Julia Stoyanovich

Associate Professor and Director of R/AIstoyanovich (at) nyu.eduPersonal Website

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Julia is an Institute Associate Professor of Computer Science and Engineering at the Tandon School of Engineering, Associate Professor of Data Science at the Center for Data Science, and Director of the Center for Responsible Ai. Julia’s goal is to make “Responsible AI” synonymous with “AI”.  She works towards this goal by engaging in academic research, education and technology policy, and by speaking about the benefits and harms of AI to practitioners and members of the public.

Julia’s research interests include AI ethics and legal compliance, and data management and AI systems.  In addition to academic publications, she has written for the New York Times, the Wall Street Journal, and Le Monde.  Julia has been teaching courses on responsible data science and AI to students, practitioners and the general public.  She is a co-author of “Data, Responsibly”, an award-winning comic book series for data science enthusiasts, and “We are AI”, a comic book series for the general audience.  

Julia is engaged in technology policy and regulation in the US and internationally, having served on the New York City Automated Decision Systems Task Force, by mayoral appointment, among other roles.

Julia received her M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics & Statistics from the University of Massachusetts at Amherst. She is a recipient of the NSF CAREER Award and a Senior Member of the ACM.

Selected publications

  1. Responsible AI literacy: A stakeholder-first approach
    Daniel Dominguez, and Julia Stoyanovich
    Big Data and Society 2023
  2. Setting the Right Expectations: Algorithmic Recourse Over Time
    João Fonseca, Andrew Bell, Carlo Abrate, Francesco Bonchi, and Julia Stoyanovich
    In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2023, Boston, MA, USA, 30 October 2023 - 1 November 2023 2023
  3. Query Refinement for Diversity Constraint Satisfaction
    Jinyang Li, Yuval Moskovitch, Julia Stoyanovich, and H. V. Jagadish
    Proc. VLDB Endow. 2023
  4. ERICA: Query Refinement for Diversity Constraint Satisfaction
    Jinyang Li, Alon Silberstein, Yuval Moskovitch, Julia Stoyanovich, and H. V. Jagadish
    Proc. VLDB Endow. 2023
  5. Subset Modelling: A Domain Partitioning Strategy for Data-efficient Machine-Learning
    Vı́tor Ribeiro, Eduardo H. M. Pena, Raphael Freitas Saldanha, Reza Akbarinia, Patrick Valduriez, Falaah Arif Khan, Julia Stoyanovich, and Fábio Porto
    In Proceedings of the 38th Brazilian Symposium on Databases, SBBD 2023, Belo Horizonte, MG, Brazil, September 25-29, 2023 2023
  6. Responsible Data Management
    Julia Stoyanovich, Bill Howe, and HV Jagadish
    Proceedings of the VLDB Endowment 2020
  7. The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
    Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Herasymova, Lucas Rosenblatt, and Julia Stoyanovich
    Proceedings of the Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023
  8. Spending Privacy Budget Fairly and Wisely
    Lucas Rosenblatt, Joshua Allen, and Julia Stoyanovich
    Theory and Practice of Differential Privacy (@ICML) 2022
  9. Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making
    Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, and Sebastian Schelter
    In Proceedings of the 39th International Conference on Data Engineering, ICDE 2023
