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Gyunam ParkView profile

Researcher

• Process Mining
• Action-Oriented Process Mining
• Object-Centric Process Analysis
• +12 more

Gyunam Park is a Research Group Lead and Process and Data Scientist at Fraunhofer FIT and a Scientific Assistant at the Chair of Process and Data Science at RWTH Aachen University, a leading institution in computer science and engineering. He is actively involved in both research and teaching, contributing to the advancement of process mining, data science, and artificial intelligence. His work bridges academic research and industrial applications, particularly in SAP ERP systems and digital twins of organizations. Research Interests: Gyunam Park’s research focuses on Action-Oriented Process Mining (AOPM) , Object-Centric Process Analysis , and Responsible Machine Learning . He aims to transform process mining insights into actionable management decisions, ensuring transparency, fairness, and compliance. His work enables organizations to monitor operational constraints, generate corrective actions, and assess their impact using data-driven methods. Publication Trends: His recent publications emphasize object-centric approaches to process mining, predictive monitoring, constraint checking, and integration with AI planning. There is a strong trend toward preserving structural information in event logs, improving machine learning performance, and applying these techniques to real-world systems like SAP ERP and after-sales service processes. Scientific Awards: No awards are explicitly mentioned in the provided text. Advising and Grants: While no formal students are listed, Gyunam Park leads research projects and collaborates with industry partners such as Samsung Electronics and SAP. His projects involve root cause analysis, resource optimization, and educational data mining. He has developed open-source tools like ProAct and OCPA , indicating active grant or institutional support for software development and research dissemination. Labs and Teams: He is a core member of the Process and Data Science (PADS) group led by Prof. Wil van der Aalst at RWTH Aachen University and leads a research group at Fraunhofer FIT. These teams focus on cutting-edge research in process mining, data science, and AI, with strong industry collaborations and regular contributions to top conferences and journals.

Anna SidorovaView profile

Professor

• Artificial Intelligence in Business
• AI Ethics and Governance
• Digital Transformation
• +7 more

Anna Sidorova is a Professor and Chair of the Department of Information Technology and Decision Sciences at the G. Brint Ryan College of Business, University of North Texas. She holds a Ph.D. in Information Systems from Washington State University and has extensive experience in both academia and industry. Ph.D., Information Systems, Washington State University MBA, Washington State University B.A., Washington State University Her research focuses on Artificial Intelligence in Business , AI Ethics and Governance , Business Intelligence and Analytics , Text Mining , and Digital Transformation . She explores how organizations adopt and benefit from advanced technologies, particularly in decision-making and process improvement. The analysis of her publications reveals a strong trajectory in AI and machine learning applications in business, with a growing emphasis on ethical and governance aspects. Her work spans technical implementation and strategic implications, often published in premier journals like MIS Quarterly and Decision Support Systems . Dr. Sidorova has held significant leadership roles, including Academic Associate Dean for Undergraduate Programs at RCOB. She previously served as an Assistant Professor at the University at Albany, SUNY, and worked as a business consultant at PricewaterhouseCoopers, advising on business strategy and IT systems. She teaches graduate courses in Artificial Intelligence in Business, Information System Development, and Information Systems Theory and Research, contributing to the development of future business and technology leaders.

• Law and technology
• Tort law
• Artificial intelligence
• +3 more

Jan De Bruyne is a Lecturer at the Faculty of Law and Criminological Sciences, KU Leuven. He chairs the Research Unit KU Leuven Centre for IT & IP Law and serves as Division Head of the CiTiP Division (Center for IT & IP Law). He is actively involved in interdisciplinary research at the intersection of law, artificial intelligence, and technology, with a focus on liability frameworks, data governance, and ethical AI. Member of Leuven.AI - KU Leuven Institute for Artificial Intelligence Member of LIM - KU Leuven Institute for Mobility Member of LISS - KU Leuven Institute for Sports Sciences His research interests center on legal challenges posed by artificial intelligence, including liability for AI systems, comparative law approaches, and ensuring compliance through design. He explores fairness in AI through moral damage compensation, safety principles in healthcare AI, and regulatory mechanisms for human oversight in AI systems. His work addresses the democratization of Big Tech regulation, quality improvement in hernia surgery via big data, and user flexibility in energy networks. Recent publications analyze intersections between the AI Act and GDPR, EU data regulation for energy transitions, and comparative liability frameworks for autonomous vehicles. As a promotor or co-promotor, he leads 12 active research projects (2024-2028) on topics ranging from AI ethics to medical device regulation. Jan De Bruyne teaches courses including ICT Law, Electronic Contracts Law, and Technology & Law at KU Leuven.

