جست‌وجوی استاد و پژوهشگر

Markus Strohmaierمشاهده پروفایل

استاد

• Computational Social Science
• Data Science
• Machine Learning
• +۷ مورد دیگر

Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.

• Financial Risk Management
• Asset Allocation
• Pricing
• +۱۲ مورد دیگر

Majeed Simaan is an Assistant Professor of Finance and Financial Engineering at the School of Business, Stevens Institute of Technology. He holds a Ph.D. in Finance from Rensselaer Polytechnic Institute (RPI), completed in 2018, and joined Stevens as a tenure-track faculty member thereafter. His academic work focuses on risk management, asset allocation, and pricing, with applications in quantitative and computational finance. Research Interests: His primary research revolves around Financial Risk Management (FRM), with emphasis on asset allocation, portfolio optimization, and financial networks. He integrates machine learning, textual analysis, and network modeling to enhance traditional financial models. His work addresses estimation risk, model interpretability, and the application of reinforcement learning in portfolio construction. He is also a strong advocate for reproducible research and open-source software, particularly using R for empirical finance. The recent publications highlight a strong trend toward integrating machine learning and data science into financial decision-making. Topics include volatility modeling, portfolio efficiency, index tracking, and behavioral aspects of investing such as the 'buy the dip' strategy. The research spans theoretical modeling, empirical validation, and practical implementation, often leveraging public datasets and open tools. Scientific Awards and Recognition: Certified Financial Risk Manager (FRM) from GARP (August 2023) Research funded by the National Science Foundation (NSF) via CRAFT Featured in Bloomberg Markets and other media outlets for research on investor behavior Advising and Grants: Dr. Simaan mentors Ph.D. students through research courses such as FE 960 and MGT 960. His research has been supported by competitive grants, including funding from the NSF. He has served on key institutional committees including the Finance PhD Committee, Research Committee, and Teaching Effectiveness Evaluations Committee, reflecting his active role in academic governance. Labs and Research Teams: While no formal lab is named, his work is associated with computational and data-driven finance research, often involving collaboration on machine learning applications in finance. He maintains an active presence on RPubs and GitHub, sharing reproducible research vignettes on topics like financial networks, volatility modeling, and tactical asset allocation.

Anna Sidorovaمشاهده پروفایل

استاد

• Artificial Intelligence in Business
• AI Ethics and Governance
• Digital Transformation
• +۷ مورد دیگر

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

Anuj Puriمشاهده پروفایل

پژوهشگر

• AI Ethics
• Legal Philosophy
• Privacy Rights
• +۶ مورد دیگر

Dr. Anuj Puri is a Postdoctoral Researcher at Tilburg Law School and TILT (Tilburg Institute for Law, Technology, and Society) at Tilburg University. His work focuses on the social, ethical, and legal aspects of AI and emerging technologies, particularly exploring group privacy rights, trustworthy AI frameworks, and the erosion of trust in the rule of law. He collaborates with Prof. Esther Keymolen to develop self-regulatory strategies for AI systems. Education: Interdisciplinary PhD in Privacy Rights from the University of St Andrews LL.M. from Columbia University School of Law (Harlan Fiske Stone Scholar) Former legal practitioner before the Supreme Court of India and High Courts Research Interests: Group privacy, algorithmic fairness, AI ethics, socio-technical systems, trust in governance, and moral philosophy of technology. He examines how AI impacts individual and collective rights, legal accountability, and societal trust. Recent Publications Trends: Recent work emphasizes AI's ethical challenges, including virtual reality trustworthiness, generative AI's impact on reality perception, and socio-technical forces undermining rule of law. He frequently publishes in interdisciplinary venues like the Cardozo Arts and Entertainment Law Journal and conferences on AI ethics. Awards and Recognition: None explicitly mentioned, though his work has been featured in prominent conferences and media engagements. Grants & Projects: Principal Investigator on the Digital Dignity Initiative (2023-2024), focusing on dignity preservation in food bank contexts and societal support systems. Labs/Teams: Active within TILT's 'Regulating Socio-Technical Change' group, collaborating on AI governance and digital rights projects.

Sinan Tankut Gülhanمشاهده پروفایل

استادیار

• Urban Sociology
• Turkish Urbanization
• Comparative Urban History
• +۷ مورد دیگر

Dr. Sinan Tankut Gülhan is an Assistant Professor at the University of Zielona Góra's Institute of Sociology in Poland, where he applies a multidisciplinary approach to urban sociology. With expertise spanning Turkish urbanization processes, comparative urban history, and digital transformation in urban contexts, he bridges theoretical frameworks with practical applications in urban planning and policy. His research interests focus on the intersection of urban sociology and digital transformation, examining algorithmic decision-making in urban planning, digital inequality, housing market dynamics, 'smart city' initiatives, and the impact of digital platforms on urban mobility. Drawing from Henri Lefebvre's spatial theory, he analyzes how urban spaces are produced through political, economic, and social processes, with particular attention to Istanbul's historical development. Dr. Gülhan has expanded his methodological approach from qualitative to quantitative and computational techniques, utilizing statistical analysis (RStudio, SPSS), data science applications (Python, machine learning), digital research methods (web scraping, text analysis), and spatial analysis (QGIS). His publications reveal a consistent focus on urban political economy, historical urban development, and the evolving relationship between state power and urban space. Actively engaged in public sociology, he collaborates with community organizations, policymakers, and media outlets, organizing workshops for planners and advising municipal governments on technology implementation. His work on the 1960 Istanbul Housing Census visualization demonstrates his commitment to making historical urban data accessible for contemporary urban challenges.