  10. The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction
    Falaah Arif Khan, and Julia Stoyanovich
    CoRR 2023
  11. On Fairness and Stability: Is Estimator Variance a Friend or a Foe?
    Falaah Arif Khan, Denys Herasymuk, and Julia Stoyanovich
    CoRR 2023
  12. The Imperative of Interpretable Machines
    Julia Stoyanovich, Jay J. Van Bavel, and Tessa V. West
    Nature Machine Intelligence 2020
  13. Introducing contextual transparency for automated decision systems
    Mona Sloane, Ian Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, and Julia Stoyanovich
    Nature Machine Intelligence 2023
  14. The Many Facets of Data Equity
    H.V. Jagadish, Julia Stoyanovich, and Bill Howe
    ACM Journal of Data and Information Quality 2023
  15. Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences
    Haoyue Ping, and Julia Stoyanovich
    Proc. ACM Manag. Data 2023
  16. Supporting Hard Queries over Probabilistic Preferences
    Haoyue Ping, Julia Stoyanovich, and Benny Kimelfeld
    PVLDB 2020
  17. Counterfactuals for the Future
    Lucius E. J. Bynum, Joshua R. Loftus, and Julia Stoyanovich
    CoRR 2022
  18. An Interactive Introduction to Causal Inference
    Lucius E.J. Bynum, Falaah Arif Khan, Oleksandra Konopatska, Joshua R. Loftus, and Julia Stoyanovich
    VISxAI: Workshop on Visualization for AI Explainability 2022
  19. Rankers, Rankees, & Rankings: Peeking into the Pandora’s Box from a Socio-Technical Perspective
    Jun Yuan, Julia Stoyanovich, and Aritra Dasgupta
    CoRR 2022
  20. The Many Facets of Data Equity
    H. V. Jagadish, Julia Stoyanovich, and Bill Howe
    In Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference, Nicosia, Cyprus, March 23, 2021 2021
  21. Translational Tutorial: Fairness and Friends
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    In 4th Annual Conference on Fairness, Accountability, and Transparency, ACM FAccT 2021
  22. The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
    Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Zakharchenko, Lucas Rosenblatt, and Julia Stoyanovich
    In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023, Chicago, IL, USA, June 12-15, 2023 2023
  23. All Aboard! Making AI Education Accessible
    Falaah Arif Khan, Lucius Bynum, Amy Hurst, Lucas Rosenblatt, Meghana Shanbhogue, Mona Sloane, and Julia Stoyanovich
    Center for Responsible AI, New York University 2023
  24. The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization’s Algorithms
    Andrew Bell, Oded Nov, and Julia Stoyanovich
    In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023, Hamburg, Germany, April 23-28, 2023 2023
  25. Personal Data for Personal Use: Vision or Reality?
    Xin Luna Dong, Bo Li, Julia Stoyanovich, Anthony Kum Hoe Tung, Gerhard Weikum, Alon Y. Halevy, and Wang-Chiew Tan
    In Companion of the 2023 International Conference on Management of Data, SIGMOD/PODS 2023, Seattle, WA, USA, June 18-23, 2023 2023
  26. Fairness in Ranking: From Values to Technical Choices and Back
    Julia Stoyanovich, Meike Zehlike, and Ke Yang
    In Companion of the 2023 International Conference on Management of Data, SIGMOD/PODS 2023, Seattle, WA, USA, June 18-23, 2023 2023
  27. Spending Privacy Budget Fairly and Wisely
    Lucas Rosenblatt, Joshua Allen, and Julia Stoyanovich
    CoRR 2022
  28. Temporal graph patterns by timed automata
    Amir Pouya Aghasadeghi, Jan Van Bussche, and Julia Stoyanovich
    VLDB Journal 2023
  29. Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance
    Andrew Bell, Oded Nov, and Julia Stoyanovich
    Data & Policy 2023
  30. Zooming Out on an Evolving Graph
    Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, and Julia Stoyanovich
    In Proceedings of the 23nd International Conference on Extending Database Technology, EDBT 2020
  31. FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions
    Sebastian Schelter, Yuxuan He, Jatin Khilnani, and Julia Stoyanovich
    In Proceedings of the 23nd International Conference on Extending Database Technology, EDBT 2020
  32. Towards Responsible Data-driven Decision Making in Score-Based Systems
    Abolfazl Asudeh, H. V. Jagadish, and Julia Stoyanovich
    IEEE Data Eng. Bull. 2019
  33. Nutritional Labels for Data and Models
    Julia Stoyanovich, and Bill Howe
    IEEE Data Eng. Bull. 2019
  34. Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation
