Julia Stoyanovich

Professor of Computer Science & Engineering, and of Data Science, Associate Dean of AI Initiatives, and Director of R/AI – stoyanovich (at) nyu.edu

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Julia is Professor of Computer Science & Engineering at the NYU Tandon School of Engineering, Professor of Data Science at the Courant Institute School of Mathematics, Computing, and Data Science, Associate Dean of AI Initiatives at NYU Tandon, and Director of the Center for Responsible AI (R/AI). Julia’s goal is to make “Responsible AI” synonymous with “AI”. She works toward this goal through academic research, education and training, and technology policy, and by speaking about the benefits and harms of AI with practitioners, policymakers, and members of the public.

Julia’s research interests include data management and AI systems, AI ethics, and legal compliance. In addition to academic publications, she has written for The New York Times, The Wall Street Journal, and Le Monde. Julia teaches courses on responsible data science and AI to students, practitioners, and the general public, and develops educational programs for industry and government. 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 U.S. 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 the recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE), an NSF CAREER Award, and is a Senior Member of the ACM.

Selected publications

  1. Seasoning Data Modeling Education with GARLIC: A Participatory Co-Design Framework
    Viktoriia Makovska, Ihor Michurin, Mariia Tokhtamysh, George Fletcher, and Julia Stoyanovich
    Proceedings of the DataEd Workshop, co-located with EDBT/ICDT 2026
  2. Memory Undone: Between Knowing and Not Knowing in Data Systems
    Viktoriia Makovska, George Fletcher, Julia Stoyanovich, and Tetiana Zakharchenko
    CoRR 2026
  3. SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems
    Rima Hazra, Bikram Ghuku, Ilona Marchenko, Yaroslava Tokarieva, Sayan Layek, Somnath Banerjee, Julia Stoyanovich, and Mykola Pechenizkiy
    2026
  4. Estimating the impact of the Russian invasion on the displacement of graduating high school students in Ukraine
    Tetiana Zakharchenko, Andrew Bell, Nazarii Drushchak, Oleksandra Konopatska, Falaah Arif Khan, and Julia Stoyanovich
    Nature Humanities and Social Sciences Communications 2025
  5. Explanation Multiplicity in SHAP: Characterization and Assessment
    Hyunseung Hwang, Seungeun Lee, Lucas Rosenblatt, Steven Euijong Whang, and Julia Stoyanovich
    CoRR 2026
  6. ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations
    Joao Fonseca, and Julia Stoyanovich
    2026
  7. VirnyFlow: A Design Space for Responsible Model Development
    Denys Herasymuk, Nazar Protsiv, and Julia Stoyanovich
    CoRR 2025
  8. From Benchmarking to Understanding FairML
    Mykola Pechenizkiy, Hilde Weerts, Cassio Campos, Yuya Sasaki, and Julia Stoyanovich
    In Proceedings of ECAI 2025
  9. Promoting transparency in AI for biomedical and behavioral research
    Tina Hernandez-Boussard, Aaron Y. Lee, Julia Stoyanovich, and Laura Biven
    Nature Medicine 2025
  10. Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation
    Falaah Arif Khan, Denys Herasymuk, Nazar Protsiv, and Julia Stoyanovich
    Proc. VLDB Endow. 2025
  11. ShaRP: Explaining Rankings and Preferences with Shapley Values
    Venetia Pliatsika, João Fonseca, Kateryna Akhynko, Ivan Shevchenko, and Julia Stoyanovich
    Proc. VLDB Endow. 2025
  12. SHAP-based Explanations are Sensitive to Feature Representation
    Hyunseung Hwang, Andrew Bell, Joao Fonseca, Venetia Pliatsika, Julia Stoyanovich, and Steven Euijong Whang
    In Conference on Fairness, Accountability, and Transparency, ACM FAccT 2025
  13. SafeNudge: Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs
    Joao Fonseca, Andrew Bell, and Julia Stoyanovich
    In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP) Nov 2025
  14. CREDAL: Close Reading of Data Models
    George Fletcher, Olha Nahurna, Matvii Prytula, and Julia Stoyanovich
    In Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA) at ACM SIGMOD Nov 2025
  15. ONION: A Multi-Layered Framework for Participatory ER Design
    Viktoriia Makovska, George Fletcher, and Julia Stoyanovich
    In Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA) at ACM SIGMOD Nov 2025
