جستجوی استاد راهنمای دانشگاهی

Michael Schaubمشاهده پروفایل

استادیار

• Network Science
• Dynamical Systems
• Machine Learning
• +۳ مورد دیگر

Michael Schaub is a tenure-track Assistant Professor in the Department of Computer Science at RWTH Aachen University, specializing in Computational Network Science. His research focuses on analyzing complex systems through network and graph models, integrating dynamical systems, control theory, and machine learning. He leads the Computational Network Science group, advancing methodologies for higher-order network models like simplicial complexes and hypergraphs. Schaub holds a PhD from Imperial College London and has held postdoctoral positions at MIT and Oxford. He is an ERC Starting Grant recipient (2022) and a Marie Curie Fellow, recognized for contributions to network dynamics and topological data analysis. Education: PhD in Mathematics, Imperial College London (2011-2015) MSc in Biomedical Engineering, Imperial College London (2010) BSc in Electrical Engineering, ETH Zurich (2007-2010) Research Interests: Schaub’s work spans interdisciplinary applications of network science, including biological systems, social networks, and technical infrastructures. Key areas include: Higher-order network models (hypergraphs, simplicial complexes) Graph signal processing and dynamics on networks Community detection and dynamical systems analysis Topological data analysis and machine learning Grants & Awards: ERC Starting Grant (2022): HIGH-HOPeS project Marie Skłodowska-Curie Fellowship (2017-2019) Junior Fellow, German Informatics Society (GI) Member of Junges Kolleg (North Rhine-Westphalia Academy) Labs & Teams: Leads the Computational Network Science Lab at RWTH Aachen, collaborating internationally on projects like the ELLIS Society and the European Laboratory for Learning and Intelligent Systems (ELLIS). Active in organizing workshops (e.g., Toponets, SIAM MDS).

Ming Caoمشاهده پروفایل

استاد

• Multi-agent systems
• Autonomous Robots
• Complex Systems and Networks
• +۴ مورد دیگر

Ming Cao is a Full Professor at the University of Groningen (Netherlands), holding positions in the Department of Discrete Technology and Production Automation, the Engineering and Technology Institute Groningen, and serving as Chair of the Jantina Tammes School of Digital Society, Technology and AI. His academic roles include Director of the Jantina Tammes School and membership in prestigious organizations such as the International Federation of Automatic Control (IFAC) and the European Commission’s DG CNECT. Cao’s research focuses on multi-agent systems, autonomous robotics, complex networks, and cooperative control, with applications in robotics, epidemic modeling, and biomimetic sensors. Education: PostDoc in Mechanical Engineering from Princeton University (2008), PhD in Electrical Engineering from Yale University (2007). Research Interests: Multi-agent systems, distributed decision-making, cooperative control, robotic teams, seal whisker-inspired flow sensing, and privacy-preserving control systems. Recent Trends in Articles: Recent work emphasizes co-evolutionary dynamics in social-technical systems, privacy in control systems, and biomimetic robotics. Key topics include feedback mechanisms in cooperation, hypergraph-based epidemic models, and seal whisker mechanics for underwater sensing. Awards: European Control Award (2016), Manfred Thoma Medal (2017), ERC Grant (2012). Grants: Vidi Grant from NWO (2015) for agent coordination research. Labs/Teams: Jan C. Willems Center for Systems and Control, Research Center for Data Science and Systems Complexity (DSSC). Active in editorial roles for journals like Artificial Life and Robotics and the SIAM Journal on Control and Optimization .

