جست‌وجوی استاد و پژوهشگر

Khalid Osmanمشاهده پروفایل

استادیار

• Environmental Justice
• Water Resources Engineering
• Socio-Technical Systems
• +۵ مورد دیگر

Khalid Osman is an Assistant Professor of Civil and Environmental Engineering at Stanford University and a Center Fellow at the Woods Institute for the Environment. He joined the university in 2022, focusing on integrating equity into infrastructure systems through mixed-methods research. His work bridges socio-technical analysis with engineering solutions to address environmental justice challenges in water systems. Education: Bachelor of Science in Civil Engineering, University of Portland (2016) Masters of Science in Civil Engineering, University of Texas at Austin (2018) Doctor of Philosophy in Civil Engineering, University of Texas at Austin (2022) Research Interests: Osman’s research emphasizes equitable infrastructure design, particularly in water systems, through frameworks that incorporate community perspectives and participatory approaches. Key themes include: Operationalizing equity in decentralized sanitation systems Water affordability and stakeholder engagement Socio-technical systems analysis for resilience Climate adaptation and flood mitigation strategies Recent Trends in Publications: His recent work highlights community-driven solutions for water infrastructure challenges, leveraging machine learning for decision-making, and analyzing disparities in water access. Notable topics include green stormwater infrastructure adoption, flood resilience in vulnerable regions, and the role of social media in crisis communication. Awards: Bill and Melinda Gates Millennium Scholars Graduate Fellowship Ford Foundation Predoctoral Fellowship Advising & Lab Activities: As head of the Osman Lab , he mentors students in advancing equitable infrastructure solutions. Current advisees include PhD candidates Shuojia and Clara. The lab focuses on socio-technical frameworks to improve underserved communities’ access to resilient infrastructure. Labs/Teams: The Osman Lab collaborates with interdisciplinary teams to develop actionable policies and technologies. Recent projects involve: Community-based participatory research (CBPR) Graph neural networks for infrastructure analysis Large language models for translatable water reports

Besim Bilalliمشاهده پروفایل

پژوهشگر

• Machine Learning
• Data Governance
• Big Data
• +۳ مورد دیگر

Dr. Besim Bilalli is a researcher at the Universitat Politècnica de Catalunya (Technical University of Catalonia) within the Barcelona School of Informatics (FIB) and the Department of Service and Information Systems Engineering . He contributes to the inSSIDE and DTIM research groups, focusing on data governance, machine learning, and software engineering for data-intensive systems. His research interests include: Fair and interpretable machine learning Knowledge graph integration with language models Automated data lifecycle management Pre-processing pipeline automation AI ethics in healthcare applications Key projects include: EXPeriment driven analytics Automated data governance frameworks Erasmus Mundus doctoral program AutoETL pipeline generation Contact: besim.bilalli@upc.edu | ORCID: 0000-0002-0575-2389

Christian Büscherمشاهده پروفایل

پژوهشگر

• Technology Assessment
• Sociotechnical Systems
• Risk Analysis
• +۳ مورد دیگر

Dr. Christian Büscher serves as a Researcher at the Sociotechnical Futures and Policies Research Group within the Institute for Technology Assessment and Systems Analysis (ITAS) at Karlsruhe Institute of Technology (KIT). Having joined ITAS in 2006, he contributes to research at the intersection of technology, society, and risk assessment, with particular focus on monitoring emerging technologies for civil security applications. Dr. Büscher earned his Diplom in Sociology from Bielefeld University in 1998, completed a year of study at the University of Edinburgh's Science Studies Unit (1995-1996), and received his doctorate from TU Darmstadt in 2003. His professional journey includes technology consulting at VDI Technologiezentrum GmbH (2004-2005), senior research at alpS - Kompetenzentrum für Naturgefahrenmanagement (2002-2004), and scholarship support from the German Research Foundation at TU Darmstadt's Graduate College 'Technization and Society' (2000-2002). His research examines how sociotechnical systems evolve and how emerging technologies can be assessed to address societal challenges. Recent work focuses on transformation assessment methodologies, analyzing how technologies like AI might be misused for extremist purposes, and developing frameworks for monitoring technological developments in civil security contexts. His approach combines sociological theory with practical technology assessment tools. Analysis of Dr. Büscher's 2023-2025 publications reveals an intensifying focus on transformation assessment as a methodological framework, with growing attention to AI safety, carbon removal services, and systemic resilience. His work consistently bridges academic research with policy applications, particularly through the MOTRA project (Monitoring System and Transfer Platform Radicalization), which examines technology monitoring for extremism prevention. The publications demonstrate interdisciplinary integration of sociology, technology assessment, and security studies perspectives. As an active member of ITAS's Sociotechnical Futures and Policies Research Group, Dr. Büscher contributes to multiple projects analyzing sociotechnical transformations. His work provides critical insights for policymakers on emerging technological risks while developing methodological approaches for anticipating and assessing technological developments in complex societal contexts.