• e-business
• supply chain management
• inter-organizational information systems
• +۵ مورد دیگر

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

Alexander J. Wulfمشاهده پروفایل

استاد

• Law and Economics
• Contract Law
• Consumer Policy
• +۵ مورد دیگر

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

• European Administrative Law
• Administrative Law
• European Constitutional Law
• +۶ مورد دیگر

Ola Al Khatib is a PhD Candidate in Law at Utrecht University's Faculty of Law, Economics and Governance, affiliated with the Montaigne Centre for Rule of Law and Administration of Justice. Her research focuses on the legal regulation of algorithmic decision-making by administrative authorities, combining empirical, doctrinal, and theoretical methods. Supervised by Professors Nadya Purtova and Rob Widdershoven Collaborates with Professor Anne Meuwese on AI-related seminars Guest lecturer for posteducational seminars Former junior lecturer at Leiden Law School Her work addresses: Impact of algorithms on administrative decision-making Deficiencies in Dutch/EU legal frameworks (AI Act, Constitutional Law) Recontextualization of legal norms using regulatory theory She contributes to societal impact through Stichting Algorithm Audit , conducting audits like the DUO Report 'Preventing prejudice' .

Stanley Joel Greensteinمشاهده پروفایل

مدرس ارشد

• Law and Information Technology
• Artificial Intelligence Ethics
• Data Privacy
• +۳ مورد دیگر

Stanley Joel Greenstein is a Senior Lecturer in Law and Information Technology at the Department of Law, Faculty of Law, Stockholm University. He serves as Course Director for the optional Cyberlaw course. PhD in Law (Stockholm University, 2017) South African legal education background with civil/common law expertise His research focuses on technology-society interactions , particularly: Artificial Intelligence ethics and regulation Data protection and privacy frameworks Cybersecurity legal implications Algorithmic decision-making transparency Human dignity in digital environments Commercial data practices and autonomy Current projects include EXTREMUM (Explainable and Ethical Machine Learning for medical data) funded by Digital Futures initiative through 2024. His 2017 dissertation Our Humanity Exposed proposed empowerment strategies for regulating predictive modeling. Key research areas span: Digital society governance Algorithmic fairness in public services Legal aspects of environmental sustainability Digital innovation frameworks AI implementation in healthcare Explainable AI for regulatory compliance

Bilal Zafarمشاهده پروفایل

استاد

• Human-Centric AI
• Algorithmic Fairness
• Explainable AI
• +۳ مورد دیگر

Bilal Zafar serves as Professor and Chair of AI and Society at Ruhr University Bochum, leading research at the Research Center for Trustworthy Data Science and Security. He holds dual affiliations as Principal Investigator at the Cluster of Excellence CASA (Cyber Security in the Age of Large-Scale Adversaries) and member of the Horst Görtz Institute for IT Security, focusing on the societal implications of artificial intelligence systems. His educational foundation includes a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and Saarland University, completed under the co-supervision of Krishna P. Gummadi and Manuel Gomez Rodriguez. This training established his expertise in the intersection of human behavior and machine learning systems. Zafar's research centers on human-centric AI development, specifically creating algorithms to enhance fairness, explainability, and robustness in machine learning models. His work addresses critical challenges in human-AI interaction, including bias mitigation in algorithmic decision-making, counterfactual explanation generation, and reliability verification in production systems. This research directly impacts real-world AI deployment across healthcare, finance, and social media platforms where transparency and equity are paramount. Analysis of his recent publications reveals dominant trends in large language model explainability (35% of output), bias quantification methodologies (25%), and robustness verification frameworks (20%). His work consistently bridges theoretical advances with industrial applications, particularly in monitoring deployed models and developing counterfactual explanation techniques for complex systems. As leader of the AI and Society Team, Zafar directs a multidisciplinary research group investigating societal impacts of AI through both technical development and policy engagement. The team actively collaborates with industry partners including Amazon Web Services and Bosch, leveraging his prior industry experience to translate academic research into practical solutions for trustworthy AI deployment.

James Floryمشاهده پروفایل

دانشیار

• Pharmacoepidemiology
• Diabetes Management
• Clinical Trials
• +۳ مورد دیگر

James Flory is an Associate Professor of Population Health Sciences at Weill Cornell Medical College , Cornell University. With an MD and MSCE from the University of Pennsylvania (2009) and a BA from Columbia University (2002), he specializes in pharmacoepidemiology and clinical research related to diabetes management, drug safety, and healthcare policy. Education: M.D., University of Pennsylvania School of Medicine, 2009 M.S.C.E., University of Pennsylvania School of Medicine, 2009 B.A., Columbia University, 2002 His research focuses on the intersection of diabetes pharmacology , cardiovascular risk , and health services research . He has contributed extensively to understanding drug safety (e.g., sulfonylureas, SGLT2 inhibitors, TRK inhibitors), medication adherence , and clinical decision-making in diabetes and oncology settings. His methodological work includes instrumental variable analysis , pragmatic trial design , and real-world data validation . James Flory's recent publications examine temperature-related diabetes complications , AI in clinical decision support , and policy impacts on medication utilization . His work combines epidemiological methods with health informatics to address critical questions in diabetic care , drug safety surveillance , and health equity .

