Julia Stoyanovich

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 125

Top Venues

Publications

Venetia Pliatsika, João Fonseca, Tilun Wang, Julia Stoyanovich
ShaRP: Explaining Rankings with Shapley Values. CoRR (2024)
Julia Stoyanovich, Rodrigo Kreis de Paula, Armanda Lewis, Chloe Zheng
Using Case Studies to Teach Responsible AI to Industry Practitioners. CoRR (2024)
Lucas Rosenblatt, Bernease Herman, Anastasia Holovenko, Wonkwon Lee, Joshua R. Loftus, Elizabeth McKinnie, Taras Rumezhak, Andrii Stadnik, Bill Howe, Julia Stoyanovich
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. SIGMOD Rec. 53 (1) (2024)
Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse. CoRR (2024)
Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. AAAI (2024)
Andrew Bell, João Fonseca, Carlo Abrate, Francesco Bonchi, Julia Stoyanovich
Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity. CoRR (2024)
Felix S. Campbell, Alon Silberstein, Julia Stoyanovich, Yuval Moskovitch
Query Refinement for Diverse Top-k Selection. CoRR (2024)
Amir Aghasadeghi, Jan Van den Bussche, Julia Stoyanovich
Temporal graph patterns by timed automata. VLDB J. 33 (1) (2024)
Felix S. Campbell, Alon Silberstein, Julia Stoyanovich, Yuval Moskovitch
Query Refinement for Diverse Top-k Selection. Proc. ACM Manag. Data 2 (3) (2024)
Andrew Bell, Julia Stoyanovich
Making Transparency Influencers: A Case Study of an Educational Approach to Improve Responsible AI Practices in News and Media. CHI Extended Abstracts (2024)
Andrew Bell, João Fonseca, Julia Stoyanovich
The Game Of Recourse: Simulating Algorithmic Recourse over Time to Improve Its Reliability and Fairness. SIGMOD Conference Companion (2024)
Denys Herasymuk, Falaah Arif Khan, Julia Stoyanovich
Responsible Model Selection with Virny and VirnyView. SIGMOD Conference Companion (2024)
João Fonseca, Andrew Bell, Carlo Abrate, Francesco Bonchi, Julia Stoyanovich
Setting the Right Expectations: Algorithmic Recourse Over Time. CoRR (2023)
João Fonseca, Andrew Bell, Carlo Abrate, Francesco Bonchi, Julia Stoyanovich
Setting the Right Expectations: Algorithmic Recourse Over Time. EAAMO (2023)
Jinyang Li, Alon Silberstein, Yuval Moskovitch, Julia Stoyanovich, H. V. Jagadish
ERICA: Query Refinement for Diversity Constraint Satisfaction. Proc. VLDB Endow. 16 (12) (2023)
Vítor Ribeiro, Eduardo H. M. Pena, Raphael de Freitas Saldanha, Reza Akbarinia, Patrick Valduriez, Falaah Arif Khan, Julia Stoyanovich, Fábio Porto
Subset Modelling: A Domain Partitioning Strategy for Data-efficient Machine-Learning. SBBD (2023)
Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu
Tutorials at The Web Conference 2023. WWW (Companion Volume) (2023)
Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. CoRR (2023)
Jinyang Li, Yuval Moskovitch, Julia Stoyanovich, H. V. Jagadish
Query Refinement for Diversity Constraint Satisfaction. Proc. VLDB Endow. 17 (2) (2023)
Falaah Arif Khan, Julia Stoyanovich
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction. CoRR (2023)
Meike Zehlike, Ke Yang, Julia Stoyanovich
Fairness in Ranking, Part I: Score-Based Ranking. ACM Comput. Surv. 55 (6) (2023)
Falaah Arif Khan, Denys Herasymuk, Julia Stoyanovich
On Fairness and Stability: Is Estimator Variance a Friend or a Foe? CoRR (2023)
Meike Zehlike, Ke Yang, Julia Stoyanovich
Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems. ACM Comput. Surv. 55 (6) (2023)
Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich
Counterfactuals for the Future. AAAI (2023)
Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, Sebastian Schelter
Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making. ICDE (2023)
Haoyue Ping, Julia Stoyanovich
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. Proc. ACM Manag. Data 1 (1) (2023)
Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Herasymova, Lucas Rosenblatt, Julia Stoyanovich
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. CoRR (2023)
Julia Stoyanovich
Responsible Data Management. SEBD (2023)
Andrew Bell, Lucius Bynum, Nazarii Drushchak, Tetiana Zakharchenko, Lucas Rosenblatt, Julia Stoyanovich
