in IT Strategy from Ionian University His work explores responsible AI governance, metaverse ecosystems, AI capability maturity models, and the interplay between business analytics capabilities and innovation outcomes. He has published extensively in top-tier journals such as Journal of Business Research , European Journal of Information Systems , and Decision Support Systems . Recent publications (2024-2025) demonstrate his focus on artificial intelligence governance, explainable AI (XAI), digital transformation in manufacturing SMEs, augmented reality marketing, and algorithm appreciation. These works span computer science, information systems, and business analytics domains with specific subfields including AI ethics, digital policy, and technology adoption.

• Cybersecurity
• Software Security
• Phishing Detection
• +4 more

Adam Doupé is a full professor at Arizona State University, specializing in cybersecurity and software security. His research focuses on automated vulnerability analysis, phishing detection, binary decompilation, and security in web technologies. Key research areas include: Cybersecurity Software Security Phishing and Fraud Detection Binary Analysis Automated Vulnerability Discovery His recent work explores large-scale phishing mitigation using machine learning (e.g., ScamNet), improving binary decompilation techniques (e.g., SAILR), and analyzing fraud browser detection via fingerprints. Trends show a strong emphasis on practical security tools, human-centric security analysis, and firmware vulnerability discovery. While no specific awards or grants are listed in the DBLP data, Doupé actively contributes to security education through frameworks like SENSAI and CTF-as-a-service. He collaborates extensively with researchers such as Yan Shoshitaishvili, Ruoyu Wang, and Tiffany Bao.

• Power Systems
• Energy Systems
• Demand Response Programs
• +7 more

Pedro Faria is an Auxiliary Researcher at GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development) at Instituto Politécnico do Porto (ISEP/P.Porto). His work focuses on power and energy systems, emphasizing demand response programs, renewable-based distributed generation, energy storage, and electric vehicles, with expertise in real-time simulation using OPAL-RT and Hardware-In-the-Loop (HIL). He has coordinated 5 workpackages in international projects, led GECAD's teams in 5 projects (2 European, 3 national), and managed scientific coordination in 15 initiatives. As PI of the FCT-funded COLORS project, he has contributed to over 300 papers, including 85 in SCI journals, holds 3 European patents, and maintains a robust international collaboration network across 10+ countries. PhD in Electrical and Computer Engineering (2016, UTAD) MSc in Electrical Engineering (2011, ISEP) BSc in Electrical Engineering (2008, ISEP) His research bridges machine learning and optimization with power systems, particularly in demand response (DR) and real-time simulation. Current projects like MAST and PROSECO explore sustainability tradeoffs and sector coupling, while COLORS and FORMACOD address contextual DR flexibility and forecasting. He pioneered IEEE Taskforce on Open Datasets and serves in IEEE PES Working Groups. Pedro has supervised 2 PhD students, mentored 100+ researchers, and published extensively on DR algorithms, renewable integration, and HIL validation. Recent publications highlight explainable AI for consumption forecasting, battery reuse strategies, and grid impacts of EVs. Keywords span Smart Grids , Renewable Integration , Energy Storage , and Machine Learning . Sub-fields include Demand Response Modeling , Consumer Aggregation , Real-Time Simulation , Grid Stability , Green Computing , and Energy Policy Analysis . FCT funded individual research contracts (PostDoc 2019, Auxiliary Researcher 2021) Co-founder, IEEE Taskforce on Open Datasets Pedro has mentored 2 PhD, 15 MSc, 11 undergraduates, and 4 Erasmus students. He coordinated teams in DOMINOES, DREAM-GO, and M2MGrids projects, with 12 members in real-time simulation and 6 in ML/optimization. He teaches 'Intelligent Systems' and 'Energy Markets' at ISEP and contributed to Marie-Curie doctoral networks internationally.