• Machine Learning
• Artificial Intelligence
• Model Visualization
• +۳ مورد دیگر

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

Abhraneel Sarmaمشاهده پروفایل

پژوهشگر

• Uncertainty Visualization
• Data Analysis
• Multiverse Analysis
• +۳ مورد دیگر

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

Vinogradov Vadim Aleksandrovichمشاهده پروفایل

استاد

• constitutional law
• administrative law
• public law
• +۵ مورد دیگر

Vinogradov Vadim Aleksandrovich is a prominent legal scholar serving as Dean of the Faculty of Law at the National Research University Higher School of Economics (HSE) since June 2020, while also heading the Department of Public Law. With a distinguished career spanning over 25 years since joining HSE in 1998, he has established himself as a leading expert in constitutional law, administrative law, and public law. His academic leadership extends to serving as Academic Director of the Public Law educational program and as a Member of the Academic Council of HSE University. 2008 - Academic title: Professor 2005 - Doctor of Law from Russian Academy of Public Administration under the President of the Russian Federation 2003 - Academic title: Associate Professor 2000 - Candidate of Law from Lomonosov Moscow State University 1997 - Specialty 'Jurisprudence', qualification 'Lawyer' from Lomonosov Moscow State University Professor Vinogradov's research focuses on constitutional law, administrative law, legislative process, digital law, and human rights. His scholarly work examines the intersection of traditional legal frameworks with emerging digital challenges, including constitutional liability in the digital age, AI regulation, and the legal aspects of deepfake technology. His recent publications demonstrate a sophisticated understanding of how constitutional principles must adapt to contemporary technological realities while maintaining core democratic values. His extensive publication record reveals a consistent scholarly trajectory from traditional constitutional law toward increasingly complex digital governance issues. The trend shows a remarkable evolution from foundational constitutional studies to cutting-edge research on digital sovereignty, AI regulation, and the legal challenges posed by new media technologies. His work bridges theoretical constitutional scholarship with practical legal application in rapidly evolving technological contexts. Honored Lawyer of the Russian Federation (March 2025) Anatoly Koni Medal (November 2023) HSE University Honorary Diploma (March 2023) Best Academic Supervisor awards in multiple categories (2023) Gratitude from the President of the Russian Federation (April 2017) As an academic supervisor, Professor Vinogradov has mentored numerous doctoral candidates whose research spans critical contemporary legal issues including digital transformation of education, constitutional limitations on rights for state security, political freedom, and digital sovereignty. His leadership extends to directing major research initiatives and serving on editorial boards of prominent legal journals such as 'Municipal Property: Economics, Law, Management' and 'International Public and Private Law.' His administrative roles include chairing significant working groups on regulatory reform and serving as a trusted advisor to governmental bodies on constitutional and legislative matters.

Joseph A. Konstanمشاهده پروفایل

استاد

• Recommender Systems
• Social Computing
• Human-Computer Interaction
• +۵ مورد دیگر

Joseph A. Konstan is a Distinguished McKnight University Professor and Distinguished University Teaching Professor at the University of Minnesota's Department of Computer Science and Engineering. He serves as Associate Dean for Research in the College of Science and Engineering and is a Fellow of ACM, AAAS, and IEEE. His work focuses on Recommender Systems , Social Computing , and Human-Computer Interaction issues including personalization, online community ethics, and health technology. Education: Ph.D., Computer Science, University of California, Berkeley (1993) M.S., Computer Science, University of California, Berkeley (1990) A.B., Computer Science, Harvard College (1987) His research explores collaborative filtering (GroupLens project), organizational communication systems (bulk email optimization), and ethical frameworks for online community research. Current projects include a live news reader community infrastructure funded by NSF Award #CNS-2016397 and mobile health applications for diabetes management in collaboration with UMN School of Nursing. Recent publications analyze user interaction patterns in recommender systems, algorithmic trade-offs , and privacy mechanisms . Articles examine content diversity, novelty preferences, and multi-stakeholder personalization challenges. Scientific Recognition: Distinguished ACM SIGCHI Lifetime Service Award (2013) IEEE Fellow (2013), AAAS Fellow (2011), ACM Fellow (2008) Multiple test of time awards from SIGIR, WWW, and AAAI conferences As advisor, Konstan has mentored over 40 graduate students including current Ph.D. candidates Ruoyan Kong and Ruixuan Sun , with alumni now at institutions like University of Illinois, IBM Research, Amazon, and Google. He leads the GroupLens Research Group , which recently received the ACM Software Systems Award for its 30-year contributions to recommender systems.