Jean Goodwinمشاهده پروفایل

استاد

• Science Communication Ethics
• Civil Argumentation
• Public Science Communication
• +۳ مورد دیگر

Dr. Jean Goodwin is the SAS Institute Distinguished Professor of Rhetoric & Technical Communication at NC State University's Department of Communication, part of the College of Humanities and Social Sciences. She specializes in science communication ethics, civil argumentation, and the rhetoric of controversial scientific topics such as climate change and GMOs. Her work bridges theory and practice, including NSF-funded initiatives like Teaching Responsible Communication of Science, which develops case studies for STEM graduate students. She also leads the Leadership in Public Science cluster through NC State's Chancellor’s Faculty Excellence Program. Education: B.A. in Mathematics (University of Chicago, 1979), J.D. (University of Chicago, 1984), and Ph.D. in Communication/Rhetoric (University of Wisconsin-Madison, 1996). Her career includes over 25 years of teaching rhetoric and mentoring students across communication subfields. Research focuses on how scientists communicate effectively with non-experts, leveraging discourse analysis and conceptual frameworks like speech act theory. Key themes include trust-building in contentious contexts, ethical advocacy roles for scientists, and historical rhetorical strategies from Cicero to modern policy debates. Her work often intersects with civic engagement and interdisciplinary collaboration, such as organizing conferences for science communication scholars and advising organizations like the AAAS. Major publications explore ethical dimensions of science communication, including climate change advocacy, disinformation detection, and pandemic messaging. Awards include the EB Knight Journal Award (2007) and her distinguished professorship. Current initiatives emphasize translating scholarly insights into practical tools for scientists and fostering dialogue between scientific and public communities through funded research partnerships.

Dino Pedreschiمشاهده پروفایل

استاد

• Big Data Analytics
• Social Network Analysis and Mining
• Analysis of Human Mobility
• +۱۷ مورد دیگر

Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.

Caren Walkerمشاهده پروفایل

استادیار

• Cognitive Development
• Causal Learning
• Relational Reasoning
• +۵ مورد دیگر

Caren Walker is an Assistant Professor in the Department of Psychology at the University of California, San Diego (UCSD), leading the Early Learning and Cognition (ELC) Lab. Her research focuses on how children learn abstract causal principles, particularly through activities like analogy, explanation, and engagement with imaginary scenarios. She explores developmental trajectories in scientific reasoning and the role of cultural context in shaping cognitive processes. Dr. Walker’s work combines interdisciplinary approaches from psychology, philosophy, and computational modeling. She investigates children’s understanding of uncertainty, causal inference, and the decline of relational reasoning with age. Her lab conducts experiments in diverse settings, including partnerships with museums, to study learning mechanisms in real-world contexts. Notable achievements include the 2024 APA Boyd McCandless Award and the 2021 NSF CAREER Award. The ELC Lab actively engages undergraduate researchers and collaborates on projects addressing cognitive diversity across cultures. Recent lab milestones include studies on US-China differences in causal reasoning and the impact of stereotypes on causal judgments.

• Critical Disability Studies
• Disablism
• Ableism
• +۱۳ مورد دیگر

Professor Dan Goodley is a leading academic in Critical Disability Studies at the University of Sheffield , affiliated with the School of Education and co-director of the iHuman research center. His work bridges critical psychology , medical sociology , and posthuman theory to challenge ableist norms in education, healthcare, and society. He has secured major grants, including a £2.9m Wellcome Trust Discretionary Award and multiple ESRC-funded projects, focusing on themes like disablism , social justice , and inclusive research methodologies . Research Themes : Critical Disability Theory, Posthumanism, Dis/ability and Technology, Decolonizing Disability, Austerity and Dis/ability, Co-Production with Marginalized Communities. Grants : Wellcome Trust, ESRC, EPSRC, Research England, European Social Fund. Professional Roles : Visiting Professor at University of Ghent, Editorial Board Member for multiple journals, ESRC Peer Review College. His recent publications interrogate the intersections of disability , pandemic ethics , and autonomous technologies , often employing co-produced and participatory frameworks. He advocates for disabled voices in research and policy, emphasizing resilience and decolonizing praxis in global contexts.