Beau SchelbleView profile

Assistant Professor

• Human-AI Teaming
• Responsible AI
• Trust in Human-AI Systems
• +12 more

Beau Schelble is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, within the Tickle College of Engineering. He is the founding director of the AI and Robotics for Collaborative Systems (ARCS) Lab, where he leads interdisciplinary research on human-AI teaming, responsible AI, and team cognition. His work bridges human factors, systems engineering, and artificial intelligence, with applications in advanced manufacturing, healthcare, emergency response, and defense. Education: PhD in Human-Centered Computing, Clemson University, 2023 BS in Psychology, Clemson University, 2018 Dr. Schelble's research focuses on optimizing collaborative systems involving humans and AI. Key interests include trust development, situational awareness, shared knowledge, and ethical AI integration. He employs mixed-methods approaches—qualitative, quantitative, and computational—to study human-AI interaction in complex environments. His work has resulted in over 30 peer-reviewed publications in top-tier venues across human factors, HCI, and systems engineering. The 15 most recent articles reflect a strong trend toward ethical AI, explainability, autonomy adaptation, and team cognition in human-AI systems. Topics span healthcare applications, collaborative technologies, training methods, and emotional expression in AI teammates, demonstrating a broad yet cohesive research agenda centered on responsible and effective human-AI collaboration. Scientific Awards and Recognitions: NSF Research Traineeship (THINKER) Scholarship, August 2019 Multiple best paper awards and nominations (5 total) in human factors and systems engineering conferences Dr. Schelble actively mentors students and leads a dynamic research lab. He has secured research support through academic collaborations and professional engagement with IEEE, HFES, ACM, and IISE. His lab, ARCS, fosters innovation in AI-driven collaborative systems. Future work includes expanding frameworks for outpatient care, adaptive autonomy in healthcare, and deeper integration of human teaming principles into AI design. He continues to publish extensively and contribute to shaping the future of human-AI teaming.

• Information Retrieval
• Digital Libraries
• Informetrics
• +5 more

Philipp Mayr-Schlegel is a Professor at the University of Göttingen’s Institute of Computer Science, leading the team 'Information & Data Retrieval' at GESIS - Leibniz-Institute for the Social Sciences. His research focuses on interactive information retrieval systems, scholarly recommendation mechanisms, and the integration of bibliometric methods with digital library technologies. University of Göttingen - Institute of Computer Science GESIS - Leibniz-Institute for the Social Sciences His work spans information retrieval , digital libraries , and applied informetrics , with particular emphasis on: Interactive search systems Non-textual ranking algorithms Scholarly document processing Knowledge representation Semantic search technologies User behavior analysis Recent research outputs (2025) include studies on LLMs for scholarly search, bibliometric reproducibility tools, scientific uncertainty annotation, and preprint adoption disparities. He has published extensively in Scientometrics , International Journal on Digital Libraries , and top conference proceedings like ACL and ECIR . As organizer of the International Workshop on Bibliometric-enhanced Information Retrieval (BIR) and Scholarly Document Processing (SDP) series, he has shaped academic discourse through editorial roles at ISSI , JCDL , and SocInfo conferences. His projects have attracted significant national and European funding.