  16. Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
    Shlomi Hod, Lucas Rosenblatt, and Julia Stoyanovich
    The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), Datasets & Benchmarks Track Nov 2025
  17. Rodeo: Making Refinements for Diverse Top-k Queries
    Felix S. Campbell, Julia Stoyanovich, and Yuval Moskovitch
    Proc. VLDB Endow. Nov 2024
  18. A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
    Lucius E. J. Bynum, Joshua R. Loftus, and Julia Stoyanovich
    In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI 2024, Jeju, South Korea Nov 2024
  19. Responsible Model Selection with Virny and VirnyView
    Denys Herasymuk, Falaah Arif Khan, and Julia Stoyanovich
    In Companion of the International Conference on Management of Data, SIGMOD/PODS, Santiago, Chile Nov 2024
  20. 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
    SIGMOD Rec. Nov 2024
  21. 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 ACM Conference on Fairness, Accountability, and Transparency, FAccT, Chicago, IL, USA Nov 2023
  22. Responsible AI literacy: A stakeholder-first approach
    Daniel Dominguez, and Julia Stoyanovich
    Big Data and Society Nov 2023
  23. 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 Nov 2023
  24. How Much Effort Is Enough? Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity
    Andrew Bell, Joao Fonseca, Carlo Abrate, Francesco Bonchi, and Julia Stoyanovich
    In Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO Nov 2025
  25. Query Refinement for Diversity Constraint Satisfaction
    Jinyang Li, Yuval Moskovitch, Julia Stoyanovich, and H. V. Jagadish
    Proc. VLDB Endow. Nov 2023
  26. Query Refinement for Diverse Top-k Selection
    Felix S. Campbell, Alon Silberstein, Julia Stoyanovich, and Yuval Moskovitch
    Proc. ACM Manag. Data Nov 2024
  27. ERICA: Query Refinement for Diversity Constraint Satisfaction
    Jinyang Li, Alon Silberstein, Yuval Moskovitch, Julia Stoyanovich, and H. V. Jagadish
    Proc. VLDB Endow. Nov 2023
  28. 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 Nov 2023
  29. Responsible Data Management
    Julia Stoyanovich, Bill Howe, and HV Jagadish
    Proceedings of the VLDB Endowment Nov 2020
  30. Spending Privacy Budget Fairly and Wisely
    Lucas Rosenblatt, Joshua Allen, and Julia Stoyanovich
    Theory and Practice of Differential Privacy (@ICML) Nov 2022
  31. 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 Nov 2023
  32. The Imperative of Interpretable Machines
    Julia Stoyanovich, Jay J. Van Bavel, and Tessa V. West
    Nature Machine Intelligence Nov 2020
  33. Introducing contextual transparency for automated decision systems
    Mona Sloane, Ian Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, and Julia Stoyanovich
    Nature Machine Intelligence Nov 2023
  34. The Many Facets of Data Equity
    H.V. Jagadish, Julia Stoyanovich, and Bill Howe
    ACM Journal of Data and Information Quality Nov 2023
  35. Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences
    Haoyue Ping, and Julia Stoyanovich
    Proc. ACM Manag. Data Nov 2023
  36. Supporting Hard Queries over Probabilistic Preferences
    Haoyue Ping, Julia Stoyanovich, and Benny Kimelfeld
    PVLDB Nov 2020
  37. Counterfactuals for the Future
    Lucius E. J. Bynum, Joshua R. Loftus, and Julia Stoyanovich
    Nov 2023
  38. 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 Nov 2022
  39. Using Case Studies to Teach Responsible AI to Industry Practitioners
    Julia Stoyanovich, Rodrigo Kreis Paula, Armanda Lewis, and Chloe Zheng
    In Proceedings of the AAAI Conference on Artificial Intelligence Nov 2025
  40. Making Transparency Advocates: An Educational Approach Towards Better Algorithmic Transparency in Practice
    Andrew Bell, and Julia Stoyanovich
    In Proceedings of the AAAI Conference on Artificial Intelligence Nov 2025
  41. We Are AI: Taking Control of Technology
    Julia Stoyanovich, Armanda Lewis, Eric Corbett, Lucius Bynum, Lucas Rosenblatt, and Falaah Arif Khan
    In Proceedings of the AAAI Conference on Artificial Intelligence Nov 2025
  42. Rankers, Rankees, & Rankings: Peeking into the Pandora’s Box from a Socio-Technical Perspective
    Jun Yuan, Julia Stoyanovich, and Aritra Dasgupta
    CoRR Nov 2022