Sam Kirshnerمشاهده پروفایل

دانشیار

• Behavioral Decision Making
• Operations Management
• Technology Management
• +۶ مورد دیگر

Associate Professor Sam Kirshner is a faculty member at the University of New South Wales within the School of Information Systems and Technology Management . His research focuses on behavioral decision making , algorithmic impact on operations , and artificial intelligence applications in business contexts. PhD in Management Science from Queen’s University, Canada Teaching expertise in data visualization, predictive analytics, and AI ethics Co-author of Business Analytics: A Management Approach Member of the Ethical AI Advisory His research explores how psychological distance and construal level theory influence decisions in supply chains, technology management, and consumer behavior. Recent work examines ChatGPT's decision biases , algorithm aversion , and sustainable operations under financial constraints. Key publication trends show focus areas: AI ethics and human-AI collaboration Behavioral supply chain analysis Temporal/spatial psychological distance effects CO2 forecasting with sparse data Consumer behavior in digital platforms Virtual reality and cognitive processing Supervision roles include mentoring 2 PhD students and 6 honors students, contributing to the next generation of scholars in business analytics and technology management.

• Health Policy
• Medical Sociology
• Disease Advocacy
• +۳ مورد دیگر

Rachel Best is an Associate Professor and Director of Graduate Studies in the Department of Sociology at the University of Michigan. Her research focuses on the intersections of politics, culture, inequality, and health, with a particular emphasis on disease advocacy, disability discrimination, and the sociological implications of medical policy. She directs the Sociology graduate program and leads computational studies on disease stigma, advocacy strategies, and ADA litigation outcomes. Her work bridges medical sociology, legal studies, and public health, addressing how societal structures shape health outcomes and policy responses. Her research interests include analyzing how disease campaigns influence health policy, the political consequences of overestimating individual health control, and the role of stigma in disability rights litigation. Notable projects use computational methods to trace policy advocacy impacts and explore visibility dynamics in disability cases. Recent publications (2022–2025) highlight her focus on disease stigma’s societal effects, legal interpretations of invisible disabilities, and the evolving nature of advocacy in health policy. Her earlier works, such as Common Enemies: Disease Campaigns in America , critique single-disease advocacy frameworks and their unintended policy consequences. Rachel Best advises on graduate studies and collaborates with interdisciplinary teams. Her research has been supported by grants focusing on sociological methods in health policy analysis. She is affiliated with the University of Michigan’s Sociology Department and the LSA College, contributing to discussions on inequality and institutional sociology.

Rodrigo Venturaمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +۴ مورد دیگر

Rodrigo Ventura is an Associate Professor at the Department of Electrical and Computer Engineering, Instituto Superior Técnico (IST), University of Lisbon. He is also a senior researcher at the Institute for Systems and Robotics (ISR-Lisbon), leading the Space and Aeronautics thematic line. His research focuses on the intersection of Robotics and Artificial Intelligence, emphasizing human-robot interaction, space robotics, and cognitive architectures. He coordinates the Minor in Space Sciences and Technologies at IST and the MBE on Space Systems for Tecnico+. As Adjoint Faculty at the International Space University (ISU), he contributes to global academic initiatives. His work includes experiments on the International Space Station and participation in analog space missions. Research interests span biologically inspired systems, machine learning, and teleoperation interfaces. Recent publications address reinforcement learning for UAVs, microgravity experiments, and pseudo-haptic feedback for robotic control. He teaches subjects like Artificial Intelligence and Decision Systems, Satellite Engineering, and Autonomous Systems.

Fei Fangمشاهده پروفایل

دانشیار

• Machine Learning
• Multi-Agent Systems
• AI for Social Good
• +۳ مورد دیگر

Fei Fang is an Associate Professor in the Software and Societal Systems Department (S3D) at Carnegie Mellon University's School of Computer Science. Their research focuses on the intersection of machine learning and multi-agent systems, aiming to leverage AI for Social Good. Recent work explores multi-agent reinforcement learning combined with large language models. Fei Fang teaches the course "Demystifying AI for Everyone: Concepts and Applications" (Fall 2025), designed for non-technical students. The course covers AI fundamentals, including machine learning, natural language processing, and computer vision, while addressing ethical, societal, and economic implications. Contact: feifang@cmu.edu | Office: 321 TCS Hall