Yana BoevaView profile

Research Fellow

• Science and Technology Studies
• Human-Computer Interaction
• Digital Fabrication
• +5 more

Dr. Yana Boeva is a Junior Research Group Leader at the University of Stuttgart , affiliated with both the Institute for Social Sciences and the Cluster of Excellence IntCDC . Her work bridges Science and Technology Studies (STS) with Computational Design , focusing on critical examinations of digital infrastructure, human-computer interaction, and sustainability in architectural contexts. Research Interests: Algorithmic entanglements in design and construction Participatory technology production Digital fabrication and material practice Epistemic cultures of computational design Socio-political implications of Building Information Modeling (BIM) Her recent publications analyze timber construction innovation trajectories , platformization in urban environments , and ghost labor in automation . She co-edited the volume Algorithmic Regimes (2024), which investigates algorithmic knowledge production across societal domains. Scientific Awards: Recipient of the DigitalFUTURES Young Award for critical computational design research Dr. Boeva teaches courses on Algorithmic Sociology and Digital Sustainability at the MA and BA levels. Her work has been supported by projects under the Excellence Cluster IntCDC and BBSR Innovationsprogramm Zukunft Bau .

• Accounting
• Auditing
• Financial Reporting
• +4 more

Zuzana Juhászová is an Associate Professor at the Department of Accounting and Auditing within the Faculty of Economic Informatics at the University of Economics in Bratislava. She holds a PhD and has served in various leadership roles including vice dean for education (2007-2011, 2011-2015) and vice rector for education (2015-2019, 2019-2023) at her university. Education: PhD in Accounting (2003), habilitation in Accounting (2009), all from University of Economics in Bratislava Leadership: Former vice dean/rector roles focused on education Expertise: Auditing oversight since 2008 Research Focus spans accounting standards (IFRS 16 adoption), bankruptcy prediction modeling, XBRL technology applications, sustainability in business (including transport sector greening), and cryptocurrency networks for economic crime prevention. She has led multiple VEGA and APVV grants since 2007, including projects on financial decision-making in unstable markets and audit quality assessment. International Engagement includes Erasmus+ staff training at universities in Turkey, Poland, and Spain. Her academic output includes 33 publications in WoS/Scopus databases with 152 citations, focusing on audit regulation, financial reporting innovations, and integrated sustainability frameworks. Teaching Impact : Supervised 57 bachelor's theses, 150 master's theses, and 7 doctoral dissertations. She has also contributed to professional audit examination commissions.

• e-business
• supply chain management
• inter-organizational information systems
• +5 more

Dr. Evangelia Kopanaki is an Associate Professor at the Department of Business Organization and Administration within the School of Economics, Business and International Studies at the University of Piraeus, Greece. With a strong academic background in Mathematics, Informatics, and Information Systems, she has established herself as a prominent researcher and educator in the fields of digital transformation, e-business, and supply chain management. Dr. Kopanaki earned her BA in Mathematics and MSc in Informatics from the National and Kapodistrian University of Athens, followed by a PhD in Information Systems from the London School of Economics and Political Science. Prior to her current position, she worked as a researcher at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens for over three years, participating in numerous Greek and European research projects. She also has industry experience as an analyst-programmer in the private sector. Her research interests focus on the intersection of information systems and business operations, particularly in the areas of e-business, supply chain management, inter-organizational information systems, Internet technologies, and Business Agility. Dr. Kopanaki has published extensively in international conferences and journals, with a recent emphasis on digital transformation across various sectors including retail, banking, tourism, and transportation. Her work often explores how digital technologies can enhance sustainability, operational efficiency, and strategic decision-making in complex business environments. A significant portion of Dr. Kopanaki's recent research (2022-2025) examines the role of digital transformation in creating sustainable business practices, with particular attention to supply chain management, tourism, and financial services. Her publications demonstrate a strong focus on practical applications of emerging technologies like blockchain, AI, and big data analytics to solve real-world business challenges. The research shows a clear trajectory toward integrating sustainability considerations with digital innovation across multiple industry sectors. Co-author of two Academic Books in the fields of e-business and Internet technologies Extensive publication record in international conferences and journals Dr. Kopanaki has taught a variety of undergraduate and postgraduate courses at the University of Piraeus, including Operations Research, Management Information Systems, E-Commerce, and E-Commerce Programming & Design. She has also shared her expertise at the National and Kapodistrian University of Athens and the Singapore Institute of Management through the University of London International Programmes. Her teaching philosophy emphasizes the practical application of theoretical concepts, preparing students for the digital challenges of modern business environments. Through her work with the University of Piraeus, Dr. Kopanaki contributes to several research laboratories and initiatives focused on digital transformation, sustainable business practices, and innovative information systems. Her research projects often involve collaboration with industry partners and international academic institutions, creating valuable bridges between theoretical knowledge and practical business applications.

