جست‌وجوی استاد و پژوهشگر

Cor Stegingمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Hybrid Intelligence
• Explainable AI
• +۳ مورد دیگر

Dr. Cor Steging is a Postdoctoral Researcher at the University of Groningen's Faculty of Science and Engineering, specializing in Artificial Intelligence through the Bernoulli Institute. His work focuses on bridging machine learning with structured reasoning, particularly in legal contexts, with strong emphasis on ethical and transparent AI development. Research interests center on Hybrid Intelligence systems that combine learning and reasoning, with specialization in Responsible AI and Explainable AI methodologies. Key focus areas include: Alignment of machine learning outputs with human-understandable reasoning Application of AI in legal domains and justice systems Development of transparent AI systems for high-stakes decision environments Handling incomplete/inconsistent data in critical applications Ethical implications of prediction systems in law Recent publications reveal a clear trajectory toward practical implementation of Responsible Hybrid Intelligence , with growing emphasis on legal applications and ethical frameworks. The 2024 doctoral thesis establishes foundational methodology for aligning learning and reasoning, while 2023 publications deepen exploration of legal domain applications and workshop organization for responsible AI development. Collaborative research demonstrates strong network connections with prominent AI researchers including Bart Verheij, Silja Renooij, and Trevor Bench-Capon. Current work addresses critical gaps in AI transparency for legal decision-making, with particular attention to small/inconsistent datasets and ethical design choices in machine learning systems.

Amna Batoolمشاهده پروفایل

پژوهشگر ارشد

• AI Governance
• Responsible Artificial Intelligence
• Human-Device Interaction in IoT
• +۳ مورد دیگر

Amna Batool is a postdoctoral researcher at CSIRO's Data61 , specializing in AI Governance , Responsible Artificial Intelligence , and Diversity in AI . Formerly, she conducted Ph.D. research at Deakin University's Faculty of Information Technology on Human-Device Interaction in IoT systems. Doctor of Philosophy (2023), Deakin University Master of Science (2017), Staffordshire University, UK Bachelor of Science (2015), Open University, UK Her research focuses on policy-driven frameworks for managing interactions in AI-embedded IoT systems, emphasizing responsible AI and socio-ethical behavior . She explores how transparent governance and inclusive design can address challenges in smart device collectives and global software development . Amna's work has been recognized with the IEEE Best Research Poster Award and Deakin HDR Best Presentation Award . She was a 3MT competition finalist and led an International Education Resilience Fund project during her Ph.D. IEEE Victorian Section Best Research Poster Award Deakin HDR conference Best Presentation Award 3MT Faculty Finalist As a Sessional Lecturer at Deakin University and Robotics (AIoT) Researcher at EXAPTEC, she bridges academic teaching with industry innovation. Currently, she mentors female STEM students through the STEM Sisters Ambassadorship program.

Lu Tangمشاهده پروفایل

دانشیار

• Biostatistics
• Machine Learning
• Health Data Science
• +۷ مورد دیگر

Lu Tang is an Associate Professor and Vice Chair for Education in the Department of Biostatistics and Health Data Science at the University of Pittsburgh School of Public Health. Her research bridges biostatistics and machine learning to advance health data science through integrative analysis of distributed and high-dimensional datasets, with significant applications in precision medicine, opioid use disorder, sepsis treatment, and public health policy. Dr. Tang's educational journey includes foundational training at Sun Yat-sen University followed by advanced degrees in quantitative fields: PhD in Biostatistics, University of Michigan (2018) MS in Statistics, University of Virginia (2013) BA in Mathematics, University of Virginia (2012) Her research program develops statistical methodologies for data integration, causal inference, and decision-making in healthcare settings. She pioneers techniques for federated learning, robust individualized treatment rules, and high-dimensional data analysis, directly addressing challenges in health disparities, electronic health records, and clinical trial heterogeneity. Her work consistently translates methodological innovations into practical tools for biomedical researchers. Analysis of Dr. Tang's publication trajectory reveals a strategic evolution toward solving real-world healthcare data challenges through distributed learning frameworks. Her recent work emphasizes robust decision rules for heterogeneous populations (2022-2025), transfer learning for federated systems (2024), and methodological innovations for longitudinal and high-dimensional data (2019-2023), demonstrating consistent contributions across biostatistics, machine learning, and public health domains. Dr. Tang has been recognized with: IMS New Researchers Travel Award (2023) She actively mentors 6 current graduate students across PhD and MS programs while supervising 8 alumni now in industry and academia. Her research program is sustained by major funding including NIH R21DA055672 (PI, 2023-2025) on federated Medicaid data analysis, NSF DMS 2310217 (PI, 2023-2026) for longitudinal missing data methods, and multiple NIH R01 grants as Co-I addressing opioid treatment equity and precision medicine in sepsis. Dr. Tang leads the development of critical open-source software including RISE (Python) for robust individualized decisions, ifedtree (R) for tree-based federated learning, and metafuse (R/CRAN) for data integration, establishing infrastructure widely adopted in health data science research communities.

