جستجوی استاد راهنمای دانشگاهی

Silvia Lindtnerمشاهده پروفایل

دانشیار

• Science and Technology Studies (STS)
• Cultural Anthropology
• Feminist Studies
• +۷ مورد دیگر

Silvia Lindtner is an Associate Professor at the University of Michigan's School of Information and Director of the Center for Ethics, Society, and Computing (ESC). She holds courtesy appointments in the Penny W. Stamps School of Art and Design and the Digital Studies Institute. Her work focuses on the social and cultural study of technology in China and globally, with a focus on data-driven governance, AI ethics, and the intersection of technology and labor. Lindtner has conducted nearly two decades of fieldwork in China, examining innovation ecosystems, digital economies, and the affective dimensions of state control. She is the author of the award-winning *Prototype Nation: China and the Contested Promise of Innovation* (2020) and co-author of *Technoprecarious* (2020). Education: PhD in Information and Computer Sciences from University of California, Irvine; BS/MS in Media Technology and Design from University of Hagenberg, Austria. Research Interests: Science and Technology Studies (STS), China Studies, HCI, Critical Computing, AI Ethics, Data Governance, Labor Studies, and Transnational Digital Economies. She explores how technological systems shape governance, labor practices, and everyday life, particularly in contexts of global inequality and state surveillance. Awards: Joseph Levenson Prize (2021), Francis L.K. Hsu Book Prize (2021), ACM Distinguished Member (2022), and fellowships from the National Committee on US-China Relations (2021-2023) and China-US Scholars Program (2021-2022). Grants: Supported by NSF, IMLS, Intel Labs, Google Anita Borg, and Chinese National Natural Science Foundation. Leads interdisciplinary initiatives including Tech.Culture.Matters research group and Michigan Interactive and Social Computing (MISC) research group. Labs/Teams: Directs the Center for Ethics, Society, and Computing (ESC) and collaborates with the Lieberthal-Rogel Center for Chinese Studies. Current projects include studies on affective control in AI governance and transnational data practices in healthcare and labor.

Panos Ipeirotisمشاهده پروفایل

استاد

• Crowdsourcing
• Machine Learning
• Human-AI Collaboration
• +۷ مورد دیگر

Panos Ipeirotis is a Professor at the Leonard N. Stern School of Business at New York University, affiliated with the Department of Technology, Operations, and Statistics. He also serves as the George A. Kellner Faculty Fellow and is associated with the Center for Data Science and Computer Science departments at NYU. PhD in Computer Science (Columbia University, 2004) MSc in Computer Science (Columbia University, 2001) BSc in Computer Engineering & Informatics (University of Patras, 1999) His research spans crowdsourcing, machine learning, human-AI collaboration, online labor markets, and social media analytics. He pioneered human-machine loop systems that combine human and machine intelligence to achieve superior outcomes. His work has applications in data quality assurance, visual media search (e.g., Google Project Glass), and economic valuation of user-generated content. Recent publications focus on algorithmic fairness in hiring systems, occupational segregation analysis, and theoretical advancements in crowdsourcing consensus mechanisms. Earlier work includes foundational studies on data quality in crowdsourcing platforms, economic impacts of product reviews, and query optimization for text-centric tasks. 2015 Lagrange Prize in Complex Systems NSF CAREER Award SIGKDD Test of Time Award (2020) Multiple Best Paper awards (WWW 2011, KDD 2008, SIGMOD 2006) He has received significant grants, including a $1.5 million Google Research Grant (2013) for integrating crowdsourcing with machine learning algorithms. His work bridges computer science, economics, and social psychology, with implications for policy-making and business strategy.

Celestine Mendler-Dünnerمشاهده پروفایل

استاد

• Machine Learning in Social Context
• Algorithmic Collective Action
• Performative Prediction
• +۶ مورد دیگر