Brígida TeixeiraView profile

Lecturer

• Artificial Intelligence
• Smart Grids
• Renewable Energy
• +7 more

Brígida Teixeira is a Ph.D. candidate in Computer Engineering (Intelligent Systems) at the University of Salamanca, Spain, and an Invited Assistant Lecturer at the School of Engineering of the Polytechnic Institute of Porto, Portugal. Her research focuses on Explainable AI (XAI) for power and energy systems, semantic interoperability in multi-agent systems, and renewable energy market optimization. Education: Ph.D. in Computer Engineering (Intelligent Systems), University of Salamanca (ongoing) Master’s in Computer Engineering, Polytechnic Institute of Porto (2019) Bachelor’s in Computer Engineering, Polytechnic Institute of Porto (2014) Her scientific work integrates XAI with smart grids and cyber-physical systems, aiming to improve transparency and user interaction in energy management. She has contributed to projects like MAS-Society, TradeRES, DOMINOES, DREAM-GO, and PRECISE, supported by grants from FCT and EU Horizon 2020. Her 27 publications span journals, book chapters, and conferences such as IEEE PES General Meeting and EPIA. Scientific Distinctions IBM Award of Scientific Excellence (2018) MDPI Electronics Journal Best Paper (2023) Certificate of Merit for Master’s Degree (2020) Certificate of Merit for Scientific Publications (2017) Brígida has supervised over 15 Master’s and undergraduate theses on topics like XAI for buildings, IoT platforms, and energy forecasting. She actively participates in IEEE working groups and conference committees, including AIPES and EPIA series.

• Energy Systems
• Electricity Markets
• Multi-Agent Systems
• +5 more

Gabriel Santos is a Research Fellow at the Polytechnic Institute of Porto, specifically at the Higher Institute of Engineering of Porto, where he works within the Research Group in Engineering and Intelligent Computing for Innovation and Development. His academic career spans over 15 years of continuous research in energy systems, with a particular focus on electricity markets and multi-agent simulation. His research interests center on the intersection of computer science and power engineering, with special emphasis on semantic interoperability, ontologies for energy systems, and multi-agent simulation of electricity markets. Santos has developed frameworks that enable different simulation platforms to communicate and work together, which is critical for modeling the complex interactions between power systems and electricity markets. His work has significant implications for renewable energy integration and the design of future electricity markets. Analysis of his recent publications reveals a strong trend toward local electricity markets, energy communities, and explainable AI for energy management. His work increasingly focuses on semantic interoperability solutions that enable realistic simulation of complex energy systems with high renewable penetration. The publications demonstrate a systematic approach to solving interoperability challenges in energy systems simulation through ontological frameworks. Santos has secured continuous funding from major research bodies including the European Commission and Portugal's Foundation for Science and Technology. His current projects include TradeRES (focusing on 100% renewable power systems) and PRECISE (cyber-physical solutions with explanatory semantic learning), indicating active research funding and relevance to current energy transition challenges. He leads research within the Research Group in Engineering and Intelligent Computing for Innovation and Development, where his team develops simulation tools for electricity markets that incorporate power flow analysis and semantic interoperability. This work supports the development of more realistic market models that account for both economic and physical constraints of power systems.

Hannes WestermannView profile

Assistant Professor

• Legal Informatics
• Artificial Intelligence in Law
• Dispute Resolution
• +4 more

Dr. Hannes Westermann serves as an Assistant Professor at the Faculty of Law, Maastricht University, specializing in Private Law. He is actively involved with the Maastricht Law and Tech Lab, focusing on the intersection of artificial intelligence and legal systems. His work combines technical innovation with legal expertise to address access to justice challenges. Maastricht University Faculty of Law Private Law Maastricht Law and Tech Lab Westermann's research centers on AI applications in legal contexts, including multimodal document analysis, dispute resolution systems, and legal autonomy frameworks. He explores the use of large language models (LLMs) for legal information processing, developing expert systems and Bayesian networks to enhance legal reasoning and accessibility. Recent publications demonstrate expertise in legal informatics, with 2024 contributions covering AI risk assessment, document analysis, and dispute resolution. His work includes 7 documented publications (2023-2024) and interdisciplinary collaborations with computer scientists and legal scholars. NWO-SGW Open Competition Law and Administration 2023 grant (€839,146) Westermann contributes to public discourse through media appearances, discussing AI's role in legal aid and strategies to close the justice gap. His research has been cited in multiple Plum Print metrics, indicating impact in legal technology and AI ethics domains.