Gabriele Margarete Buchholtzمشاهده پروفایل

استادیار

• Public Law
• Social Law
• Migration Law
• +۴ مورد دیگر

Prof. Dr. Gabriele Margarete Buchholtz holds the Junior Professorship for Social Security Law with a Focus on Digitalization and Migration at the University of Hamburg Faculty of Law . She has been a faculty member since November 2020 and leads research intersecting public law, social law, and digital governance . Education: Studium der Rechtswissenschaften, Bucerius Law School (2006–2011) First State Exam, Hanseatisches Oberlandesgericht (2011) Dr. iur., summa cum laude (2014) Second State Exam (2016) Research Focus: Her work addresses migration law, data protection, AI governance, and social rights in digital contexts . She co-edited Integratives Recht (2021) and Digital Health und Recht (2024), focusing on interdisciplinary legal frameworks. Article Trends: Recent publications examine AI ethics, federated learning in healthcare, data trust models, and European social rights . Collaborative works with computational researchers highlight privacy-preserving technologies and regulatory harmonization . Scientific Awards: Hugo Sinzheimer Dissertationspreis (2015) Kliemt & Vollstädt-Dissertationspreis (2014) Claussen-Simon-Stiftung Auszeichnung (2018) Daimler und Benz Stiftung Fellowship (2019) Konrad-Adenauer-Stiftung Promotionsförderung (2012–2013) Grants & Projects: Co-leader of TreuMed , a research project on data trust models in medical AI (funded by BMAS/FIS) Contributions to EU labor standards and OECD guidelines Labs & Teams: Collaborates with Computational Systems Biology Lab (Prof. Jan Baumbach) Part of interdisciplinary workshops on data certification and privacy labels

Victor Bolbotمشاهده پروفایل

پژوهشگر

• Autonomous ships
• Marine systems safety
• Ship propulsion systems
• +۳ مورد دیگر

Victor Bolbot serves as a Postdoctoral Researcher in the Department of Energy and Mechanical Engineering at Aalto University, Finland, affiliated with the Marine and Arctic Technology research group. His work focuses on advancing safety, reliability, and cybersecurity frameworks for autonomous maritime systems through rigorous systems engineering approaches and data-driven methodologies. He maintains active collaborations with international researchers and institutions, evidenced by extensive co-authorship across high-impact publications. Dr. Bolbot's research centers on autonomous ships, marine systems safety, ship propulsion cybersecurity, and risk modeling. He employs systems-theoretic process analysis (STPA), Bayesian networks, and association rule mining to address critical challenges including maritime accident causation, cybersecurity vulnerabilities in dual-fuel engines, safety acceptance criteria for autonomous vessels, and socio-technical implications of maritime automation. His methodological innovations bridge theoretical safety engineering with practical applications in Arctic navigation, inland waterways, and regulatory compliance, emphasizing the integration of cyber-physical risk assessment. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Development of cyber-physical risk frameworks like STPA-Cyber for maritime cybersecurity; (2) Real-time Bayesian modeling for dynamic operations including remote pilotage and ice navigation; and (3) Socio-technical investigations into regulatory frameworks, educational needs, and workforce skill transformations for autonomous shipping. His work consistently addresses the interplay between technological innovation and safety assurance, with growing emphasis on cybersecurity as a critical maritime safety component. As an active member of Aalto University's Marine and Arctic Technology research group, Dr. Bolbot contributes to interdisciplinary projects tackling complex challenges in marine safety engineering, Arctic operations, and sustainable maritime technologies. The group's collaborative environment supports the development of safer, more efficient, and environmentally conscious maritime systems through experimental validation, computational modeling, and industry partnerships.