Celestine Mendler-Dünner is a Principal Investigator at the ELLIS Institute in Tübingen, co-affiliated with the Max Planck Institute for Intelligent Systems and the Tübingen AI Center. She leads the Algorithms and Society research group, focusing on machine learning in social contexts and the role of prediction in digital economies. Her work bridges theoretical machine learning with practical societal impact, developing tools for safe, reliable, and equitable AI ecosystems. Her educational background includes a PhD from ETH Zurich in collaboration with IBM Research, followed by an SNSF postdoctoral fellowship at UC Berkeley hosted by Moritz Hardt. She was previously a group leader at the Max Planck Institute for Intelligent Systems before joining the ELLIS Institute. Mendler-Dünner's research spans several interconnected themes including performative prediction (where predictions change the behavior they aim to predict), algorithmic collective action (how participants can steer AI systems toward common goals), and the role of LLMs in social science research. Her work combines theoretical foundations with practical implementations, addressing challenges in interactive machine learning, optimization in dynamic environments, and context-specific evaluation of AI systems. She particularly examines how algorithmic predictions mediate services and platforms at societal scale, exploring concepts of economic power in digital markets. Her publication record shows a clear evolution from system-aware machine learning algorithms (including foundational work on IBM Snap ML) toward increasingly sociotechnical questions at the intersection of machine learning, economics, and policy. Recent work focuses on measuring performative power in digital economies, evaluating LLMs as risk scores, and developing frameworks for algorithmic collective action in recommender systems and labor markets. Among her notable recognitions are the ETH Medal for her dissertation, the IBM Research Division Award, the Fritz Kutter Award, and the IBM Eminence and Excellence Award. She is an ELLIS Scholar, a fellow of the Elisabeth-Schiemann-Kolleg, and affiliated with several prestigious research programs including the International Max Planck Research School for Intelligent Systems and the Max Planck ETH Center for Learning Systems. ETH Medal (dissertation award) IBM Research Division Award Fritz Kutter Award IBM Eminence and Excellence Award SNSF Early Postdoc Mobility Fellowship Mendler-Dünner actively mentors the next generation of researchers, advising PhD student Patrik Wolf and supervising research interns including Joachim Baumann, Haiqing Zhu, and Anna Badalyan, as well as Master's student Dorothee Sigg. She serves as core faculty for the International Max Planck Research School and associated faculty for the Max Planck ETH Center for Learning Systems. Her group has secured significant research funding through fellowships and institutional support, enabling work on projects like Powermeter (measuring search engine influence) and Snap ML (resource-efficient machine learning library with over 1 million PyPI downloads). She leads the Algorithms and Society research group, which examines machine learning as part of broader sociotechnical ecosystems. The group explores human-population interactions with algorithmic systems and incorporates these insights into learning system fundamentals. Current projects include investigating economic incentives in digital platforms, developing tools for systematic LLM evaluation in social science contexts, and creating frameworks for collective action in algorithmic systems. Mendler-Dünner also co-organizes the Algorithmic Collective Action workshop at NeurIPS 2025, demonstrating her leadership in emerging research directions at the AI-society interface.

Amy Bruckmanمشاهده پروفایل

استاد

• Social Computing
• Online Collaboration
• Content Moderation
• +۳ مورد دیگر

Amy Bruckman is a Regents’ Professor and Senior Associate Chair in the School of Interactive Computing at Georgia Institute of Technology. As a Fellow of The ACM and member of the SIGCHI Academy , she contributes to social computing research focusing on online collaboration, cross-cultural understanding, and content moderation. Her 2022 book "Should You Believe Wikipedia? Online Communities and the Construction of Knowledge" explores digital knowledge creation. Education: Ph.D. from MIT Media Lab (1997), B.A. in Physics from Harvard (1987) Research Affiliations: GVU Center, IRI People and Technology Her work addresses social computing challenges including: AI ethics in human-AI interaction Algorithmic bias in content moderation Epistemic justice in online communities Comparative platform analysis (Reddit, Discord, TikTok) Grassroots technology movements Recent publications examine: AI support tools for online counseling Community-driven research frameworks Racial bias mitigation in toxic language detection Designing teachable social media experiences Human trafficking intervention ethics Scientific recognition includes: ACM Fellowship SIGCHI Academy membership She has contributed to: Georgia Tech's Computing Education initiatives Research ethics frameworks for Human-Computer Interaction

Siân Bayneمشاهده پروفایل

استاد

• Higher Education Futures
• Utopian Studies
• Digital Education
• +۹ مورد دیگر

Professor Siân Bayne is a leading academic in digital education at the University of Edinburgh , where she serves as Assistant Principal for Education Futures and directs the Centre for Research in Digital Education . Her work bridges critical theory and practical innovation in higher education. Interdisciplinary research on digital education and futures studies Leadership in the Edinburgh Futures Institute and Moray House School of Education and Sport Global impact through UNESCO collaborations and UKRI GCRF projects Bayne’s research explores higher education futures , utopian theory , and digital enhancement , with a focus on: AI’s role in teaching and learning Ethical implications of educational technologies Anonymous social media in academic spaces Speculative scenarios for educational systems Global South digital education models Augmented reality applications in assessment Her 15 most recent publications span 2017-2025 , covering critical perspectives on: Generative AI and educational innovation Utopian design in universities Data governance in learning analytics Augmented reality pedagogy Digital cultural heritage Scientific recognition includes: IASH Sabbatical Fellowship (2023) Bayne leads Higher Education Futures initiatives and partners with institutions worldwide, including: UNESCO Global Education and Technology Report World Bank collaborations European university leadership programs She also drives major research centers like: Centre for Research in Digital Education UKRI GCRF Urban Disaster Risk Hub

• Operations Management
• Supply Chain Management
• Sharing Economy
• +۶ مورد دیگر

Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.