• Philosophy of Mind
• Philosophy of Technology
• AI Ethics
• +۵ مورد دیگر

Giulio Mecacci is an Associate Professor in Ethics and Philosophy of Intelligent Technology at Radboud University Nijmegen, affiliated with the Donders Institute for Cognition and the Faculty of Social Sciences. His work focuses on bridging philosophy with emerging technologies through ethical frameworks like Meaningful Human Control. Primary Affiliation : Donders Institute for Cognition (Radboud University Nijmegen) Teaching Roles : Ethics and societal impact of AI courses (bachelor/master), Neurophilosophy course (Donders CNS master's programme) Research Focus : Giulio investigates ethical, legal, and societal implications of AI and neurotechnologies. His research emphasizes responsible innovation and value-sensitive design , particularly addressing responsibility gaps in human-AI systems through the operationalization of Meaningful Human Control. Educational Impact : He actively contributes to engineering education through the 4TU.Centre for Engineering Education, integrating ethical considerations into technical training programs.

• Gender Studies in Engineering
• Diversity in Engineering Education
• Responsible Research and Innovation
• +۵ مورد دیگر

Carmen Leicht-Scholten serves as Professor for Gender and Diversity in Engineering at RWTH Aachen University, holding dual appointments in the Faculty of Civil Engineering and Faculty of Arts and Humanities. She directs the Responsible Research and Innovation (RRI) Hub and previously served as Vice Dean for Studies (2012-2016) and Rector's delegate for Socially Responsible Education (2016-2019). In 2014, she was awarded the Kármán Fellowship enabling her visiting professorship at Stanford University. Her research focuses on the social construction of science and technology, with particular emphasis on integrating diverse societal perspectives into participatory innovation processes for sustainable solutions. She has pioneered approaches to incorporate gender and diversity perspectives into engineering curricula at both national and international levels, serving as deputy member of the German Accreditation Council and as member of the European Association for the Study of Science and Technology (EASST). Analysis of her recent publications reveals an evolving research trajectory from foundational gender studies in engineering toward contemporary work examining algorithmic fairness, resilience in engineering education, and responsible AI implementation. Her scholarship consistently bridges social sciences with engineering practice while expanding into emerging technological ethics domains, demonstrating remarkable thematic coherence across nearly two decades of scholarly work. Scientific Recognition: Kármán Fellow (2014) Professor Leicht-Scholten actively contributes to multiple European educational initiatives and serves on the German Accreditation Council. Her leadership extends to directing the RRI Hub at RWTH Aachen, which focuses on strengthening resilience in urban environments through participatory approaches. She has developed innovative teaching approaches including flipped classroom concepts for diversity reflection in large engineering courses and has significantly influenced curriculum development across multiple European technical universities.

• Algorithmic Fairness
• Ethics
• Gender & Diversity Studies
• +۳ مورد دیگر

Marie Mirsch is a research assistant and doctoral candidate at RWTH Aachen University, affiliated with the Gender and Diversity in Engineering Research Group . Her work bridges mathematics, ethics, and social sciences, focusing on anchoring diversity perspectives in technology, particularly through intersectional algorithmic fairness and ethical AI . She is part of the ENHANCE European Universities of Technology Alliance and coordinates national/international projects via the Responsible Research and Innovation (RRI) Hub. Research Interests: Algorithmic fairness, intersectionality, procedural justice, participatory AI design, ethics in engineering. Teaching: Seminar 'Responsible AI for Engineers', MOOC 'Responsible Innovators of Tomorrow', workshop 'Responsible AI' at the University of Koblenz. Scientific Awards: Research Fellow of the AI Campus. Memberships: Executive Board of Open Aachen, Women in AI Aachen, and peer reviewer for journals like Frontiers in Artificial Intelligence and European Journal of Engineering Education. Her publications analyze ethical challenges in AI, procedural fairness in machine learning, and frameworks for responsible AI education. She supervises theses on topics like AI ethics and gender studies in engineering.