Alexander J. WulfView profile

Professor

• Law and Economics
• Contract Law
• Consumer Policy
• +5 more

Dr. Alexander J. Wulf is a Professor of Law and Economics at SRH Berlin University of Applied Sciences since 2023, specializing in the intersection of legal frameworks and economic principles. He also serves as a Lecturer at Bucerius Law School (2023). His research focuses on consumer policy, digital regulation, and institutional economics through empirical analysis and behavioral experiments. Doctor of Economics (2017), University of Siegen Doctor of Law (2013), Bucerius Law School MSc in Social Research Methods (2008), London School of Economics Master of Law and Business (2007), Bucerius Law School/WHU His publications examine transparency obligations in EU consumer law, GDPR compliance, energy regulation, and AI governance. Ongoing funded projects include climate change skepticism analysis (DBU) and online disclosure duties (DFG Germany). Association of scholarship holders and alumni of the Naumann Foundation (2014) SRH University award for outstanding teaching (2015) Current collaborations span institutions in Germany, UK, India, and the US, with visiting appointments at University of Oxford, Kyoto University, and UC Berkeley.

Katharina FroschView profile

Professor

• Human Resource Management
• Digital HR Tools for SMEs
• Work-Integrated Learning
• +6 more

Prof. Dr. Katharina Frosch holds the professorship for General Business Administration with a focus on Human Resource Management at the Brandenburg University of Technology since March 2015. She also serves as the overall project leader for the SCALE-C initiative and has held a research professorship in the field of "Digital- and AI-supported learning at the workplace" since September 2024. Additionally, she has been a member of the Senate of the Brandenburg University of Technology since October 2023. Her research focuses on digitally supported human resource management tools for small and medium-sized enterprises (SMEs), human resource economic analyses in knowledge-intensive sectors, and AI-supported workplace learning. Key research areas include testing digitally supported onboarding processes in SMEs, hybrid approaches to work-integrated learning, and developing low-threshold digital HR tools for the Brandenburg-Berlin metropolitan region. Her work emphasizes professionalizing interactions between HR managers and employees at critical points to improve recruitment, motivation, and retention of skilled workers. Prof. Frosch's recent publications demonstrate a strong trend toward AI-enhanced learning solutions, particularly in microlearning, conversation training, and cybersecurity education. Her research increasingly examines how AI technologies can transform workplace learning while maintaining human elements of communication and trust. The SCALE-C project represents a significant interdisciplinary effort combining cybersecurity, artificial intelligence, and learning design to create semi-automated microlearning content. Best Paper Award at eLmL 2023 for 'Scan to Learn: A Lightweight Approach for Informal Mobile Micro-Learning at the Workplace' Best Paper Award at ICDS 2023 for 'Taking the Matter in Their Own Hands – Can Business Unit Developers Fullfill their Digital Demands with Low-Code Development Platforms?' Prof. Frosch actively collaborates with SMEs and public institutions in the Brandenburg-Berlin metropolitan region, leading a community of researchers, students, and HR practitioners developing Open HRM tools. She offers numerous opportunities for students to participate in research through project work, theses, and the SCALE-C initiative. Her teaching portfolio includes courses on Human Resources and Organization, Strategic Personnel Management, and Applied Research in Personnel Psychology, with a special focus on the Open HRM Hackathon. She leads the Open HRM Community, which conducts regular hackathons to develop functional HR app prototypes. Current projects include scientific support for the Federal Office for Foreign Affairs in implementing psychologically supported digital onboarding approaches, developing digital learning laboratories for workplace competence acquisition in SMEs, and implementing digital HR processes for companies like Autohaus Mothor GmbH.