    Serge Abiteboul, and Julia Stoyanovich
    ACM Journal of Data and Information Quality 2019
  35. MithraLabel: Flexible Dataset Nutritional Labels for Responsible Data Science
    Chenkai Sun, Abolfazl Asudeh, H. V. Jagadish, Bill Howe, and Julia Stoyanovich
    In Proceedings of the 28th International Conference on Information and Knowledge Management, CIKM 2019
  36. Balanced Ranking with Diversity Constraints
    Ke Yang, Vasilis Gkatzelis, and Julia Stoyanovich
    In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
  37. Designing Fair Ranking Schemes
    Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, and Gautam Das
    In Proceedings of the 2019 International Conference on the Management of Data, SIGMOD 2019
  38. MithraRanking: A System for Responsible Ranking Design
    Yifan Guan, Abolfazl Asudeh, Pranav Mayuram, H. V. Jagadish, Julia Stoyanovich, Gerome Miklau, and Gautam Das
    In Proceedings of the 2019 International Conference on the Management of Data, SIGMOD 2019
  39. The Responsibility Challenge for Data
    H. V. Jagadish, Francesco Bonchi, Tina Eliassi-Rad, Lise Getoor, Krishna P. Gummadi, and Julia Stoyanovich
    In Proceedings of the 2019 International Conference on the Management of Data, SIGMOD 2019
  40. Research Directions for Principles of Data Management, Dagstuhl Perspectives Workshop 16151)
    Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Mpdfak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, and Ke Yi
    Dagstuhl Manifestos 2018
  41. On Obtaining Stable Rankings
    Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, and Julia Stoyanovich
    PVLDB 2018
  42. Panel: A Debate on Data and Algorithmic Ethics
    Julia Stoyanovich, Bill Howe, H. V. Jagadish, and Gerome Miklau
    PVLDB 2018
  43. Probabilistic Inference Over Repeated Insertion Models
    Batya Kenig, Lovro Ilijasic, Haoyue Ping, Benny Kimelfeld, and Julia Stoyanovich
    In Proceedings of the 32nd Conference on Artificial Intelligence, AAAI 2018
  44. Online Set Selection with Fairness and Diversity Constraints
    Julia Stoyanovich, Ke Yang, and H. V. Jagadish
    In Proceedings of the 21th International Conference on Extending Database Technology, EDBT 2018
  45. Computational Social Choice Meets Databases
    Benny Kimelfeld, Phokion G. Kolaitis, and Julia Stoyanovich
    In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
  46. Generating Evolving Property Graphs with Attribute-Aware Preferential Attachment
    Amir Aghasadeghi, and Julia Stoyanovich
    In Proceedings of the 7th International Workshop on Testing Database Systems, DBTest at SIGMOD 2018
  47. A Query Engine for Probabilistic Preferences
    Uzi Cohen, Batya Kenig, Haoyue Ping, Benny Kimelfeld, and Julia Stoyanovich
    In Proceedings of the 2018 International Conference on the Management of Data, SIGMOD 2018
  48. Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management
    Julia Stoyanovich, Bill Howe, and H. V. Jagadish
    In Proceedings of the 2018 International Conference on the Management of Data, SIGMOD 2018
  49. A Nutritional Label for Rankings
    Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, and Gerome Miklau
    In Proceedings of the 2018 International Conference on the Management of Data, SIGMOD 2018
  50. MobilityMirror: Bias-Adjusted Transportation Datasets
    Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, and Bill Howe
    In Proceedings of the 1st Workshop on Big Social Data and Urban Computing, BiDU at VLDB 2018
  51. Zooming in on NYC Taxi Data with Portal
    Julia Stoyanovich, Matthew Gilbride, and Vera Zaychik Moffitt
    In Poster Track of the 1st Workshop on Big Social Data and Urban Computing, BiDU at VLDB 2018
  52. Diversity in Big Data: A Review
    Marina Drosou, H. V. Jagadish, Evaggelia Pitoura, and Julia Stoyanovich
    Big Data 2017
  53. A Database Framework for Probabilistic Preferences
    Batya Kenig, Benny Kimelfeld, Haoyue Ping, and Julia Stoyanovich
    In Proceedings of the 11th Alberto Mendelzon International Workshop on Foundations of Data Management and the Web, AMW 2017
  54. Automatically and Adaptively Determining Execution Plans for Queries with Parameter Markers
    Wei Fan, Guy Lohman, Volker Markl, Nimrod Megiddo, Jun Rao, David Simmen, and Julia Stoyanovich
    2011
  55. Social Behavior Analysis and Inferring Social Networks for a Recommendation System