  43. 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 Nov 2021
  44. Translational Tutorial: Fairness and Friends
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    In 4th Annual Conference on Fairness, Accountability, and Transparency, ACM FAccT Nov 2021
  45. 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 Nov 2023
  46. 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 Nov 2023
  47. 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 Nov 2023
  48. 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 Nov 2023
  49. Temporal graph patterns by timed automata
    Amir Pouya Aghasadeghi, Jan Van Bussche, and Julia Stoyanovich
    VLDB Journal Nov 2023
  50. Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance
    Andrew Bell, Oded Nov, and Julia Stoyanovich
    Data & Policy Nov 2023
  51. 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 Nov 2020
  52. 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 Nov 2020
  53. Towards Responsible Data-driven Decision Making in Score-Based Systems
    Abolfazl Asudeh, H. V. Jagadish, and Julia Stoyanovich
    IEEE Data Eng. Bull. Nov 2019
  54. Nutritional Labels for Data and Models
    Julia Stoyanovich, and Bill Howe
    IEEE Data Eng. Bull. Nov 2019
  55. 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 Nov 2019
  56. 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 Nov 2019
  57. Balanced Ranking with Diversity Constraints
    Ke Yang, Vasilis Gkatzelis, and Julia Stoyanovich
    In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI Nov 2019
  58. 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 Nov 2019
  59. 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 Nov 2019
  60. 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 Nov 2019
  61. 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 Nov 2018
  62. On Obtaining Stable Rankings
    Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, and Julia Stoyanovich
    PVLDB Nov 2018
  63. Panel: A Debate on Data and Algorithmic Ethics
    Julia Stoyanovich, Bill Howe, H. V. Jagadish, and Gerome Miklau
    PVLDB Nov 2018
  64. 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 Nov 2018
  65. 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 Nov 2018
  66. 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 Nov 2018
  67. 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 Nov 2018
  68. 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 Nov 2018
  69. 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 Nov 2018
  70. 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 Nov 2018
  71. 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 Nov 2018
  72. 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 Nov 2018
  73. Diversity in Big Data: A Review
    Marina Drosou, H. V. Jagadish, Evaggelia Pitoura, and Julia Stoyanovich
    Big Data Nov 2017
  74. 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 Nov 2017
  75. 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
    Nov 2011
  76. Social Behavior Analysis and Inferring Social Networks for a Recommendation System
    Sihem Amer-Yahia, Evgeniy Gabrilovic, Bo Pang, Julia Stoyanovich, and Cong Yu
    Nov 2011
  77. Temporal graph algebra
    Vera Zaychik Moffitt, and Julia Stoyanovich
    In Proceedings of The 16th International Symposium on Database Programming Languages, DBPL Nov 2017
  78. 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 Nov 2017
  79. 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 Nov 2017
  80. 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 Nov 2017
  81. Measuring Fairness in Ranked Outputs
    Ke Yang, and Julia Stoyanovich
    In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, SSDBM Nov 2017
  82. Synthetic Data for Social Good
    Bill Howe, Julia Stoyanovich, Haoyue Ping, Bernease Herman, and Matt Gee
    Proceedings of Data for Good Exchange D4GX Nov 2017
  83. 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 Nov 2016
  84. 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 Nov 2016
  85. 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 Nov 2016
  86. 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 Nov 2015
  87. Analyzing Crowd Rankings
    Julia Stoyanovich, Marie Jacob, and Xuemei Gong
    In Proceedings of the 18th International Workshop on Web and Databases, WebDB at SIGMOD Nov 2015
