جست‌وجوی استاد و پژوهشگر

Britt Holbrookمشاهده پروفایل

دانشیار

• Science Policy
• Research Ethics
• Academic Freedom
• +۷ مورد دیگر

Britt Holbrook is an Associate Professor in the Department of Humanities and Social Sciences at New Jersey Institute of Technology (NJIT). His work focuses on science policy, research ethics, and the societal impact of academic activities. He holds a Ph.D. in Philosophy from Emory University (2004), an M.A. in Philosophy from Emory University (1997), and a B.A. in Philosophy with honors from Sewanee, The University of the South (1992). Dr. Holbrook’s research explores the intersection of academic values, science policy, and interdisciplinary collaboration. Key areas include the ethics of peer review, the broader impacts of research, and the role of philosophy in shaping science governance. He critically examines issues like open science, academic freedom, and transformative research frameworks. His work often bridges theoretical philosophy with practical policy implications. Recent publications highlight debates on replication studies, the basic-applied research distinction, and engineering ethics for social justice. He advocates for reforms in scholarly publishing and research evaluation to enhance transparency and societal benefit. Holbrook’s contributions emphasize ethical responsibility in academia and the need for interdisciplinary dialogue to address contemporary challenges in science and education. His website jbrittholbrook.com provides additional insights into his research and teaching activities.

• Intelligent Interactive Systems
• Behavioral Research at Scale
• Design for Equity and Social Justice
• +۳ مورد دیگر

Krzysztof Gajos is a Gordon McKay Professor of Computer Science at the Harvard Paulson School of Engineering and Applied Sciences, leading the Intelligent Interactive Systems Group. His research focuses on principles of intelligent interactive systems, tools for large-scale behavioral research (e.g., LabintheWild.org), and design for equity/social justice. He holds a PhD from the University of Washington and degrees from MIT, with postdoctoral work at Microsoft Research. Education: PhD (University of Washington), M.Eng & B.Sc (MIT) Affiliations: ACM Transactions on Interactive Intelligent Systems (former co-editor-in-chief), General Chair of ACM UIST 2017 Research spans accessible computing, creativity tools, and health informatics. Recent work emphasizes ethical AI, human-AI collaboration, and systems that empower marginalized communities. Awards include the Sloan Fellowship and impactful paper recognitions at CHI, IUI, and COMPASS. Grants: Federal grants supporting PhD students; current focus on mitigating disruptions caused by grant terminations Lab: IIS Group develops systems that balance technical innovation with societal impact

Kristofer Reyesمشاهده پروفایل

دانشیار

• Applied Mathematics
• Computational Chemistry
• Materials Science
• +۶ مورد دیگر

Kristofer Reyes is an Associate Professor in the Department of Materials Design and Innovation at the University at Buffalo (School of Engineering and Applied Sciences). His research focuses on computational and statistical methods applied to materials science, particularly in developing machine learning frameworks for small-data regimes. He leads the Computational and Statistical Material Science (CSMS) Lab, which emphasizes Bayesian models, reinforcement learning, and fusion of physics-based knowledge. Education: PhD in Applied and Interdisciplinary Mathematics, University of Michigan, 2013 BS in Computer Science and Mathematics, Purdue University, 2004 Research Interests: Reyes' work bridges computation, mathematics, and materials science. Key areas include: - Autonomous experimentation systems (e.g., self-driving fluidic labs) - Bayesian optimization and decision-making under uncertainty - Machine learning for nanomaterials synthesis (e.g., perovskite nanocrystals) - Integration of physics-informed models in AI workflows - High-cost experimental design optimization Recent Achievements: SMARTDOPE paper awarded 'Best in Advanced 2023' Developed AlphaFlow for autonomous chemical synthesis Pioneered 'self-driving labs' for materials discovery Labs & Teams: CSMS Lab (134 Bell Hall) focuses on problem-fluent models for materials research. Current projects include quantum circuit optimization, bio-chemical pathway modeling, and sustainable nanomanufacturing. Collaborates with industry and national labs on AI-driven materials development.

Fuyuan Zhangمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Cybersecurity
• Formal Methods
• +۷ مورد دیگر

Fuyuan Zhang is a Postdoctoral Researcher at the Max Planck Institute for Software Systems, specializing in advanced software testing methodologies and formal verification techniques. His research focuses on improving the reliability and security of AI systems, quantum computing frameworks, and concurrent systems through innovative testing criteria, adversarial attacks, and compositional reasoning. Key areas of expertise include: Large Language Model (LLM) testing and validation Quantum program analysis and security Adversarial machine learning and neural network robustness Formal verification of concurrent and cyber-physical systems Automated bug detection in complex software systems His work bridges theoretical foundations with practical applications, addressing critical challenges in AI safety, quantum software reliability, and system-wide security certification.