    Sihem Amer-Yahia, Evgeniy Gabrilovic, Bo Pang, Julia Stoyanovich, and Cong Yu
    2011
  56. Temporal graph algebra
    Vera Zaychik Moffitt, and Julia Stoyanovich
    In Proceedings of The 16th International Symposium on Database Programming Languages, DBPL 2017
  57. Querying Probabilistic Preferences in Databases
    Batya Kenig, Benny Kimelfeld, Haoyue Ping, and Julia Stoyanovich
    In Proceedings of the 36th Symposium on the Principles of Database Systems, PODS 2017
  58. DataSynthesizer: Privacy-Preserving Synthetic Datasets
    Haoyue Ping, Julia Stoyanovich, and Bill Howe
    In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, SSDBM 2017
  59. Fides: Towards a Platform for Responsible Data Science
    Julia Stoyanovich, Bill Howe, Serge Abiteboul, Gerome Miklau, Arnaud Sahuguet, and Gerhard Weikum
    In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, SSDBM 2017
  60. Measuring Fairness in Ranked Outputs
    Ke Yang, and Julia Stoyanovich
    In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, SSDBM 2017
  61. Synthetic Data for Social Good
    Bill Howe, Julia Stoyanovich, Haoyue Ping, Bernease Herman, and Matt Gee
    Proceedings of Data for Good Exchange D4GX 2017
  62. Data, Responsibly: Fairness, Neutrality and Transparency in Data Analysis
    Julia Stoyanovich, Serge Abiteboul, and Gerome Miklau
    In Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016
  63. Workload-driven learning of Mallows mixtures with pairwise preference data
    Julia Stoyanovich, Lovro Ilijasic, and Haoyue Ping
    In Proceedings of the 19th International Workshop on Web and Databases, WebDB at SIGMOD 2016
  64. Towards a Distributed Infrastructure for Evolving Graph Analytics
    Vera Zaychik Moffitt, and Julia Stoyanovich
    In Proceedings of the 6th Temporal Web Analytics Workshop, TempWeb at WWW 2016
  65. The Elephant in the Room: Getting Value from Big Data
    Serge Abiteboul, Xin Luna Dong, Oren Etzioni, Divesh Srivastava, Gerhard Weikum, Julia Stoyanovich, and Fabian M. Suchanek
    In Proceedings of the 18th International Workshop on Web and Databases, WebDB at SIGMOD 2015
  66. Analyzing Crowd Rankings
    Julia Stoyanovich, Marie Jacob, and Xuemei Gong
    In Proceedings of the 18th International Workshop on Web and Databases, WebDB at SIGMOD 2015
  67. Data, Responsibly (Dagstuhl Seminar 16291)
    Serge Abiteboul, Gerome Miklau, Julia Stoyanovich, and Gerhard Weikum
    Dagstuhl Reports 2016
  68. Collaborative Access Control in WebdamLog
    Vera Zaychik Moffitt, Julia Stoyanovich, Serge Abiteboul, and Gerome Miklau
    In Proceedings of the 2015 International Conference on the Management of Data, SIGMOD 2015
  69. A System for Management and Analysis of Preference Data
    Marie Jacob, Benny Kimelfeld, and Julia Stoyanovich
    PVLDB 2014
  70. Understanding Local Structure in Ranked Datasets
    Julia Stoyanovich, Sihem Amer-Yahia, Susan B. Davidson, Marie Jacob, and Tova Milo
    In Proceedings of 6th Biennial Conference on Innovative Data Systems Research, CIDR 2013
  71. Learning Feature Weights from Positive Cases
    Sidath Gunawardena, Rosina O. Weber, and Julia Stoyanovich
    In Proceedings of 21st International Conference on Case-Based Reasoning Research and Development, ICCBR 2013
  72. Rule-based application development using Webdamlog
    Serge Abiteboul,  Antoine, Gerome Miklau, Julia Stoyanovich, and Jules Testard
    In Proceedings of the 2013 International Conference on the Management of Data, SIGMOD 2013
  73. Search and result presentation in scientific workflow repositories
    Susan B. Davidson, Xiaocheng Huang, Julia Stoyanovich, and Xiaojie Yuan
    In Proceedings of the Conference on Scientific and Statistical Database Management, SSDBM 2013
  74. Learning to explore scientific workflow repositories
    Julia Stoyanovich, Paramveer S. Dhillon, Susan B. Davidson, and Brian Lyons
    In Proceedings of the Conference on Scientific and Statistical Database Management, SSDBM 2013
  75. Viewing the Web as a Distributed Knowledge Base
    Serge Abiteboul,  Antoine, and Julia Stoyanovich
    In Proceedings of the 28th International Conference on Data Engineering, ICDE 2012
  76. AnnotCompute: Annotation-based exploration and meta-analysis of genomics experiments
    Jie Zheng, Julia Stoyanovich, Elisabetta Manduchi, Junmin Liu, and Christian J. Stoeckert Jr.