Tor Endestadمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Cognitive Neuroscience
• Brain Imaging Methodology
• +۷ مورد دیگر

Tor Endestad is an Associate Professor in Cognitive Psychology at the University of Oslo, specializing in Cognitive Neuroscience and Brain Imaging Methodology. He leads the Endestad Brain Imaging Group (EBIG) and serves as Head of the fMRI Laboratory at the Center for the Study of Human Cognition. His research focuses on visual information processing, attention, memory control mechanisms, and motor responses to conflicting stimuli. International collaborations with University of Regensburg (Germany) and University of California, Berkeley (USA) Key research areas: source memory, constructive perception, neural oscillations, and music-brain interactions Recent publications span topics like auditory stream encoding, musical sensibility genetics, and neuroimaging techniques. His work integrates fMRI, EEG, and fNIRS methodologies across cognitive and clinical domains. EBIG members include postdoctoral fellows and researchers from psychology, medicine, computer science, and linguistics disciplines. The group participates in UiO:Life Sciences initiatives.

Julien Perretمشاهده پروفایل

پژوهشگر

• Geographical Information Science
• Urban Dynamics
• 3D Urban Simulation
• +۶ مورد دیگر

Julien Perret is a senior researcher at the National Institute of Geographic and Forest Information (IGN) in France, affiliated with the LASTIG laboratory and STRUDEL research team. His work spans geographical information science, urban dynamics, and historical cartography. Current Affiliation: National Institute of Geographic and Forest Information (IGN) Research Team: LASTIG, STRUDEL Academic Rank: Senior Researcher (Directeur de Recherche) Education Habilitation (HDR) in Geographical Information Science, Université Paris-Est (2016) PhD in Computer Science, Université Rennes 1 (2006) Engineering Degree in Computer Science, INSA Rennes (2002) Research Interests Perret's research focuses on urban dynamics through computational approaches, including agent-based modeling and 3D urban simulation . He investigates historical cartographic data like the Napoleonic land registry and Cassini Carte de France to understand long-term urban evolution. His work integrates geospatial data with epidemiological modeling using digital twins, particularly for pandemic simulations. Scientific Contributions Key publications include: 2025: Building change models for urban densification studies 2024: Historical map vectorization benchmarks 2017: Scalable point cloud management systems 2015: 3D analysis of urban regulation impact 2005: Procedural geometry modeling with FL-systems Advising and Collaborations Perret has supervised multiple PhD students and collaborated on projects like SoDUCo (1789-1950 Paris urban dynamics) and iSpace&Time (4D GIS for city modeling). He contributes to open-source GIS tools like GeOxygene .

• Explainable Artificial Intelligence
• Type-2 Fuzzy Logic Systems
• Computational Intelligence
• +۱۲ مورد دیگر

Hani Hagras is a Professor in the School of Computer Science and Electronic Engineering at the University of Essex, UK , where he leads pioneering research in type-2 fuzzy logic systems and explainable artificial intelligence (XAI) . His work bridges theoretical advances with real-world applications in smart infrastructure, healthcare, telecommunications, and ambient intelligence. His research interests include explainable AI, type-2 fuzzy logic, computational intelligence, machine learning, human-computer interaction, and intelligent systems. He investigates how fuzzy systems can enhance the transparency, robustness, and adaptability of AI models, particularly in uncertain and dynamic environments. His recent work explores applications in genomics, predictive maintenance, and smart grid optimization. The publication trends show a strong focus on integrating fuzzy logic with deep learning and optimization techniques to create interpretable models. His work frequently appears in top-tier journals such as IEEE Transactions on Fuzzy Systems , IEEE Transactions on Artificial Intelligence , and Neurocomputing . He emphasizes real-world applicability, often collaborating with industry partners like BT. ORCID: 0000-0002-2818-5292 He has advised numerous PhD and Master’s students, including Mehrin Kiani, Ashish Bhatia, and Hugo Leon-Garza, many of whose research projects focus on workforce optimization, healthcare AI, and intelligent systems. His research has been supported by major grants, particularly in smart environments and telecommunications. Hani Hagras is actively involved in leading research labs and teams at the University of Essex, including work on augmented reality for field service support, georeferenced data visualization , and ambient-assisted living systems. His team develops fuzzy logic frameworks for real-time decision-making in complex environments.