Stephan Hauمشاهده پروفایل

استاد

• Clinical Psychology
• Psychodynamic Diagnosis
• Trauma Studies
• +۳ مورد دیگر

Stephan Hau is a Professor at the Department of Psychology, Stockholm University. His research spans clinical psychology, trauma studies, and the intersection of art therapy with mental health. Notable ongoing projects include 'Playrooms – Animation and mentalization in puppetry' (2022–2024) examining puppetry's psychological mechanisms, and 'Posttraumatic Dreams and Symbolisation' (2014–2023) analyzing dream processes in PTSD patients. He also leads initiatives like 'Training better clinical psychologists: new methods based on machine learning, AI, and deliberate practice' (2024–2027) funded by the Norwegian Research Council. Primary Affiliation: Department of Psychology, Stockholm University Research Themes: Trauma integration through dreams, emotion recognition training, psychodynamic diagnosis for youth, AI in psychotherapy education His work combines qualitative interviews, polysomnography, and thematic analysis. Publications focus on resilience in marginalized groups, pandemic psychotherapy, and diagnostic systems like OPD-CA-2. Collaborations span institutions in Sweden, Norway, Serbia, and Germany.

• Anaesthesia
• Perioperative Medicine
• Artificial Intelligence
• +۳ مورد دیگر

Kira Philipsen Prahm serves as an External Lecturer within the Department of Clinical Medicine at the University of Copenhagen. Her institutional affiliation is evidenced by her regionsjaelland.dk email domain and Copenhagen address (Blegdamsvej 3, 2200 København N), linking her to Region Zealand's healthcare-academic partnership. Her research focuses on integrating artificial intelligence into perioperative medicine, specifically through the development of the TRIPLE-A (AI and Automation in Anaesthesia) Perioperative Database. This work centers on creating scalable platforms for epidemiological analysis, predictive modeling, quality control systems, and automated data retrieval within anaesthesia practice. Her methodology emphasizes real-world clinical implementation to enhance surgical safety and operational efficiency through data-driven decision support. Analysis of her sole documented publication reveals a strong trend toward operationalizing AI in routine anaesthesia workflows, with emphasis on longitudinal database utility since 2017. The research bridges clinical practice and data science, targeting practical applications in quality monitoring and predictive analytics for perioperative outcomes. Scientific Awards: No awards or honors were documented in the provided materials Advising and Grants: No graduate students or doctoral advisees were listed No research grants or funding sources were specified Laboratory and Collaborative Efforts: Active member of the TRIPLE-A Collaborator Group, a multidisciplinary Danish research consortium focused on AI implementation in anaesthesia Collaborates with clinicians and data scientists across Eastern Denmark's healthcare institutions

• Software Engineering
• Requirements Engineering
• Agile Methodologies
• +۳ مورد دیگر

Oriol Hilari is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Facultat d'Informàtica de Barcelona (FIB) and the Departament d'Enginyeria de Serveis i Sistemes d'Informació. He is part of the GESSI - Group of Software and Service Engineering and the inSSIDE research groups. His work focuses on software engineering methodologies, requirements engineering, and AI-driven systems. He has been involved in over 78 academic activities including 40 conference presentations, 13 journal articles, and 13 competitive R+D+I projects. Education: Ph.D. in Computer Science (implied by research output) Research interests span software quality management, agile development, DevOps automation, and sentiment analysis applied to user feedback. He leads projects like QaSD: Quality-aware Strategic Dashboard and Human-centred collaborative framework for software development . Key contributions include work on requirements mining from app reviews, context-aware monitoring architectures, and integrating gamification in learning environments. His research emphasizes practical applications in industry collaborations and educational tools for software teams. Awards: Best Forum Paper Award at RCIS 2023 He has secured funding through programs like Horizon Europe and the Spanish National Research Plan, collaborating with institutions like the Catalan Government and EU frameworks. His work bridges academia and industry, addressing challenges in AI system governance and trustworthy autonomous systems.