David GotzView profile

Professor

• Visualization
• Visual Analytics
• Data Analysis
• +5 more

David Gotz is a Professor at the University of North Carolina at Chapel Hill School of Information and Library Science (SILS) , where he serves as Director of the Carolina Health Informatics Program and UNC's Certificate in Applied Data Science . He is also an Adjunct Professor of Computer Science at UNC. Dr. Gotz leads the Visual Analytics and Communication Lab (VACLab) , focusing on interactive visual methods for data analysis and communication in healthcare and life sciences. Education: PhD in Computer Science (UNC-Chapel Hill, 2005), MS in Computer Science (UNC-Chapel Hill, 2001), BS in Computer Science (Georgia Tech, 1999). His research integrates data visualization, human-computer interaction, statistics, and machine learning to address complex data challenges, particularly in healthcare. Recent work explores counterfactual reasoning in visual analytics to improve causal inferences from clinical data. He has received grants from the National Science Foundation (NSF) and National Institutes of Health (NIH) to support this work. Dr. Gotz has been recognized with awards such as the 2017 ACM Computing Reviews Best of Computing Honoree , 2016 ACM IUI Best Paper Award , and multiple IBM Research Accomplishment Awards for his contributions to visual analytics and health informatics. Scientific Awards: 2017 ACM Computing Reviews Best of Computing Honoree 2016 ACM IUI Best Paper Award 2015 Data Fellow, National Consortium for Data Science 2013 IBM Research Accomplishment Awards 2012 IBM Research Accomplishment Awards At UNC, Dr. Gotz teaches courses including INLS 560: Programming for Information Professionals , INLS 582: Systems Analysis , and INLS 641: Visual Analytics . He is open to advising new doctoral students through the VACLab , which emphasizes interdisciplinary collaboration with healthcare professionals and cancer researchers.

Tina Blegind JensenView profile

Professor

• Digitalization
• Organizational Transformation
• Algorithmic Management
• +7 more

Tina Blegind Jensen is Professor at the Department of Digitalization , Copenhagen Business School (CBS), Denmark. She investigates how digital technologies reshape work, organizations, and society, with a particular focus on human dignity, algorithmic management, and the future of digital labor. Research Interests Digitalization & Organizational Transformation: longitudinal studies of how enterprise systems, platforms, and AI reconfigure work practices and power relations. Algorithmic Management & Labour Organizing: trade-union perspectives on workplace datafication and collective responses to algorithmic control. Human Flourishing & Ethics in Digital Futures: conceptual and empirical work on preserving human dignity, agency, and well-being in increasingly data-driven environments. Healthcare Information Infrastructures: sociotechnical analyses of large-scale e-health implementations, comparing national strategies and clinical outcomes. Sociomateriality & Sensemaking: theoretical development of sociomaterial practice theory and sensemaking lenses to understand technology-in-use. Across 88 scholarly outputs (2018-2025) she has traced a trajectory from early critical studies of electronic patient records to cutting-edge debates on generative AI and the governance of digital labour platforms. A recurring theme is the tension between technological promise and lived experience of workers, patients, and citizens. Scientific Awards & Recognition While no specific awards are listed in the provided text, Professor Jensen’s sustained visibility in premier IS outlets ( Communications of the AIS, Scandinavian Journal of Information Systems, HICSS, Academy of Management ) and frequent keynote invitations testify to her scholarly impact. Doctoral Advising & Research Leadership Supervised at least two doctoral or master’s theses (recorded under “Supervised Work”). Active in doctoral consortia and serves on review committees (e.g., Aalborg University). Leads or co-leads multiple research projects on digital work futures funded by Danish and EU sources (exact grants not detailed in text). Labs, Teams & Collaboration She heads the Digitalization Research Group at CBS, coordinates the Copenhagen Digital Futures research network, and collaborates internationally with scholars in the US, UK, Germany, and Scandinavia. The group’s lab facilities support ethnographic field studies, digital trace data analytics, and participatory design workshops.