Arvind Karunakaranمشاهده پروفایل

استادیار

• Sociology of Work and Occupations/Professions
• Organization Theory
• Technological/Organizational Change
• +۴ مورد دیگر

Arvind Karunakaran is an Assistant Professor at Stanford University in the Department of Management Science and Engineering. He holds affiliations with the Center for Work, Technology, and Organization (WTO) , Stanford Technology Ventures Program (STVP) , Stanford Institute for Human-centered Artificial Intelligence (HAI) , and the Digital Economy Lab (DEL) . His research focuses on authority and accountability in the workplace , particularly under technological change and human-AI augmentation. Education: Ph.D. from MIT Sloan School of Management (2018) His work employs ethnographic and field-based methods to study empirical puzzles in workplace dynamics, complemented by comparative-historical analysis and quantitative/textual data analysis . Key research areas include social/algorithmic evaluation of workers , human-AI reskilling , and conflicts in symmetrical relations . Recent publications analyze AI's impact on workplace inequality , platform governance , and crowd-based accountability . His findings are published in top journals like Administrative Science Quarterly and Organization Science . Scientific Awards & Recognitions: Best Published Paper Award (ASA, 2025) Gerard J. Tellis Best Junior Faculty Paper Award (AIM Conference, 2025) W. Richard Scott Article Award (ASA, 2024) Responsible Research in Management Award (RRBM, 2024) Future of Organizations Fellowship (2024) Professor Karunakaran advises doctoral and master's students in areas related to technology and organizations , and teaches courses on organizational behavior , organizational theory , and innovation management .

• Critical Platform and Data Studies
• Platform Labour
• Platform Cooperativism
• +۷ مورد دیگر

Rafael Grohmann is an Assistant Professor of Media Studies at the University of Toronto Scarborough (UTSC), with a graduate cross-appointment at the Faculty of Information (iSchool). He leads the DigiLabour Initiative and is a researcher with Fairwork, focusing on Critical Platform and Data Studies. His research emphasizes platform labour, the platformization of work, and resistance strategies among workers in Latin America. Grohmann holds a PhD in Communication from the University of São Paulo and has held prior academic positions at institutions in Brazil, including Unisinos University. His research interests span platform cooperativism, public policies for technology and labor, AI's impact on work, and data-driven labour practices. He is an editorial board member for Big Data & Society and Work, Employment and Society , and contributes to UCLA’s Center for Critical Internet Inquiry (C2i2). His work examines intersections of technology, labour precarity, and solidarity economies, with a focus on global South contexts. Recent publications analyze click farm labour in Brazil, gender dynamics in platform cooperatives, and global-local trends in platform worker organizing. Grohmann’s work bridges critical theory with action research, advocating for fair work standards in digital economies. He participates in initiatives like the Platform Cooperativism Consortium and the Labor Tech Research Network.

Taina Bucherمشاهده پروفایل

استاد

• Algorithmic Studies
• Social Media
• Digital Infrastructure
• +۸ مورد دیگر

Taina Bucher is a Professor at the Department of Media and Communication, University of Oslo, specializing in algorithmic studies, digital infrastructure, and human-machine communication. She leads the Screen Cultures research group and serves as Principal Investigator for HumAIn , a five-year humanities hub reimagining AI (2024-2029). Research Focus: Her work examines Algorithmic power and politics Cultural imaginaries of digital technology Temporalities of algorithmic media Feminist epistemologies in digital contexts Monitorial citizenship in platform societies Publications: Bucher has authored two monographs: Facebook (Polity Press, 2021) and IF…THEN: Algorithmic Power and Politics (Oxford University Press, 2018). Her recent articles explore facial recognition systems, algorithmic temporality, and digital divides. Academic Background: PhD in Media Studies (University of Oslo, 2012), MSc in Culture & Society (London School of Economics, 2007), with visiting scholar appointments at The New School, Ryerson University, and New York University. Teaching: She supervises and teaches topics including Digital infrastructure Algorithm studies Screen cultures Media theory Critical data studies Digitalization of public sectors Editorial Roles: Active on editorial boards for Journal of Communication , New Media & Society , and Information, Communication & Society .