• Human-Computer Interaction
• Computer Mediated Communication
• Personal Information Management
• +۱۱ مورد دیگر

Steve Whittaker is Professor of Human-Computer Interaction at the University of California at Santa Cruz. He conducts interdisciplinary research at the intersection of social science and computer science, focusing on how technology affects human memory, communication, and personal information management. His current research explores human-centric AI systems, mental health technologies, and digital identity. His research interests center on designing interactive systems that support human needs in digital environments. He investigates how people manage digital information, remember personal experiences through lifelogging, and interact with conversational agents and social robots. His work emphasizes computational well-being, affective computing, and the social implications of technology use. He has made foundational contributions to the fields of personal information management (PIM), computer-mediated communication (CMC), and human-robot interaction. The recent publications reflect a strong trend toward mental health technology, human-AI interaction, and digital well-being. His work spans from theoretical models of emotion and memory to practical systems for mental health apps, chatbots, and immersive visualization. He frequently publishes in top-tier venues such as CHI, CSCW, and IUI, often in collaboration with researchers across disciplines. Lifetime Research Achievement Award from SIGCHI Fellow of the Association for Computational Machinery (ACM) Member of the CHI Academy Lasting Impact Award from ACM CSCW Best Paper Award at CSCW10 Best Paper Award at CHI07 Honourable Mention at ACM CHI 2020 Multiple best paper nominations at CHI, CSCW, and IUI MIT Siegel Prize Steve Whittaker has supervised numerous PhD and Master’s students, though specific names are not listed in the provided text. His research has been funded by major grants from NSF, NIH, and industry partners, enabling long-term studies on digital behavior and system development. He is Editor of the journal Human Computer Interaction and has authored over 200 peer-reviewed publications. His most recent book, The Science of Managing Our Digital Stuff (MIT Press), co-authored with Ofer Bergman, synthesizes decades of research on personal information management. He leads a vibrant research lab at UC Santa Cruz that focuses on human-centered computing, where students and collaborators work on projects involving AI, mental health, digital memory, and social interaction. The lab has produced influential work on lifelogging, email management, telepresence robots, and algorithmic transparency. The team employs mixed methods, combining qualitative studies with system design and evaluation.

Carolyn Parkinsonمشاهده پروفایل

دانشیار

• Social Neuroscience
• Affective Neuroscience
• Social Psychology
• +۴ مورد دیگر

Carolyn Parkinson is an Associate Professor at the University of California, Los Angeles (UCLA), holding the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair in Cognitive Neuroscience. Her research integrates social psychology with computational neuroscience to explore how the human brain represents, navigates, and shapes social environments. University: University of California, Los Angeles (UCLA) Academic Rank: Associate Professor Research Focus: Social and Affective Neuroscience, Social Network Analysis, Neural Mechanisms of Psychological Distance At the Computational Social Neuroscience Lab , Parkinson investigates: Neural encoding of social network structures Shared mechanisms for spatial, temporal, and social distance perception Computational modeling of social cognition Functional MRI analysis of social relationships Her work reveals that: Resting-state brain connectivity predicts social proximity Multivoxel patterns decode social knowledge representations Old cortical structures repurpose spatial processing for social cognition Neural population coding transcends historical phrenology-based approaches Notable awards include the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair. She employs machine learning and social network theory to analyze distributed brain activity patterns, advancing understanding of human social behavior and cognition.

Sebastian Rudolphمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Description Logics
• +۷ مورد دیگر

Prof. Sebastian Rudolph is a Professor of Computational Logic at the Institute for Artificial Intelligence , Faculty of Computer Science , TU Dresden. Since 2021, he has been an Affiliate Member of the Faculty of Mathematics. His research spans theoretical and applied artificial intelligence, focusing on Knowledge Representation and Reasoning through formalisms like Description Logics, Existential Rules, and Formal Concept Analysis, with applications in Semantic Technologies. 2017 : ERC Consolidator Grant for decidability principles in logic-based knowledge representation 2006-2013 : Postdoctoral researcher, project leader, and Privatdozent at KIT's Institute AIFB 2011 : Habilitation at KIT Earlier : PhD in Algebra and teaching qualification in mathematics, physics, and computer science at TU Dresden His recent publications address decidability of logical reasoning, non-monotonic extensions in formal concept analysis, standpoint logics, and multiagent systems. He supervises the DeciGUT and KIMEDS projects, and is involved in the SECAI and ScaDS.AI centers. Teaching activities include courses on Theoretical Computer Science, Existential Rules, and Formal Concept Analysis.