• Human-Computer Interaction
• Collaborative and Social Computing
• Computer Supported Cooperative Work
• +7 more

Dr. Ioanna Lykourentzou is an Associate Professor in the Software Technology for Learning and Teaching department at Utrecht University's Faculty of Science. She leads the Collaborative Technologies Lab and coordinates the Computing Science Master's and Information Sciences Honors Bachelor's programs. Additionally, she serves as a Fair Data and Software fellow within the Open Science Team of the Faculty of Science and as a member of the Ethics Review Board for the Faculties of Science and Geosciences. Her research focuses on collaborative and crowd systems, developing methods that help people work together, coordinate efforts, and innovate at scale, both online and in physical spaces. Her interdisciplinary approach combines computational science (machine learning, agent-based modeling, mathematical optimization) with social sciences (personality testing, team building). Her expertise spans Human-Computer Interaction, Algorithms, Agent-Based Modelling, Telecollaboration, Creativity, and Innovation. Her recent publications (2021-2025) demonstrate a strong focus on human-AI interaction, generative models, and applications in cultural heritage and education. She examines how technology can facilitate collaboration, with particular attention to team formation, personality factors, and digital nudging techniques. Her work bridges theoretical research with practical applications in digital humanities, cultural heritage, and computing education. Dr. Lykourentzou has received significant recognition for her research, with multiple publications garnering substantial citations and reader attention across platforms like Mendeley and social media. Her work on personality-based team formation (2016) has been particularly influential with over 90 citations. Prior to joining Utrecht University, she worked as a Senior Researcher at the Luxembourg Institute of Science and Technology (LIST), where she coordinated the European H2020 project CROSSCULT. She has also collaborated with the Human-Computer Interaction Institute of Carnegie Mellon University as a visiting researcher and with INRIA Nancy-Grand Est and the Public Research Center Henri Tudor as a postdoctoral fellow.

• Psychopathology
• Posttraumatic Stress Disorder
• Systematic Reviews
• +6 more

Bruno Messina Coimbra is a Researcher at Utrecht University's Faculty of Social and Behavioural Sciences, Department of Methodology and Statistics. He collaborates with Professor Rens van de Schoot on the development of ASReview and leads the FORAS project (Fully Open-source and Real-time AI-aided Systematic Literature Screening in Inclusive Databases). His work bridges methodology, statistics, and mental health research with a particular focus on trauma and PTSD. Dr. Coimbra holds a doctoral degree in Psychiatry and Medical Psychology. Previously, he served as research manager in the Program of Research and Care on Violence and PTSD at the Federal University of São Paulo (UNIFESP), where he investigated trauma effects on neuroprogression and adapted psychotherapeutic techniques for sexual assault survivors. His professional background includes extensive work with marginalized communities in disadvantaged regions of São Paulo. His research interests center on psychopathology, particularly Posttraumatic Stress Disorder (PTSD), with expertise in systematic reviews, meta-analysis, and telomere research as a biological mechanism for health disparities related to psychosocial stressors. He has made significant contributions to understanding moral injury among healthcare workers during the pandemic, the relationship between tonic immobility and PTSD development, and the impact of racial discrimination on mental health outcomes. His recent work integrates artificial intelligence with systematic review methodology to enhance research efficiency. Dr. Coimbra's publication record demonstrates a consistent focus on trauma-related mental health, with recent work expanding into AI-assisted literature screening methodologies. His research spans clinical investigations with sexual assault survivors, cross-cultural validation of assessment tools, genetic and epigenetic factors in PTSD, and the mental health impacts of the COVID-19 pandemic. The FORAS project represents his commitment to developing open-source tools that democratize access to advanced research methodology. Dr. Coimbra actively collaborates across international boundaries, working with institutions including RadboudUMC, UNIFESP, Umeå University, and NorthWest University in South Africa. His work with the Global Collaboration on Traumatic Stress and projects examining moral injury in healthcare workers demonstrates his commitment to addressing pressing mental health challenges on a global scale. He has contributed significantly to validating assessment tools like the Global Psychotrauma Screen in diverse populations. Based at the Sjoerd Groenman Building at Utrecht University, Dr. Coimbra leads research teams focused on AI-assisted systematic reviews and trauma research. His FORAS project team is developing innovative open-source tools to enhance literature screening processes, while his clinical research teams continue to investigate PTSD trajectories and treatment outcomes, particularly among vulnerable populations including sexual assault survivors and healthcare workers.