Ming Yinمشاهده پروفایل

دانشیار

• Social Computing
• Crowdsourcing
• Human-AI Interaction
• +۶ مورد دیگر

Ming Yin is an Associate Professor in the Department of Computer Science at Purdue University. Her research bridges human-computer interaction, applied artificial intelligence, computational social science, and behavioral sciences. She focuses on leveraging human behavior data to design intelligent systems that balance machine efficiency with human understanding, trust, and engagement. Education : PhD in Computer Science (Harvard University, 2017), B.E. in Computer Software (Tsinghua University, 2011) Previous Roles : Postdoctoral researcher at Microsoft Research New York City (2017–2018) Teaching : Courses on AI, Human-AI Interaction, Data Mining, and Human-Centered Computing Research Interests center on social computing, crowdsourcing, human-AI interaction, and ethical AI. She employs experimental and computational methods to study how human behavior can improve AI systems' design, fairness, and user trust. Her work has significant implications for gig economy platforms, decision support systems, and algorithmic accountability. Scientific Contributions include over 15 recent articles in top venues like CHI, IJCAI, and ACL. These works explore topics such as LLM-driven trust calibration, adversarial social influence, and ethical AI design. Her research has been recognized with the NSF CAREER Award Siebel Scholar (Class of 2017) Multiple Best Paper and Honorable Mention Awards at CHI, CSCW, and HCOMP Teaching Expertise spans courses like Introduction to Artificial Intelligence (CS 471), Human-AI Interaction (CS 592-HAI), and Data Mining (CS 573). She emphasizes project-based learning and designing systems for real-world problems, such as "learning in a new era" in her 2025 HCI course.

Elliott Ashمشاهده پروفایل

دانشیار

• Law and Economics
• Political Economy
• Econometrics
• +۵ مورد دیگر

Elliott Ash is an Associate Professor of Law, Economics, and Data Science at ETH Zurich's Center for Law & Economics. He holds a Ph.D. in Economics and J.D. from Columbia University, a B.A. in Economics, Government, and Philosophy from the University of Texas at Austin, and an LL.M. in International Criminal Law from the University of Amsterdam. His research focuses on empirical legal studies using econometrics, NLP, and ML, examining topics like judicial behavior, legislative impact, and AI-driven governance. He has been funded by the ERC, Swiss NSF, and others. Research Interests: Elliott explores automation of legal decisions, text-as-data analysis in law, and the intersection of AI with legal systems. He develops tools like BallotBot and LePaRD to enhance legal transparency and public understanding. His work bridges law, economics, and computer science, with publications in top journals like the American Economic Journal and Review of Economics and Statistics . Teaching: Courses include Building a Robot Judge , Natural Language Processing for Law , and Big Data for Public Policy . He co-organizes the Zurich Workshop in AI+Economics and Monash-Warwick-Zurich Text-as-Data Workshops. Awards: European Research Council Starting Grant, Swiss National Science Foundation Grant, and multiple grants from U.S. and Swiss institutions. His work has been featured in NPR , VoxEU , and Georgetown Law Journal . Labs/Teams: Leads the Swiss AI Initiative's Human-AI Alignment team, collaborates with the CEPR on Political Economy research, and serves as an Economic Journal Associate Editor.

• Economics of IT Labor
• Technological Change and Reskilling
• Algorithms and AI in HR and Management
• +۵ مورد دیگر

Prasanna (Sonny) Tambe is a Professor at the Wharton School of the University of Pennsylvania, specializing in the economics of technology and labor markets. His research explores AI’s impact on workforce dynamics, HR algorithms, and the gender wage gap in tech industries. Education: Ph.D. in Managerial Science and Applied Economics (Wharton, UPenn); S.B. and M.Eng. in Electrical Engineering and Computer Science (MIT). His work leverages internet-scale data from job platforms and patent databases to analyze trends in skill acquisition, remote work diversity, and algorithmic bias in hiring. Recent studies examine AI’s role in HR decision-making, the economics of emerging technologies, and labor market responses to IT innovation. Scientific Awards: Best Undergraduate Professors (Poets & Quants, 2020) Best Paper Awards (Management Science, Information Systems Research) ISS Sandra A. Slaughter Early Career Award (2016) Tambe co-directs Wharton Human-AI Research, focusing on ethical AI integration in organizations. His teaching includes award-winning courses on AI’s societal implications and data-driven business strategies.