    Database 2011
  77. Putting Lipstick on Pig: Enabling Database-style Workflow Provenance
    Yael Amsterdamer, Susan B. Davidson, Daniel Deutch, Tova Milo, Julia Stoyanovich, and Val Tannen
    PVLDB 2011
  78. Keyword Search in Workflow Repositories with Access Control
    Susan B. Davidson, Soohyun Lee, and Julia Stoyanovich
    In Proceedings of the 5th Alberto Mendelzon International Workshop on Foundations of Data Management, AMW 2011
  79. Enabling Privacy in Provenance-Aware Workflow Systems
    Susan B. Davidson, Sanjeev Khanna, Val Tannen, Sudeepa Roy, Julia Stoyanovich, Yi Chen, and Tova Milo
    In Proceedings of the 5th Biennial Conference on Innovative Data Systems Research, CIDR 2011
  80. Making interval-based clustering rank-aware
    Julia Stoyanovich, Sihem Amer-Yahia, and Tova Milo
    In Proceedings of the 14th International Conference on Extending Database Technology, EDBT 2011
  81. Deriving probabilistic databases with inference ensembles
    Julia Stoyanovich, Susan B. Davidson, Tova Milo, and Val Tannen
    In Proceedings of the 27th International Conference on Data Engineering, ICDE 2011
  82. On provenance and privacy
    Susan B. Davidson, Sanjeev Khanna, Sudeepa Roy, Julia Stoyanovich, Val Tannen, and Yi Chen
    In Proceedings of the 14th International Conference on Database Theory, ICDT 2011
  83. SkylineSearch: semantic ranking and result visualization for PubMed
    Julia Stoyanovich, Mayur Lodha, William Mee, and Kenneth A. Ross
    In Proceedings of the 2011 International Conference on the Management of Data, SIGMOD 2011
  84. Semantic ranking and result visualization for life sciences publications
    Julia Stoyanovich, William Mee, and Kenneth A. Ross
    In Proceedings of the 26th International Conference on Data Engineering, ICDE 2010
  85. Rank-aware clustering of structured datasets
    Julia Stoyanovich, and Sihem Amer-Yahia
    In Proceedings of the 18th Conference on Information and Knowledge Management, CIKM 2009
  86. Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy
    Lucas Rosenblatt, Bernease Herman, Anastasia Holovenko, Wonkwon Lee, Joshua R. Loftus, Elizabeth Mckinnie, Taras Rumezhak, Andrii Stadnik, Bill Howe, and Julia Stoyanovich
    Proc. VLDB Endow. 2023
  87. MutaGeneSys: estimating individual disease susceptibility based on genome-wide SNP array data
    Julia Stoyanovich, and Itsik Pe’er
    Bioinformatics 2008
  88. Efficient network aware search in collaborative tagging sites
    Sihem Amer-Yahia, Michael Benedikt, Laks V. S. Lakshmanan, and Julia Stoyanovich
    PVLDB 2008
  89. Leveraging Tagging to Model User Interests in del.icio.us
    Julia Stoyanovich, Sihem Amer-Yahia, Cameron Marlow, and Cong Yu
    In Proceedings of the Spring Symposium on Social Information Processing 2008
  90. Schema polynomials and applications
    Kenneth A. Ross, and Julia Stoyanovich
    In Proceedings of the 11th International Conference on Extending Database Technology, EDBT 2008
  91. From del.icio.us to x.qui.site: recommendations in social tagging sites
    Sihem Amer-Yahia, Alban Galland, Julia Stoyanovich, and Cong Yu
    In Proceedings of the 2008 International Conference on the Management of Data, SIGMOD 2008
  92. EntityAthority: Semantically Enriched Graph-Based Authority Propagation
    Julia Stoyanovich, Srikanta J. Bedathur, Klaus Berberich, and Gerhard Weikum
    In Proceedings of the 10th International Workshop on the Web and Databases, WebDB at SIGMOD 2007
  93. A Faceted Query Engine Applied to Archaeology
    Kenneth A. Ross, Angel Janevski, and Julia Stoyanovich
    In Proceedings of the 31st International Conference on Very Large Data Bases, VLDB 2005
  94. Symmetric Relations and Cardinality-Bounded Multisets in Database Systems
    Kenneth A. Ross, and Julia Stoyanovich
    In Proceedings of the 30th International Conference on Very Large Data Bases, VLDB 2004