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. FAccT (2023)
Mona Sloane, Ian Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, Julia Stoyanovich
Introducing contextual transparency for automated decision systems. Nat. Mac. Intell. 5 (3) (2023)
Lucas Rosenblatt, Bernease Herman, Anastasia Holovenko, Wonkwon Lee, Joshua R. Loftus, Elizabeth Mckinnie, Taras Rumezhak, Andrii Stadnik, Bill Howe, Julia Stoyanovich
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. Proc. VLDB Endow. 16 (11) (2023)
Daniel Dominguez Figaredo, Julia Stoyanovich
Responsible AI literacy: A stakeholder-first approach. Big Data Soc. 10 (1) (2023)
Julia Stoyanovich, Meike Zehlike, Ke Yang
Fairness in Ranking: From Values to Technical Choices and Back. SIGMOD Conference Companion (2023)
Andrew Bell, Oded Nov, Julia Stoyanovich
The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization's Algorithms. CHI Extended Abstracts (2023)
Xin Luna Dong, Bo Li, Julia Stoyanovich, Anthony Kum Hoe Tung, Gerhard Weikum, Alon Y. Halevy, Wang-Chiew Tan
Personal Data for Personal Use: Vision or Reality? SIGMOD Conference Companion (2023)
Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich
Counterfactuals for the Future. CoRR (2022)
Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Julia Stoyanovich
Resume Format, LinkedIn URLs and Other Unexpected Influences on AI Personality Prediction in Hiring: Results of an Audit. AIES (2022)
Marcelo Arenas, Pedro Bahamondes, Amir Aghasadeghi, Julia Stoyanovich
Temporal Regular Path Queries. ICDE (2022)
Anthony McCosker, Xiaofang Yao, Kath Albury, Alexia Maddox, Jane Farmer, Julia Stoyanovich
Developing data capability with non-profit organisations using participatory methods. Big Data Soc. 9 (1) (2022)
Falaah Arif Khan, Eleni Manis, Julia Stoyanovich
Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. CoRR (2022)
Julia Stoyanovich, Serge Abiteboul, Bill Howe, H. V. Jagadish, Sebastian Schelter
Responsible data management. Commun. ACM 65 (6) (2022)
Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Julia Stoyanovich
External Stability Auditing to Test the Validity of Personality Prediction in AI Hiring. CoRR (2022)
H. V. Jagadish, Julia Stoyanovich, Bill Howe
The Many Facets of Data Equity. ACM J. Data Inf. Qual. 14 (4) (2022)
Jun Yuan, Julia Stoyanovich, Aritra Dasgupta
Rankers, Rankees, & Rankings: Peeking into the Pandora's Box from a Socio-Technical Perspective. CoRR (2022)
Andrew Bell, Ian Solano-Kamaiko, Oded Nov, Julia Stoyanovich
It's Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy. FAccT (2022)
Stefan Grafberger, Paul Groth, Julia Stoyanovich, Sebastian Schelter
Data distribution debugging in machine learning pipelines. VLDB J. 31 (5) (2022)
Alene K. Rhea, Kelsey Markey, Lauren D'Arinzo, Hilke Schellmann, Mona Sloane, Paul Squires, Falaah Arif Khan, Julia Stoyanovich
An external stability audit framework to test the validity of personality prediction in AI hiring. Data Min. Knowl. Discov. 36 (6) (2022)
Andrew Bell, Oded Nov, Julia Stoyanovich
Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance. CoRR (2022)
Armanda Lewis, Julia Stoyanovich
Teaching Responsible Data Science: Charting New Pedagogical Territory. Int. J. Artif. Intell. Educ. 32 (3) (2022)
Lucas Rosenblatt, Joshua Allen, Julia Stoyanovich
Spending Privacy Budget Fairly and Wisely. CoRR (2022)
Lucas Rosenblatt, Anastasia Holovenko, Taras Rumezhak, Andrii Stadnik, Bernease Herman, Julia Stoyanovich, Bill Howe
Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. CoRR (2022)
Falaah Arif Khan, Eleni Manis, Julia Stoyanovich
Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. EAAMO (2022)
Julia Stoyanovich
Teaching Responsible Data Science. DataEd@SIGMOD (2022)
Amir Pouya Aghasadeghi, Jan Van den Bussche, Julia Stoyanovich
Temporal graph patterns by timed automata. CoRR (2022)
Lucius Bynum, Joshua R. Loftus, Julia Stoyanovich
Disaggregated Interventions to Reduce Inequality. EAAMO (2021)
Meike Zehlike, Ke Yang, Julia Stoyanovich
Fairness in Ranking: A Survey. CoRR (2021)