Amélie Marianمشاهده پروفایل

استاد

• Data Management
• Algorithms
• Accountability of Decision-making Systems
• +۷ مورد دیگر

Amélie Marian is a Professor in the Department of Computer Science at Rutgers University. She maintains an active research program with numerous recent publications and research projects. Her office is located in CoRE 324 on the Busch Campus, and she can be reached at amelie.marian@rutgers.edu or by phone at (848) 445-8324. Dr. Marian's primary research interests focus on Data Management and Algorithms, with specific emphasis on Accountability and Transparency of Algorithms for Decision-Making, Explainable Rankings, Personal Information Management, Data Integration, and Data Corroboration. Her work bridges theoretical computer science with practical applications in decision systems, personal data management, and privacy-preserving technologies. She leads several major research initiatives including YourDigitalSelf (connecting, searching, and understanding personal digital traces), Explainable Rankings (toward transparent ranking functions), and Decentralized Collaborative Filtering (privacy-aware personal recommendations). Analyzing her recent publications reveals a clear trajectory toward increasingly important societal challenges in algorithmic transparency and accountability. Her work spans technical aspects of database systems and information retrieval while addressing critical social implications of algorithmic decision-making. The research shows strong interdisciplinary connections between computer science, social choice theory, human-computer interaction, and public policy. Microsoft Live Labs Award (2006) Google Research Awards (2008, 2010, 2012) NSF CAREER award (2009) NSF MCA Grant Award for Transparent and Accountable Decision Systems (2022) Multiple Google Research Awards for projects including Remembrance of Data Past and PERSEUS Dr. Marian actively mentors graduate students including PhD candidates Yehuda Gale and Shuchang Liu, and MS student Shuyuan Xu. Her research has been supported by significant grants including multiple NSF awards (NSF-SES 2218975, NSF-IIS 0844935, BCS-CDI-Type I 1027801), Google Research Awards, and Microsoft funding. She leads the YourDigitalSelf research group focused on personal information management systems and has established collaborative projects with researchers across multiple institutions.

Kristof Coussementمشاهده پروفایل

استاد

• Deep Learning
• Machine Learning
• Text Mining
• +۳ مورد دیگر

Kristof Coussement is a Full Professor and Academic Director of the MSc in Big Data Analytics for Business at IÉSEG School of Management. He holds a HDR in Business Administration from University of Paris Dauphine and Ph.D. in Applied Economics from Ghent University. He directs the IESEG Center for Marketing Analytics (ICMA). His research focuses on big data analytics, machine learning applications in marketing, and explainable AI. He develops advanced analytical frameworks for customer behavior prediction, financial forecasting, and algorithmic decision-making. Coussement's recent work shows strong emphasis on ethical AI development, algorithmic bias mitigation, and industry-specific language modeling. His publications increasingly address the intersection of AI technology and business decision-making processes.

Luke Sanfordمشاهده پروفایل

استادیار

• Environmental Policy
• Political Institutions
• Remote Sensing
• +۵ مورد دیگر

Luke Sanford is an Assistant Professor of Environmental Policy and Governance at Yale School of the Environment with a secondary appointment in Political Science. His research examines how political institutions shape environmental policymaking, particularly the relationship between public preferences and policy outcomes, alongside spatial and temporal distributional impacts of natural resource decisions. His educational background includes: Ph.D. in Political Science and International Affairs from University of California San Diego M.A. in Political Science from University of California San Diego, School of Global Policy and Strategy B.A. in Politics from Whitman College Sanford specializes in integrating digital data methodologies—including satellite imagery and text analysis—with environmental policy research. His work bridges political institutions, remote sensing, machine learning, economic development, and causal inference to measure policy preferences and outcomes. He develops innovative techniques for analyzing deforestation patterns, air pollution disparities, and carbon market effectiveness. Recent publications reveal a pronounced shift toward data-intensive environmental governance research, with increasing emphasis on satellite-driven spatial analysis and machine learning applications. His 2021-2025 work demonstrates methodological innovation in causal inference using remote sensing, particularly in deforestation monitoring, air pollution justice, and jurisdictional climate initiatives like REDD+. Sanford is affiliated with The Forest School and Yale Institute for Biospheric Studies, teaching courses including ENV 821a Environmental Policymaking: From Local to Global. He will be on leave during Spring 2026 semester.