• Cyber Law
• Artificial Intelligence and Law
• Business Law
• +۷ مورد دیگر

Zaklina Spalevic is a distinguished Professor at Singidunum University, specializing in the intersection of law, technology, and business. With a strong academic background in criminal law and extensive research in cyber law, artificial intelligence applications in legal systems, and tourism law, she has established herself as a leading scholar in digital legal frameworks. Her work spans multiple disciplines, connecting traditional legal principles with emerging technological challenges. Dr. Spalevic earned her doctoral degree in Criminal Law from the University of the Academy of Economics in Novi Sad (2008-2012), following basic studies in General Law at the University of Pristina (1996-2001). Her educational foundation in Science and Mathematics from First Pristina High School (1992-1996) provided the analytical basis for her interdisciplinary approach to legal scholarship. Her research interests focus on the evolving landscape of cyber law, particularly the legal implications of artificial intelligence in judicial systems, electronic governance, and tourism industry regulation. Dr. Spalevic has pioneered work on digital evidence processing, algorithmic justice, and the integration of green law principles into sustainable business practices. Her publications reveal a consistent pattern of addressing emerging legal challenges in the digital age, with increasing emphasis on AI applications across various legal domains. Analysis of her recent publications shows a clear trend toward interdisciplinary research that bridges law, technology, and business. Her work increasingly focuses on practical applications of legal frameworks for emerging technologies, particularly in tourism, agriculture, and judicial systems. The integration of technical solutions with legal regulation represents a distinctive feature of her scholarly contributions. Dr. Spalevic has authored numerous publications including three books: 'Fundamentals of Law with Special Reference to Business and Tourism Law' (2021, 2024 editions) and 'Legal Aspects of Cyberspace' (2018). Her extensive publication record includes over 100 journal articles and conference papers spanning cyber security, electronic governance, intellectual property in digital environments, and legal frameworks for emerging technologies. She actively contributes to academic discourse through conference presentations and collaborative research projects, particularly focusing on the legal implications of artificial intelligence across various sectors. Her work demonstrates a commitment to developing practical legal frameworks that address real-world technological challenges while maintaining foundational legal principles.

Motahhare Eslamiمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Social Computing
• Responsible Computing
• +۷ مورد دیگر

Motahhare Eslami is an Assistant Professor at Carnegie Mellon University’s School of Computer Science, Human-Computer Interaction Institute. Her research bridges human-computer interaction, social computing, and AI ethics. Education : PhD in Computer Science from University of Illinois at Urbana-Champaign, advised by Karrie Karahalios Research Focus : Dr. Eslami investigates algorithmic opacity and user behavior in socio-technical systems, developing frameworks to enhance transparency and stakeholder participation in AI governance. Her work addresses: Algorithmic bias mitigation through participatory audits Ethical implications of generative AI and smart assistants Inclusion of marginalized communities in AI design Transparency mechanisms for opaque algorithms Civic technology and public sector AI Recent Article Trends : Her publications analyze algorithmic harms through lenses of: Medical imaging and data generation Labor market equity and low-wage employment Youth perspectives on AI ethics Content creator experiences with demonetization Explainability in black-box AI systems Scientific Recognition : Best Paper at AAAI HCOMP (2025) Google Academic Research Award (2024) Microsoft AI & Society Fellowship (2024) 100 Brilliant Women in AI Ethics (2023) Teaching Innovation Award at CMU (2023) Advising & Collaborations : Mentors PhD students Shixian Xie, Wesley Deng, Seyun Kim, and former post-doc Jaemarie Solyst. Collaborates with NSF AI Institute for Collaborative Assistance (2022–2027), Amazon, Google, and Microsoft on responsible AI initiatives.

Antonio A. Casilliمشاهده پروفایل

استاد

• Digital Labor
• Sociology of Technology
• Platform Economy
• +۴ مورد دیگر

Antonio A. Casilli is a Professor of Sociology at Télécom Paris (Institut Polytechnique de Paris) and a researcher at the Interdisciplinary Institute of Innovation (i3) . He is an associate member of LACI-IIAC (formerly the Edgar Morin Center) at EHESS and serves as a Faculty Fellow at the Nexa Center for Internet and Society (Polytechnic University of Turin) since 2018. Research Focus: Digital labor, platform economy, AI ethics, and the social implications of technology Awards: Prix Étoiles de la SCAM, Prix Meilleur Documentaire de l'Année (Bangkok), selected as Nature Journal Top Science Pick His work analyzes how digital platforms reshape labor dynamics, privacy norms, and social inequalities. Recent studies explore global AI data work, including fieldwork in Latin America, Africa, and Europe. He advocates for ethical frameworks recognizing human labor behind automation. Media Engagement: Regular contributor to France Culture , Le Monde , Wired , and Rue89 . Authored En attendant les robots (2019) and Schiavi del clic (2020), investigating hidden digital labor structures.