Marc Juarez Miroمشاهده پروفایل

مدرس

• Cyber Security
• Privacy
• Machine Learning Security
• +۷ مورد دیگر

Marc Juarez Miro is a Lecturer in Cyber Security and Privacy at the School of Informatics, University of Edinburgh. He is a member of the Security, Privacy, and Trust (SecPrivTru) research group, and affiliated with the Security and Privacy Research Institute and the Laboratory for Foundations of Computer Science. His research lies at the intersection of cybersecurity, privacy, and machine learning. Key areas include ML-based traffic analysis , security and privacy of machine learning models , and fairness in private learning systems . He investigates both theoretical and practical aspects of privacy-preserving technologies, including watermarking in generative AI and defenses in anonymity networks like Tor. Recent publications in venues such as USENIX Security, PETS, and SaTML highlight his work on vulnerabilities in watermarking schemes, fairness in differentially private ML, and traffic analysis mitigation. These works reflect a strong trend toward auditing and improving the trustworthiness of AI and privacy systems. Google Research Scholar Award in Security (2024) PETS Student Paper Award He actively supervises PhD and Master’s students, including Kai Yao and Lisa Lavrentieva, and has secured competitive seed funding such as the GAIL grant for research on undetectable watermarks in generative AI. His advising focuses on privacy, security, and ethical AI. Marc leads and co-organizes research initiatives such as a workshop on watermarking for generative AI and contributes to open-source tools like wfpadtools and dispa-plugin, indicating strong engagement with both theoretical and applied aspects of privacy engineering.

Damir Filipovicمشاهده پروفایل

استاد

• Quantitative Finance
• Risk Management
• Machine Learning
• +۷ مورد دیگر

Academic Profile: Damir Filipovic is a Full Professor and the Swissquote Chair in Quantitative Finance at the College of Management of Technology (CDM) of École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He previously held academic positions at the University of Vienna, University of Munich, and Princeton University, and served as Head of the Vienna Institute of Finance. Research Focus: Quantitative finance, risk management, stochastic processes, term structure modeling, volatility risk, and machine learning applications in financial markets. Industry Collaboration: Co-developed the Swiss Solvency Test for insurance capital requirements while consulting for the Swiss Federal Office of Private Insurance. Publications: Contributed extensively to journals like Journal of Financial Economics, Mathematical Finance, and Annals of Applied Probability, with a textbook on Term-Structure Models. Academic Service: Editorial board member of multiple journals and organizer of advanced workshops on systemic risk and financial technology. Recent Research: His work emphasizes machine learning for portfolio risk management, kernel-based yield curve estimation, and robust stochastic modeling. Keynote speaker at international conferences on finance and insurance mathematics, with over 15 recent publications in 2023-2025 addressing high-dimensional financial problems, neural control systems, and causal inference in market data. Education: Ph.D. in Mathematics from ETH Zurich (2000). Graduate of ETH Zurich and University of Vienna. Teaching & Mentorship: Supervises current and former EPFL Ph.D. students in quantitative finance, including Nicolas Camenzind, Joshua Hayes, Andrea Ruglioni, and ten others. Former students like Damien Ackerer and Lotfi Boudabsa now lead research in risk management. Labs & Programs: Directs EPFL's Finance and Technology Programme, leads the Computational Finance Group (CSF) at EPFL, and contributes to Swiss Finance Institute initiatives. Scientific Leadership: Served on EPFL Committee of Academic Evaluation and Doctoral Program Finance committee.