Joachim Baumeisterمشاهده پروفایل

استاد

• Semantic Information Systems
• Knowledge Graphs
• Deep Learning
• +۵ مورد دیگر

Joachim Baumeister is a Professor at the Chair of Computer Science VI - Artificial Intelligence and Knowledge Systems within the Institute of Computer Science at the University of Würzburg's Faculty of Mathematics and Computer Science. While his primary employment since September 2010 has been at denkbares GmbH, a company specializing in knowledge-based systems, he continues to regularly give lectures at the university. His research focuses on Semantic Information Systems, Knowledge Graphs, Deep Learning applications, Natural Language Processing, and Knowledge-based Configuration for Industry 4.0. Professor Baumeister's work bridges theoretical AI research with practical industry applications, particularly in knowledge-based configuration systems and semantic technologies. His recent publications (2020-2024) reveal a strong emphasis on product configuration systems, semantic knowledge representation, regulatory document processing, and knowledge-based systems. His research has evolved from foundational work on semantic wikis and knowledge engineering to more recent applications involving deep learning and large language models, demonstrating adaptability to emerging technologies while maintaining focus on practical knowledge representation problems. Professor Baumeister's work demonstrates significant contributions to case-based reasoning, knowledge configuration, and semantic technologies, with applications spanning regulatory compliance, industrial configuration systems, and document processing. His current research areas include: Semantic Information Systems and Knowledge Graphs Deep Learning for Image Recognition and Language Understanding Knowledge-based Configuration for Industry 4.0 Natural Language Processing Intelligent Personal Assistants and Chat Bots Though specific students aren't listed in the provided information, Professor Baumeister actively invites students to contact him regarding projects, bachelor theses, and master theses in his areas of expertise. His work at denkbares GmbH focuses on the design, implementation, and evolution of knowledge-based systems and semantic information systems.

Guy Jacobsمشاهده پروفایل

پژوهشگر ارشد

• Evolutionary genetics
• Population genetics
• Human evolutionary biology
• +۱۲ مورد دیگر

Guy Jacobs is a Research Fellow at the University of Cambridge, Department of Archaeology, specializing in evolutionary genetics and microbiome ecology. His work combines large-scale genomic datasets with computational modeling to investigate human evolutionary history, archaic hominin interactions, and microbiome dynamics during subsistence transitions in traditionally hunter-gatherer communities across India and Indonesia. Primary focus on population genetics, human adaptation, and social network impacts Expertise in computational modeling of evolutionary processes Collaborations with C-CLEAR DTP and CREATES partnerships Research spans ancient DNA analysis, archaic introgression patterns, and the interplay between genetic ancestry, environment, and health outcomes. Key projects include studies of Denisovan ancestry in Island Southeast Asia, microbiome differentiation in lifestyle transitions, and sociocultural influences on genetic diversity. Recent publications highlight trends in human adaptation to malaria and high-altitude environments, microbiome evolution during urbanization, and computational methods for detecting selective sweeps. His work integrates genomic data with social and environmental variables to address questions in biological diversity and human phenotypic variation. As part of the Cambridge NERC Doctoral Landscape Awards, he supervises students on topics ranging from archaic introgression analysis to genetic disease mapping. He utilizes datasets from Indonesia, India, and the Indonesian archipelago, combining genetic, transcriptomic, and mobility data in his research.