  88. Data, Responsibly (Dagstuhl Seminar 16291)
    Serge Abiteboul, Gerome Miklau, Julia Stoyanovich, and Gerhard Weikum
    Dagstuhl Reports Nov 2016
  89. 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 Nov 2015
  90. A System for Management and Analysis of Preference Data
    Marie Jacob, Benny Kimelfeld, and Julia Stoyanovich
    PVLDB Nov 2014
  91. 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 Nov 2013
  92. 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 Nov 2013
  93. 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 Nov 2013
  94. 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 Nov 2013
  95. 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 Nov 2013
  96. 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 Nov 2012
  97. AnnotCompute: Annotation-based exploration and meta-analysis of genomics experiments
    Jie Zheng, Julia Stoyanovich, Elisabetta Manduchi, Junmin Liu, and Christian J. Stoeckert Jr.
    Database Nov 2011
  98. Putting Lipstick on Pig: Enabling Database-style Workflow Provenance
    Yael Amsterdamer, Susan B. Davidson, Daniel Deutch, Tova Milo, Julia Stoyanovich, and Val Tannen
    PVLDB Nov 2011
  99. 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 Nov 2011
  100. 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 Nov 2011
  101. 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 Nov 2011
  102. 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 Nov 2011
  103. 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 Nov 2011
  104. 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 Nov 2011
  105. 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 Nov 2010
  106. Rank-aware clustering of structured datasets
    Julia Stoyanovich, and Sihem Amer-Yahia
    In Proceedings of the 18th Conference on Information and Knowledge Management, CIKM Nov 2009
  107. 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. Nov 2023
  108. MutaGeneSys: estimating individual disease susceptibility based on genome-wide SNP array data
    Julia Stoyanovich, and Itsik Pe’er
    Bioinformatics Nov 2008
  109. Efficient network aware search in collaborative tagging sites
    Sihem Amer-Yahia, Michael Benedikt, Laks V. S. Lakshmanan, and Julia Stoyanovich
    PVLDB Nov 2008
  110. 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 Nov 2008
  111. Schema polynomials and applications
    Kenneth A. Ross, and Julia Stoyanovich
    In Proceedings of the 11th International Conference on Extending Database Technology, EDBT Nov 2008
  112. 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 Nov 2008
  113. 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 Nov 2007
  114. 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 Nov 2005
  115. 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 Nov 2004
  116. A Faceted Query Engine Applied to Archaeology
    Kenneth A. Ross, Angel Janevski, and Julia Stoyanovich
    Internet Archaeology Nov 2007
  117. 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 Nov 2019
  118. Towards sequenced semantics for evolving graphs
    Vera Zaychik Moffitt, and Julia Stoyanovich
    In Proceedings of the 20th International Conference on Extending Database Technology, EDBT Nov 2017
  119. Follow the Data! Algorithmic Transparency Starts with Data Transparency
    Julia Stoyanovich, and Bill Howe
    The Ethical Machine Nov 2018
  120. 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
  121. What is AI?
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  122. What is AI? (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  123. What is AI? (Ukrainian Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2024
  124. Learning from data (Ukrainian Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2024
  125. Who lives? Who dies? Who decides? (Ukrainian Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2024
  126. All about that bias (Ukrainian Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2024
  127. We are AI (Ukrainian Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2024
  128. What is AI? (Greek Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  129. Learning from data
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  130. Learning from data (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  131. Who lives, who dies, who decides?