Greg Moriمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Video Analysis
• +۴ مورد دیگر

Greg Mori is a Professor at the School of Computing Science, Simon Fraser University. He holds a Ph.D. from UC Berkeley and an Hon. B.Sc. from the University of Toronto. His research focuses on computer vision and machine learning, particularly human pose estimation and activity recognition. He has served as Director of the School of Computing Science (2015–2018) and is now Senior Research Director at Borealis AI. Mori has contributed to methodologies like hidden Conditional Random Fields (hCRF), LDA variants, and deep networks. His work emphasizes features capturing visual intuition operationalized via machine learning. Education: Ph.D. in Computer Science, University of California, Berkeley (2004) Hon. B.Sc. in Computer Science and Mathematics, University of Toronto (1999) Research Interests: Computer vision, machine learning, video analysis, human activity recognition, human pose estimation, pedestrian detection and tracking, object recognition. Awards: CIPPRS Research Excellence Award (2008) NSERC Discovery Accelerator Supplement (2008, 2015) ICCV Helmholtz Prize (2017) Outstanding Reviewer Awards (ICCV 2009, CVPR 2010) Grants & Service: Program Chair for CVPR 2020 and General Chair for CVPR 2023 Editorial roles for IJCV and T-PAMI Organizing committee member for CVPR, ICCV, ECCV, NeurIPS, and ICLR Labs/Teams: Vision and Media Lab at Simon Fraser University, leading research in computer vision and machine learning applications.

• Machine Learning
• Algorithmic Fairness
• Human-Centric AI
• +۳ مورد دیگر

Lydia T. Liu is an Assistant Professor in the Department of Computer Science at Princeton University, with affiliations to the Center for Information Technology Policy and the Center for Statistics and Machine Learning. Her research bridges theoretical foundations of machine learning with societal impact, focusing on fairness, welfare outcomes, and policy implications in algorithmic decision-making. Education: Ph.D. in Electrical Engineering and Computer Sciences, University of California, Berkeley (2022) B.S.E. in Operations Research and Financial Engineering, Princeton University (2017) Liu’s work examines the intersection of machine learning and societal systems, including fairness evaluation, ethical deployment, and interventionist paradigms. She explores how predictive models operationalize policy changes and shape long-term outcomes, emphasizing human decision-makers and organizational constraints. Her recent research trends include: 2025 publications on coreset selection, interventionist AI, and multilingual language model evaluation 2024 studies on ride-sharing fairness, outcome prediction actionability, and workshop proceedings on bridging prediction and intervention 2023 PNAS paper reimagining ML for education equity Scientific Awards: Microsoft Ada Lovelace Fellowship Open Philanthropy AI Fellowship Amazon Research Award ICML Best Paper Award (2018, 2024) NeurIPS Joint Workshop Best Paper Award NUS Development Grant Liu advises PhD student Kara Schechtman and has led Princeton’s graduate course on “AI, Society, and Education,” with project groups presenting at AAAI 2025. She co-organized the 2024 BIRS workshop on prediction-intervention bridging and serves as ethics chair for ICML 2025. Her labs and workshops focus on interdisciplinary collaboration, including the Artificial Intelligence, Policy, and Practice (AIPP) initiative at Cornell and the Simons Institute’s 2026 Bridging Prediction and Intervention Problems in Social Systems workshop.

Atoosa Kasirzadehمشاهده پروفایل

استادیار

• AI Ethics
• AI Governance
• Risk Governance
• +۳ مورد دیگر

Atoosa Kasirzadeh serves as Assistant Professor in Carnegie Mellon University's Department of Philosophy within the Dietrich College of Humanities and Social Sciences, holding a courtesy appointment as Adjunct Professor in the Software and Societal Systems Department (School of Computer Science). Her research critically examines the intersection of AI development and ethical governance, focusing on responsible AI systems that benefit society through rigorous technical-philosophical integration. Her educational background includes dual doctoral degrees: a Ph.D. in Philosophy of Science and Technology from the University of Toronto and a Ph.D. in Mathematics (Operations Research) from École Polytechnique de Montréal, complemented by B.Sc. and M.Sc. degrees in Systems Engineering. Dr. Kasirzadeh's work bridges computational AI development with ethical frameworks through two primary research streams: Risk Governance (applying aviation safety models to identify/measure AI risks from incremental to catastrophic) and AI Value Alignment (operationalizing human values in AI design). She translates philosophical concepts into actionable technical guidelines, addressing transparency demands between users and algorithms while examining relationships among immediate, long-term, and systemic risks in advanced AI systems. Her scientific recognition includes: 2024 Schmidt Sciences AI2050 Early Career Fellow Fellow at the Centre for the Governance of AI Chancellor’s Fellow at University of Edinburgh DCMS/UKRI Senior Policy Fellow Governance of AI Fellow at Oxford As Steering Committee Member for ACM FAccT conference and World Economic Forum Global Future Council member (2025-2027), she advises public/private institutions on AI governance. Her collaborative work spans CMU's Philosophy, Software and Societal Systems, and Language Technologies Institute departments, advancing Herbert Simon's legacy of interdisciplinary integration where ethics becomes foundational to AI innovation rather than an afterthought.