Michael Eichbergمشاهده پروفایل

استاد

• Software Engineering
• Static Analysis
• Software Development Tools
• +۳ مورد دیگر

Michael Eichberg is a Professor at Technische Universität Darmstadt, Germany, where his work centers on software engineering, static analysis, programming languages, and secure software development tools. He is the principal architect of the OPAL framework for Java bytecode analysis and has an extensive publication record spanning PLDI, ICSE, ESEC/FSE, ISSTA, ASE, FSE, SOAP, and other premier venues. Research Interests: Static program analysis and its scalability to real-world code bases Software security, particularly cryptographic API misuse and Android app repackaging detection Concurrent and parallel programming models, including deterministic concurrency in Scala Software architecture conformance, drift and erosion detection, and rule reuse Development of open extensible tools and frameworks (OPAL, LectureDoc, QScope, Sextant, XIRC, IRC) Publication Trends: His recent work (2015-2022) demonstrates a strong focus on empirical evaluation of static analysis techniques, modular composition of analyses, and security-related program understanding. Key themes include unsoundness in call graph construction, purity and immutability analyses, parallelization of static analyses, and large-scale studies of cryptographic API misuse. Tools & Frameworks: OPAL – A flexible Java bytecode analysis and manipulation framework (core developer until 2019) LectureDoc 2 – Web-based lecture material authoring and presentation system QScope – Open extensible metrics framework for modern software projects Sextant – Eclipse-integrated software exploration tool XIRC/IRC – Frameworks for enforcing system-wide properties and architectural constraints

Stacey Hendersonمشاهده پروفایل

دانشیار

• International Space Law
• Disarmament and Arms Control
• International Humanitarian Law
• +۷ مورد دیگر

Dr. Stacey Henderson serves as Associate Professor at Flinders University's College of Business, Government and Law, where she leads the Defence, Security & Space research theme within the Jeff Bleich Centre for Democracy and Disruptive Technologies. Her institutional affiliations include the Australian Centre for Space Governance (founding member), International Institute of Space Law, and Australian and New Zealand Society of International Law (council member 2020-2025). Her research focuses on the protective capacity of international law, with specialized expertise in space governance, disarmament, and atrocity prevention. Key areas include commercial space activities, grey zone operations in space/cyber domains, information warfare, sustained human presence in space, and the Responsibility to Protect (R2P) framework. Her current Office of National Intelligence-funded project examines chemical/biological agent use against non-human targets. Recent scholarly output demonstrates strong thematic concentration in space law evolution (2023-2024), with 10 publications addressing critical infrastructure protection, sustainable resource utilization, and corporate accountability in space. Concurrent work explores disinformation threats to democracy and legal education reform. Her research directly supports UN Sustainable Development Goals through contributions to peace, justice, and institutional development. Vice Chancellor's Early Career Researcher Award (2024) Director, Space Law Council of Australia and New Zealand (2022-2024) Steering Committee Member, Australian Centre for Space Governance Henderson actively contributes to national security policy through media engagements on arms control, space law, and information operations. Her Jeff Bleich Centre leadership role connects academic research with defense and security applications. Current projects include developing frameworks for space as critical infrastructure and analyzing disinformation impacts on democratic processes.

Mort D. Websterمشاهده پروفایل

استاد

• Stochastic optimization
• Electric power systems
• Energy systems design under uncertainty
• +۷ مورد دیگر

Mort D. Webster is Professor of Energy Engineering and Associate Department Head for Graduate Education at the John and Willie Leone Family Department of Energy and Mineral Engineering, College of Engineering, Pennsylvania State University. His research focuses on stochastic optimization and decision-making under uncertainty for energy and environmental systems, with particular expertise in electric power systems, climate impacts, and coupled multi-sector dynamics. Ph.D. in Engineering Systems, MIT (2000) M.S. in Technology and Policy, MIT (1996) B.S.E. in Computer Science and Engineering, University of Pennsylvania (1988) Webster's research program includes stochastic multi-stage optimization algorithms , electric power systems planning , coupled energy-water-land modeling , and resilience studies . He leads the Program for Coupled Human and Earth Systems (PCHES), funded by the U.S. Department of Energy, which develops integrated models for weather-related variability impacts on power systems. Recent work involves transmission expansion under uncertainty , electricity market flexibility valuation , and cross-sectoral climate impact analysis . His publications span journals in energy systems, environmental science, and operations research, with methodological innovations in scenario reduction and stochastic programming. Scientific Awards : U.S. Department of Energy Early Career Award (2010) Mentorship includes advising graduate students Jesse Bukenberger, Vijay Kumar, Brayam Valqui, and Sourabh Dalvi. His research has received funding from the National Science Foundation, U.S. Department of Energy, and General Electric Power Services Division. Collaborative efforts include partnerships with Karen Fisher-Vanden and Uday Shanbhag on coupled system resilience, and Thomas Hertel on energy-agriculture-water nexus projects.