Matthew Kopecمشاهده پروفایل

مدرس

• Ethics in Technology
• Computer Science Education
• Social Media Ethics
• +۳ مورد دیگر

Matthew Kopec is a Program Director and Lecturer at Harvard University's Embedded EthiCS program, which integrates ethics into computer science education. He holds an MA from Virginia Tech (supervised by Joe Pitt) and a PhD from the University of Wisconsin-Madison (supervised by Elliott Sober). Previously, he taught at Northeastern, Australian National University, Northwestern, and the University of Colorado-Boulder. His research focuses on the ethical implications of computing technologies, including content moderation on social media, algorithmic predictions' societal impacts, and tech ethics education efficacy. Education: PhD in Philosophy, University of Wisconsin-Madison MA in Philosophy, Virginia Tech Research Interests: Kopec explores normative dimensions of technology, such as misinformation governance, big tech regulation, and ethical design in computational systems. His work bridges philosophy and computer science, emphasizing practical applications of ethical frameworks in education and policy. Recent Research Trends: Kopec's publications (2021–2023) highlight empirical studies on ethics education in CS curricula, experimental approaches to moral psychology, and the governance of social media platforms. His work underscores interdisciplinary collaboration between ethics, technology, and policy. Awards: None explicitly mentioned in the provided texts. Advising & Grants: No specific details on advisees or grants are provided here. Labs/Teams: Central to his role is the Embedded EthiCS program, which collaborates across Harvard's CS departments to embed ethical modules into technical coursework.

Samuel Dahanمشاهده پروفایل

دانشیار

• Legal AI
• Dispute Resolution
• Global Work
• +۴ مورد دیگر

Samuel Dahan is an Associate Professor at Queen’s University Faculty of Law and Director of the Conflict Analytics Lab. He holds visiting faculty positions at Cornell University, Paris Dauphine University, ENA, and Harvard University. His expertise spans Legal AI, Dispute Resolution, and Global Work, with a focus on open-source platforms like OpenJustice and the Deel Lab for global employment policy. Education: MA: Sorbonne-Ecole Normale Supérieure Ulm LLM: Katholieke Universiteit Leuven PhD: University of Cambridge Research Interests: Dahan’s work integrates data science with legal challenges, including AI-driven legal tools, conflict resolution analytics, and global workforce compliance. He leads initiatives like OpenJustice, an open-source platform with over 20,000 monthly queries, and the Deel Lab for HR tech innovation. Notable Achievements: Secured $1.1M in grants (NSERC-MITACS Partnership). Published in top venues: AAAI, ICML, McGill Law Journal. Keynote speaker at the French Supreme Court Hearing, Stanford Codex, and Law Society of Ontario. Labs & Teams: Directs the Conflict Analytics Lab at Queen’s University and co-leads the Deel Lab. His teams develop tools like the Deel AI Classifier and MyOpenCourt, addressing legal challenges through data-driven solutions.

• Service-Oriented Architectures
• Cloud Computing
• Data Management
• +۷ مورد دیگر

Professor Kyriazis Dimosthenis holds a faculty position at the Department of Digital Systems, University of Piraeus. He earned his diploma in Electrical & Computer Engineering from the National Technical University of Athens (2001) and a cross-disciplinary MSc in Techno-Economic Systems (2004). His academic rank is Professor specializing in service-oriented architectures with a focus on quality of service and workflow management. He has led European projects like BigDataStack, CrowdHEALTH, and CYBELE, addressing challenges in cloud computing, edge computing, and AI-driven solutions for healthcare, finance, and industrial sectors. His research emphasizes resilient service-oriented systems, AI explainability, and human-centric digital transformation. Notable contributions include frameworks for dynamic resource allocation in hybrid cloud/edge environments, AI applications for maritime safety, and data governance solutions for cross-sector integration. He coordinates initiatives such as the Future Internet Architecture Board and Cloud QoS&SLAs, driving advancements in federated data marketplaces and sustainable computing practices. His recent work explores Large Language Model (LLM) applications in financial decision-making, conversational AI for MLOps, and neurosymbolic systems for defect detection. He also investigates XAI methodologies, including VirtualXAI, which leverages GPT-generated personas for explainability assessment. His projects often bridge technical innovation with societal impact, such as the iHELP platform for holistic health records and SmartCHANGE for behavioral change strategies in youth health. Key themes in his publications include bias mitigation in machine learning, dynamic deployment prediction in hybrid cloud settings, and energy-efficient data spaces for mobility. He has contributed to standards like the H2020-funded IRMOS and 5GTANGO, emphasizing interoperability and fault-tolerant architectures. His work frequently intersects with EU policy frameworks, particularly in data governance and ethical AI implementation.