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  132. Who lives, who dies, who decides? (Spanish Edition)
    Julia Stoyanovich, Mona Sloane, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  133. All about that bias
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  134. All about that bias (Spanish Edition)
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  135. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  136. We are AI
    Julia Stoyanovich, and Falaah Arif Khan
    We are AI Comic Series Nov 2021
  137. Mirror, Mirror
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  138. Mirror, Mirror (French Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  139. Mirror, Mirror (Spanish Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  140. Mirror, Mirror (Portugueze Edition)
    Falaah Arif Khan, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2020
  141. Fairness and Friends
    Falaah Arif Khan, Eleni Manis, and Julia Stoyanovich
    Data, Responsibly Comic Series Nov 2021
  142. Revealing Algorithmic Rankers
    Julia Stoyanovich, and Ellen P. Goodman
    Freedom to Tinker, Center for Information Technology Policy, Princeton University Aug 2016
  143. 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
  144. 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
  145. The Data, Responsibly Manifesto
    Serge Abiteboul, and Julia Stoyanovich
    ACM SIGMOD blog Nov 2015
  146. Search and Ranking in Semantically Rich Applications
    Julia Stoyanovich
    Nov 2010
  147. 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
  148. 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
  149. 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
  150. 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
  151. 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
  152. COVID-19 Brings Data Equity Challenges to the Fore
    H. V. Jagadish, Julia Stoyanovich, and Bill Howe
    Digit. Gov. Res. Pract. Nov 2021
  153. Fairness in Ranking, Part I: Score-Based Ranking
    Meike Zehlike, Ke Yang, and Julia Stoyanovich
    ACM Computing Surveys Nov 2023
  154. Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems
    Meike Zehlike, Ke Yang, and Julia Stoyanovich
    ACM Computing Surveys Nov 2023
  155. 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
  156. 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
  157. Taming Technical Bias in Machine Learning Pipelines
    Sebastian Schelter, and Julia Stoyanovich
    IEEE Data Eng. Bull. Nov 2020
  158. 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
  159. 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
  160. Causal Intersectionality and Fair Ranking
    Ke Yang, Joshua Loftus, and Julia Stoyanovich
    In Symposium on the Foundations of Responsible Computing FORC Jul 2021
  161. 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
  162. Responsible Data Management
    Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, and Sebastian Schelter
    Communications of the ACM Jul 2022
  163. 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
  164. Teaching Responsible Data Science
    Armanda Lewis, and Julia Stoyanovich
    International Journal of Artificial Intelligence in Education (IJAIED) Jul 2022
  165. 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
  166. Making Transparency Influencers: A Case Study of an Educational Approach to Improve Responsible AI Practices in News and Media
    Andrew Bell, and Julia Stoyanovich
    In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, CHI EA 2024, Honolulu, HI, USA, May 11-16, 2024 Jul 2024
  167. 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
  168. 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
  169. We are AI: Taking Control of Technology
    Julia Stoyanovich, and Eric Corbett
    Center for Responsible AI, New York University Jul 2021
  170. A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy
    Lucas Rosenblatt, Julia Stoyanovich, and Christopher Musco
    In Thirty-Eighth AAAI Conference on Artificial Intelligence Jul 2024
  171. The Game Of Recourse: Simulating Algorithmic Recourse over Time to Improve Its Reliability and Fairness
    Andrew Bell, João Fonseca, and Julia Stoyanovich
    In Companion of the 2024 International Conference on Management of Data, SIGMOD/PODS 2024, Santiago AA, Chile, June 9-15, 2024 Jul 2024
  172. On Fairness and Stability: Is Estimator Variance a Friend or a Foe?
    Falaah Arif Khan, Denys Herasymuk, and Julia Stoyanovich
    CoRR Jul 2023