Dewar FinlayView profile

Professor

• Healthcare Technology
• Artificial Intelligence
• Digital Signal Processing
• +5 more

Dewar Finlay is a Professor of Electronic Systems and Head of the School of Engineering at Ulster University . He previously served as Research Director for the School of Engineering and Interim Associate Dean for Research & Impact within the Faculty of Computing, Engineering and the Built Environment. His work bridges healthcare technology and computational engineering. Education: BEng in Electronic Systems, Ulster University PhD in Computing, Ulster University Research Interests: His research focuses on healthcare technology with emphasis on computerised ECG analysis and deep learning applications in cardiology . He explores AI-driven diagnostics , signal processing , and medical device validation through projects like DTNet+ Digital Twin Network and IoT-Driven Cybersecurity Framework for Intrusion Detection in Drones . Scientific Awards: Best Poster (2024) - Calibrated Uncertainty AI in ECG Analysis Early Career Investigators Award (2022) - British Society for Heart Failure Grants & Collaborations: He has secured funding from EU Horizon 2020 , RCUK , DEL , and InvestNI . Current projects include AI-assisted echocardiography for congenital heart defects in Sub-Saharan Africa and federated learning frameworks for cardiac healthcare.

• Machine Learning
• Artificial Intelligence
• Model Visualization
• +3 more

Martin Mozina serves as an Assistant Professor and Researcher at the Faculty of Computer and Information Science, University of Ljubljana, where he has been affiliated with the Artificial Intelligence Laboratory since 2004. His primary institutional role focuses on advancing machine learning methodologies integrated with domain knowledge. His research centers on developing machine learning algorithms that incorporate prior knowledge alongside training data, with significant contributions to model visualization through nomograms and automated chess position analysis. Key innovations include argument-based machine learning frameworks and techniques for resolving knowledge acquisition bottlenecks in intelligent systems. Analysis of his 2004-2009 publications reveals consistent emphasis on interpretable AI, combining symbolic reasoning with statistical learning. His work bridges theoretical machine learning with practical applications in medical diagnostics, game AI, and decision support systems, particularly through nomogram-based classifier visualization and chess tutoring systems. He actively participates in major research initiatives including: DRIFT (L2-4436): Real-time optimization of low-voltage networks using deep incentivized learning (2022-2025) Umetna inteligenca in inteligentni sistemi: Agency-funded AI research program (2015-2020) Strojno učenje v gradnji inteligentnih sistemov: Machine learning for intelligent tutoring systems (2011-2014, 2013-2014) Molecular markers for lung cancer research (2011-2014, 2016-2018) X-MEDIA: Large-scale knowledge sharing across media (EU project, 2006-2009) Mozina's work within the Artificial Intelligence Laboratory demonstrates sustained focus on making machine learning more transparent and applicable to complex real-world problems through hybrid symbolic-statistical approaches.

Abhraneel SarmaView profile

Researcher

• Uncertainty Visualization
• Data Analysis
• Multiverse Analysis
• +3 more

Abhraneel Sarma is a PhD candidate in Computer Science at Northwestern University, advised by Professors Matthew Kay and Jessica Hullman. His research focuses on addressing uncertainty in data analysis through tools like multiverse (an R package for sensitivity analysis) and Milliways (a visualization system for multiverse analysis validation). Uncertainty visualization Multiverse analysis Bayesian inference Reproducibility in research His work combines empirical studies and system development to improve data-driven decision-making. Publications include best paper awards at CHI 2019 and honorable mentions at CHI 2024, CHI 2023, and VIS 2022. 2025 : CHI 2024 : CHI (Best Paper Honorable Mention) 2023 : CHI (Best Paper Honorable Mention) 2022 : VIS (Best Paper Honorable Mention) 2019 : CHI (Best Paper Award) Email: abhraneel@u.northwestern.edu