  95. A Faceted Query Engine Applied to Archaeology
    Kenneth A. Ross, Angel Janevski, and Julia Stoyanovich
    Internet Archaeology 2007
  96. TransFAT: Translating Fairness, Accountability, and Transparency into Data Science Practice
    Julia Stoyanovich
    In Proceedings of the 1st International Workshop on Processing Information Ethically, PIE at CAiSE 2019
  97. Towards sequenced semantics for evolving graphs
    Vera Zaychik Moffitt, and Julia Stoyanovich
    In Proceedings of the 20th International Conference on Extending Database Technology, EDBT 2017
  98. Follow the Data! Algorithmic Transparency Starts with Data Transparency
    Julia Stoyanovich, and Bill Howe
    The Ethical Machine Nov 2018
  99. MobilityMirror: Bias-Adjusted Transportation Datasets
    Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich, and Bill Howe
    In Big Social Data and Urban Computing - First Workshop, BiDU@VLDB 2018, Rio de Janeiro, Brazil, August 31, 2018, Revised Selected Papers Nov 2018
  100. What is AI?
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  101. What is AI? (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  102. What is AI? (Greek Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  103. Learning from data
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  104. Learning from data (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  105. Who lives, who dies, who decides?
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  106. Who lives, who dies, who decides? (Spanish Edition)
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  107. All about that bias
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  108. All about that bias (Spanish Edition
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  109. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  110. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  111. Mirror, Mirror
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  112. Mirror, Mirror (French Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  113. Mirror, Mirror (Spanish Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  114. Mirror, Mirror (Portugueze Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  115. Fairness and Friends
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2021
  116. Revealing Algorithmic Rankers
    Julia Stoyanovich, and Ellen P. Goodman
    Freedom to Tinker, Center for Information Technology Policy, Princeton University Aug 2016
  117. Analyzing Crowd Rankings
    Julia Stoyanovich, Marie Jacob, and Xuemei Gong
    In Proceedings of the 18th International Workshop on Web and Databases, Melbourne, VIC, Australia, May 31, 2015 Aug 2015
  118. Refining the Concept of a Nutritional Label for Data and Models
    Julia Stoyanovich, and Bill Howe
    Freedom to Tinker, Center for Information Technology Policy, Princeton University May 2018
  119. The Data, Responsibly Manifesto
    Serge Abiteboul, and Julia Stoyanovich
    ACM SIGMOD blog Nov 2015
  120. Search and Ranking in Semantically Rich Applications
    Julia Stoyanovich
    Nov 2010
  121. Temporal Regular Path Queries
    Marcelo Arenas, Pedro Bahamondes, Amir Aghasaedeghi, and Julia Stoyanovich
    In Proceedings of the 38th International Conference on Data Engineering, ICDE Nov 2022
  122. Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    In Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2022, Arlington, VA, USA, October 6-9, 2022 Nov 2022
  123. Disaggregated Interventions to Reduce Inequality
    Lucius Bynum, Joshua R. Loftus, and Julia Stoyanovich
    In EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5 - 9, 2021 Nov 2021
  124. Resume Format, LinkedIn pdfs and Other Unexpected Influences on AI Personality Prediction in Hiring: Results of an Audit
    Alene K. Rhea, Kelsey Markey, Lauren D’Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, and Julia Stoyanovich