Ashwinee Kumarمشاهده پروفایل

پژوهشگر

• International Health Law
• Cybersecurity Law
• Data Protection and Privacy
• +۳ مورد دیگر

Ashwinee Kumar serves as Scientific Employee at the Metajuridica research group within the Law, Science, Technology and Society (LSTS) department of Vrije Universiteit Brussel's Faculty of Law and Criminology. Concurrently, Kumar holds elected leadership as Co-coordinator of the European Society of International Law's Interest Group on International Health Law (2024-2028) and maintains active membership in ESIL. Research centers on technology-law-society intersections with emphasis on international health law , medical device cybersecurity , algorithmic governance , and blockchain regulation . Current projects address urgent gaps in digital health regulation including MDCG cybersecurity guidance implementation and WHO pandemic treaty frameworks. The work bridges technical specifications with legal requirements through translational research methodologies. Analysis of 14 publications (2019-2025) reveals consistent focus on operationalizing abstract principles into implementable frameworks, particularly in EU regulatory contexts. Recent outputs show growing emphasis on healthcare technology governance, with 2024-2025 works addressing real-time monitoring systems for medical device security and equitable digital health access. Kumar directs significant research initiatives including CYMEDSEC (focusing on LESoP aspects of medical cybersecurity) and contributes to LOCARD's blockchain forensics development. Current leadership in organizing the 2025 HELT Symposium and HALL-EKFZ Summer School demonstrates active project management and international collaboration. The 6-month OECD internship (2024) provided direct policy implementation experience. Based in VUB's Metajuridica group, Kumar operates within a dynamic interdisciplinary environment that connects legal scholars with computer scientists and public health experts. The research unit maintains active collaborations with EU institutions, WHO, and industry partners through projects like CYMEDSEC, with recent work influencing EU medical device cybersecurity standards and digital health equity frameworks.

• Biostatistics
• Health Outcomes Research
• Global Health Implementation
• +۴ مورد دیگر

Professor Alberto Nettel Aguirre holds dual roles as Honorary Professor in the School of Social Sciences and Professor of Biostatistics in the School of Mathematics and Applied Statistics at the University of Wollongong. He also directs the Centre for Health and Social Analytics. With over 20 years of expertise, he specializes in methodological rigor for health research, bridging clinical/medical challenges with statistical solutions through observational studies and trials. His work emphasizes global health intervention science and implementation strategies. Current research focuses include operationalizing diversity in healthcare AI datasets and enhancing public trust in secondary use of medical data. He co-supervises doctoral students in Canada and Australia, focusing on mitochondrial dynamics in neurodegenerative diseases and social media health communication strategies. Grants: Led projects funded by Advancement and Equity Grants Scheme (AEGiS), Canadian Institutes of Health Research (CIHR), and Alberta Innovates. Collaborations: Active in multi-disciplinary teams addressing global health challenges. Educational initiatives: Received a Learning and Teaching Innovation Grant (2022) for pedagogical advancements.

Reeshad S. Dalalمشاهده پروفایل

استاد

• Industrial/Organizational Psychology
• Job Performance
• Judgment and Decision-Making
• +۲ مورد دیگر

Dr. Reeshad S. Dalal is a Professor of Industrial/Organizational Psychology at George Mason University. He earned his Ph.D. from the University of Illinois at Urbana-Champaign and previously served as Assistant Professor at Purdue University. His research focuses on judgment/decision-making, job performance, work situations, personality, and cybersecurity psychology. Research interests span: Employee performance and counterproductive behaviors Decision-making competence and styles Personality-situation interactions Organizational approaches to cybersecurity His publications demonstrate strong interdisciplinary focus on behavioral dynamics, with recent work exploring AI advice systems, emotion regulation interventions, and leadership taxonomies. Articles emphasize methodological rigor through meta-analyses and ecological momentary assessments. Honors include Fellowship in the Society for Industrial and Organizational Psychology. He actively mentors Ph.D. students in organizational psychology and decision science.