Marion Tränkleمشاهده پروفایل

مدرس

• Performance Art
• Systems Thinking
• Interactive Media
• +۵ مورد دیگر

Marion Tränkle is an active lecturer at the ArtScience Interfaculty of the Royal Academy of Art, The Hague (KABK), where she coaches students and develops courses on systems thinking and rule-based performance systems. She also serves as a Coach and Industrial Liaison at Eindhoven University of Technology's Department of Industrial Design since 2014, working with Professor Harm van Essen on 'social interactions with shared systems.' Her educational background spans multiple disciplines: PhD from Brunel University London (2012), MSc in Media Technology from Leiden University (2005), BA in Contemporary Dance from Amsterdam School of the Arts (2001), and an Engineer Diploma in Architecture from Technical University Berlin (1993). She has also completed specialized training in Software Engineering (2017/18) and Stage Lighting (2016). Tränkle's research interests center on the intersection of performance art, systems thinking, and technology. She creates work that deliberately negotiates 'the constructive tension between the carefully constructed and generative processes, between risk and responsibility, and between autonomous performance and human intervention.' Her practice integrates computational processes with live-performance, often using electronics, EEG data, and interactive systems to create immersive stage scenarios. She explores how simple rules can generate complex emergent behaviors, drawing from complexity science and computing principles. Her recent creative works demonstrate a consistent exploration of brain-computer interfaces, interactive light systems, and collaborative performance structures. Projects like (un)focussed and BLINK...and sync use EEG data to create real-time visual and auditory experiences, while ON TRACK and TAROT investigate mechanical systems and embodied symbolism through performance. 2nd Prize in the competition for short dance films on Internet 'webdans' (2001) Netherlands Foundation for Visual Arts, Design and Architecture Research/Travel Grant (2010) e-MobiLArt participant, funded EU CULTURE 2007 Programme (2008-09) Brunel University Doctoral Research Scholarship/fee waiver (2007-10) Tränkle actively collaborates with artists, designers, and engineers through collectives like NOW (with Ivo Bol and Roos van Berkel) and previously In Serial. She is a member of the BAU Committee for Amsterdam's independent performance scene. Her teaching philosophy emphasizes that 'making, learning, and teaching are reciprocal processes that flourish best in collaborative, and project-based environments,' which she implements through workshops, seminars, and interdisciplinary courses across multiple institutions in the Netherlands, Germany, and Canada.

James Repettiمشاهده پروفایل

استاد

• Tax Law
• International Taxation
• Estate and Gift Taxation
• +۴ مورد دیگر

James Repetti is the William J. Kenealy, S.J., Professor of Law at Boston College Law School, where he has taught since 1986. He holds an A.B. from Harvard University, an M.B.A. from Boston College, and a J.D. from Boston College. As a nationally recognized tax expert, Repetti serves as co-author of three major textbooks including Introduction to United States International Taxation (7th Ed., 2022), Partnership Income Taxation (7th Ed., 2023), and Federal Wealth Transfer Taxation (2015). He has published extensively in top law reviews and is a fellow of the American College of Tax Lawyers with an AV Preeminent Martindale-Hubbell rating. Harvard University - A.B. Boston College - M.B.A. Boston College Law School - J.D. Repetti's research focuses on international taxation, estate and gift taxation, partnership tax structures, and tax equity principles. His work addresses both theoretical frameworks and practical applications in federal tax policy, with particular attention to wealth inequality, corporate governance, and cross-border tax implications. He co-founded BC Law’s Tax Policy Collaborative and has consulted for the U.S. Senate Budget Committee, Internal Revenue Service, and Justice Department. His scholarly contributions include over 20 books and numerous articles in journals such as the NYU Law Review , Vanderbilt Law Review , and Notre Dame Law Review . Repetti has received significant recognition, including Boston College Law School’s first Excellence in Teaching Award (1999) and election to the American College of Tax Counsel (2020). His commentary appears regularly in major media outlets including Bloomberg, Washington Post , and Wall Street Journal . Fellow, American College of Tax Lawyers AV Preeminent Martindale-Hubbell rating Excellence in Teaching Award, BC Law (1999) Member, American College of Tax Counsel (2020)