Elena Espositoمشاهده پروفایل

استاد

• Communication theory
• Systems theory
• Digital communication
• +۵ مورد دیگر

Elena Esposito is a Full Professor at the Department of Political and Social Sciences, University of Bologna, and at the Faculty of Sociology, University of Bielefeld. She holds the scientific-disciplinary sector GSPS-06/A (Sociology of cultural and communicative processes). Her work bridges systems theory, digital communication, and algorithmic futures, with a focus on artificial intelligence, prediction mechanisms, and media sociology. She has received prestigious fellowships from institutions like the ERC, Wissenschaftskolleg Berlin, and Columbia University. PhD in Sociology (1990, University of Bielefeld) Habilitation (2001, University of Bielefeld) National Scientific Qualification (2013, Italy) Degree in Philosophy (1987, University of Bologna, summa cum laude) Degree in Sociology (1983, University of Bologna, summa cum laude) Esposito's research spans algorithmic prediction, artificial communication, digital media, and systems theory. Her work examines how algorithms shape social intelligence in insurance, medicine, and policing, the paradoxes of contingency in financial markets, and the societal implications of virtuality. She connects Niklas Luhmann's theoretical frameworks to contemporary issues like AI ethics and pandemic-era social systems. Her recent publications emphasize AI's role in constructing unpredictable futures, the social management of algorithmic opacity, and the transformation of risk perception in digital societies. She has authored 13 books and over 100 peer-reviewed articles, exploring topics from media memory to financial forecasting. ERC Advanced Grant (2018): €2.08M for algorithmic prediction studies Volkswagen Foundation Grant (€1.5M) for U3B project Leverhulme Trust funding for international network on value performances Esposito serves on editorial and advisory boards for journals like Sociologica and organizations including the Weizenbaum Institute. She directs the FAIR project on AI implications and co-leads initiatives like DEMOPE (Democracy under Pressure) and CRC 1567 on Virtual Worlds.

Karolina Drobotowiczمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Public Sector Technology
• Ethical AI
• +۳ مورد دیگر

Karolina Drobotowicz is a Doctoral Researcher in the Department of Computer Science at Aalto University, affiliated with the School of Science. Her work focuses on the design and ethical implications of AI services in the public sector, emphasizing inclusivity, civic empowerment, and trustworthy technology implementation. She holds a Master's in Engineering and Technology from Aalto University (2020) and dual Bachelor's degrees in Engineering and Technology, and Control Engineering and Robotics from Gdańsk University of Technology (2016). Her research explores practitioners' and citizens' perspectives on AI adoption in public services, addressing challenges in algorithmic fairness, public trust, and equitable access. Key contributions include studies on Finnish public sector AI governance and co-design methodologies for citizen-centric AI solutions. Active in interdisciplinary projects like CAAI (Citizen Agency in AI), she investigates democratizing algorithmic services in urban environments. Her work aligns with UN Sustainable Development Goals related to quality education and innovation. Recent activities include organizing public workshops on AI in the public sector and presenting at international conferences on topics such as LLM-powered decision systems and civic empowerment through technology.

Zoë Waltersمشاهده پروفایل

دانشیار

• Epigenetics and Genomics
• Cancer Biology
• Target Prioritisation and Validation
• +۳ مورد دیگر

Dr. Zoë Walters is an Associate Professor in Translational Epigenomics at the University of Southampton, affiliated with the Faculty of Medicine and Cancer Sciences department. She leads the MSc Genomics program's Genomics Guided Treatment and Dissertation modules and contributes to BMedSci teaching. Her research focuses on epigenetic mechanisms in cancer and developmental disorders, particularly targeting therapies for pediatric cancers like neuroblastoma and rhabdomyosarcoma. She collaborates on projects addressing therapy resistance, tumor microenvironment dynamics, and precision medicine approaches. Current research includes investigating EZH2 inhibitors in combination therapies, leveraging omic data for sarcoma treatment, and understanding mechanisms of therapeutic resistance. She has received awards such as the Norman Williams Prize (2024) and Young Investigator Award (2023). Her lab also explores AI applications in clinical decision-making for oesophageal cancer. Zoë has supervised numerous PhD students and contributed to over 10 peer-reviewed publications. She serves on editorial boards (e.g., Frontiers in Cell and Developmental Biology) and reviews for journals like Nature Communications and Clinical Epigenetics. Her work spans interdisciplinary collaborations, including with engineering and computer science teams for AI-driven oncology solutions.