    In Proceedings of the Fifth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) Nov 2022
  125. An External Stability Audit Framework to Test the Validity of Personality Prediction in AI Hiring
    Alene K. Rhea, Kelsey Markey, Lauren D’Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Falaah Arif Khan, and Julia Stoyanovich
    Data Mining and Knowledge Discovery, Special Issue on Bias and Fairness in AI Nov 2022
  126. COVID-19 Brings Data Equity Challenges to the Fore
    H. V. Jagadish, Julia Stoyanovich, and Bill Howe
    Digit. Gov. Res. Pract. Nov 2021
  127. Fairness in Ranking, Part I: Score-Based Ranking
    Meike Zehlike, Ke Yang, and Julia Stoyanovich
    ACM Computing Surveys Nov 2023
  128. Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems
    Meike Zehlike, Ke Yang, and Julia Stoyanovich
    ACM Computing Surveys Nov 2023
  129. Fairness-Aware Instrumentation of Preprocessing Pipelines for Machine Learning
    Ke Yang, Biao Huang, Julia Stoyanovich, and Sebastian Schelter
    In Proceedings of the Workshop on Human-In-the-Loop Data Analytics, HILDA at SIGMOD Nov 2020
  130. Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines
    Stefan Grafberger, Julia Stoyanovich, and Sebastian Schelter
    In CIDR 2021, 11th Conference on Innovative Data Systems Research, Online Proceedings Nov 2021
  131. Taming Technical Bias in Machine Learning Pipelines
    Sebastian Schelter, and Julia Stoyanovich
    IEEE Data Eng. Bull. Nov 2020
  132. Data Distribution Debugging in Machine Learning Pipelines
    Stefan Grafberger, Paul Groth, Julia Stoyanovich, and Sebastian Schelter
    The VLDB Journal — The International Journal on Very Large Data Bases (Special Issue on Data Science for Responsible Data Management Nov 2021
  133. Algorithmic Techniques for Necessary and Possible Winners
    Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, and Julia Stoyanovich
    ACM/IMS Trans. Data Sci. Jul 2021
  134. Causal Intersectionality and Fair Ranking
    Ke Yang, Joshua Loftus, and Julia Stoyanovich
    In Symposium on the Foundations of Responsible Computing FORC Jul 2021
  135. Comparing Apples and Oranges: Fairness and Diversity in Ranking (Invited Talk)
    Julia Stoyanovich
    In 24th International Conference on Database Theory, ICDT 2021, March 23-26, 2021, Nicosia, Cyprus Jul 2021
  136. Responsible Data Management
    Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, and Sebastian Schelter
    Communications of the ACM Jul 2022
  137. Teaching Responsible Data Science
    Julia Stoyanovich
    In Proceedings of the 1st ACM SIGMOD International Workshop on Data Systems Education: Bridging Education Practice with Education Research, DataEd@SIGMOD 2022, 17 June 2022, Philadelphia, PA, USA Jul 2022
  138. Teaching Responsible Data Science
    Armanda Lewis, and Julia Stoyanovich
    International Journal of Artificial Intelligence in Education (IJAIED) Jul 2021
  139. It’s Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy
    Andrew Bell, Ian Solano-Kamaiko, Oded Nov, and Julia Stoyanovich
    In Proceedings of the 5th Annual ACM Conference on Fairness, Accountability, and Transparency, FAccT Jul 2022
  140. Developing data capability with non-profit organisations using participatory methods
    Anthony McCosker, Xiaofang Yao, Kath Albury, Alexia Maddox, Jane Farmer, and Julia Stoyanovich
    Big Data & Society Jul 2022
  141. Counterfactuals for the Future
    Lucius E. J. Bynum, Joshua R. Loftus, and Julia Stoyanovich
    In Proceedings of the AAAI Conference on Artificial Intelligence Jul 2023
  142. Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    In Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2022, Arlington, VA, USA, October 6-9, 2022 Jul 2022
  143. We are AI: Taking Control of Technology
    Julia Stoyanovich, and Eric Corbett
    Center for Responsible AI, New York University Jul 2021