Theo Araujoمشاهده پروفایل

استاد

• Automated Decision-Making
• Digital Society
• Conversational Agents
• +۴ مورد دیگر

Prof. Theo Araujo is a Full Professor of Media, Organisations and Society at the University of Amsterdam's Department of Communication Science, and Scientific Director of the Amsterdam School of Communication Research (ASCoR). He leads the Digital Data Donation Infrastructure (D3I) consortium, co-directs the Trust in the Digital Society research priority area, and is a senior researcher in the Public Values in the Algorithmic Society (AlgoSoc) program. His research focuses on AI's societal impacts, computational social science methodologies, and data donation frameworks. Key roles include coordinating multi-university initiatives and advising on digital ethics. Research interests emphasize automated decision-making, conversational agents, and digital inequality. He has pioneered tools like the Conversational Agent Research Toolkit and OSD2F framework. His work bridges communication science with computational methods, addressing challenges in data collection, algorithmic transparency, and human-AI interaction. Recent studies explore chatbot persuasion mechanisms, public trust in AI systems, and cross-cultural consumer behavior. He has published extensively on brand engagement, media analytics, and the ethical implications of automated systems. Current projects include smart speaker data donation studies and hybrid methods for health communication research. Grants and collaborations involve EU-funded initiatives and partnerships with Dutch universities. His lab work focuses on developing ethical AI applications and improving digital trace data methodologies. Future directions include advancing participatory data donation practices and mitigating algorithmic biases in automated decision-making systems.

Johannes Peter Wallnerمشاهده پروفایل

دانشیار

• Knowledge Representation and Reasoning
• Artificial Intelligence
• Argumentation
• +۷ مورد دیگر

Johannes Peter Wallner is an Associate Professor at Graz University of Technology (TU Graz), working in the Institute of Software Engineering and Artificial Intelligence within the Faculty of Computer Science and Biomedical Engineering. He leads the Knowledge Representation and Reasoning (KRR) research group and has previously been a researcher at TU Wien's DBAI group and the Constraint Reasoning and Optimization group at the University of Helsinki. Dr. Wallner's research focuses on knowledge representation and reasoning, artificial intelligence, argumentation, abduction, belief change, inconsistency handling and measurement, computational social choice, computational complexity, Boolean satisfiability, and answer set programming. His work bridges theoretical foundations with practical applications, particularly in developing computational models for argumentation systems. He has made significant contributions to structured argumentation frameworks, including assumption-based argumentation and ASPIC+. His recent publications demonstrate a strong trend toward advancing algorithmic approaches to probabilistic argumentation, abstraction techniques in argumentation systems, and applications of argumentation in domains like healthcare. He has been particularly active in exploring the computational complexity of various argumentation semantics and developing efficient algorithms for reasoning tasks. Dr. Wallner has received multiple prestigious awards including being selected for the IJCAI 2024 Early Career Track (only 12 researchers globally selected), being named a Top Scholar by ScholarGPS in 2024 (top 0.5% worldwide in AI), and receiving the AI 2000 Most Influential Scholar Honorable Mention in Knowledge Engineering in 2021 and 2022. As Principal Investigator, Dr. Wallner has secured significant research funding from the Austrian Science Fund (FWF), including two major projects: "A Novel Computational Workflow for Argumentation in AI" (grant P 35632, 358,848 €) and "Extending Belief Change to Advance Dynamics in Argumentation" (grant P30168-N31, 353,438 €). He is highly active in the academic community, serving on program committees for major AI conferences including AAAI, IJCAI, KR, and ECAI, and was a member of the Program Committee Board of IJCAI (2022-2024). He leads the Knowledge Representation and Reasoning (KRR) research group at TU Graz, which develops both theoretical foundations and practical implementations for computational argumentation systems. The group has contributed to several software systems including CEGARTIX (a SAT-based argumentation system), Vispartix (visualization of argumentation frameworks), ADFsys (an ASP-based argumentation system for abstract dialectical frameworks), and others that implement various argumentation frameworks.