Haoyue Ping, Julia Stoyanovich
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. CoRR (2021)
Stefan Grafberger, Julia Stoyanovich, Sebastian Schelter
Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. CIDR (2021)
Falaah Arif Khan, Eleni Manis, Julia Stoyanovich
Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy. CoRR (2021)
Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, Julia Stoyanovich
Algorithmic Techniques for Necessary and Possible Winners. Trans. Data Sci. 2 (3) (2021)
Ke Yang, Joshua R. Loftus, Julia Stoyanovich
Causal Intersectionality and Fair Ranking. FORC (2021)
Stefan Grafberger, Shubha Guha, Julia Stoyanovich, Sebastian Schelter
MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. SIGMOD Conference (2021)
Julia Stoyanovich
Comparing Apples and Oranges: Fairness and Diversity in Ranking (Invited Talk). ICDT (2021)
Marcelo Arenas, Pedro Bahamondes, Julia Stoyanovich
Temporal Regular Path Queries: Syntax, Semantics, and Complexity. CoRR (2021)
H. V. Jagadish, Julia Stoyanovich, Bill Howe
The Many Facets of Data Equity. EDBT/ICDT Workshops (2021)
Anna Jobin, Kingson Man, Antonio Damasio, Georgios Kaissis, Rickmer Braren, Julia Stoyanovich, Jay J. Van Bavel, Tessa V. West, Brent D. Mittelstadt, Jason Eshraghian, Marta R. Costa-jussà, Asaf Tzachor, Aimun A. B. Jamjoom, Mariarosaria Taddeo, Edoardo Sinibaldi, Yipeng Hu, Miguel A. Luengo-Oroz
AI reflections in 2020. Nat. Mach. Intell. 3 (1) (2021)
Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich
Impact Remediation: Optimal Interventions to Reduce Inequality. CoRR (2021)
H. V. Jagadish, Julia Stoyanovich, Bill Howe
COVID-19 Brings Data Equity Challenges to the Fore. Digit. Gov. Res. Pract. 2 (2) (2021)
Vishal Chakraborty, Theo Delemazure, Benny Kimelfeld, Phokion G. Kolaitis, Kunal Relia, Julia Stoyanovich
Algorithmic Techniques for Necessary and Possible Winners. CoRR (2020)
Sebastian Schelter, Julia Stoyanovich
Taming Technical Bias in Machine Learning Pipelines. IEEE Data Eng. Bull. 43 (4) (2020)
Julia Stoyanovich, Bill Howe, H. V. Jagadish
Responsible Data Management. Proc. VLDB Endow. 13 (12) (2020)
Ke Yang, Joshua R. Loftus, Julia Stoyanovich
Causal intersectionality for fair ranking. CoRR (2020)
Julia Stoyanovich, Jay J. Van Bavel, Tessa V. West
The imperative of interpretable machines. Nat. Mach. Intell. 2 (4) (2020)
Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld
Supporting Hard Queries over Probabilistic Preferences. CoRR (2020)
Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. EDBT (2020)
Haoyue Ping, Julia Stoyanovich, Benny Kimelfeld
Supporting Hard Queries over Probabilistic Preferences. Proc. VLDB Endow. 13 (7) (2020)
Amir Aghasadeghi, Vera Zaychik Moffitt, Sebastian Schelter, Julia Stoyanovich
Zooming Out on an Evolving Graph. EDBT (2020)
Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich
Towards Responsible Data-driven Decision Making in Score-Based Systems. IEEE Data Eng. Bull. 42 (3) (2019)
Serge Abiteboul, Julia Stoyanovich
Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation. ACM J. Data Inf. Qual. 11 (3) (2019)
Julia Stoyanovich
TransFAT: Translating Fairness, Accountably and Transparency into Data Science Practice. PIE@CAiSE (2019)
Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich
Balanced Ranking with Diversity Constraints. CoRR (2019)
Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich
Balanced Ranking with Diversity Constraints. IJCAI (2019)
H. V. Jagadish, Francesco Bonchi, Tina Eliassi-Rad, Lise Getoor, Krishna P. Gummadi, Julia Stoyanovich
The Responsibility Challenge for Data. SIGMOD Conference (2019)
Serge Abiteboul, Julia Stoyanovich
Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation. CoRR (2019)
Chenkai Sun, Abolfazl Asudeh, H. V. Jagadish, Bill Howe, Julia Stoyanovich
MithraLabel: Flexible Dataset Nutritional Labels for Responsible Data Science. CIKM (2019)
Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. CoRR (2019)
Yifan Guan, Abolfazl Asudeh, Pranav Mayuram, H. V. Jagadish, Julia Stoyanovich, Gerome Miklau, Gautam Das
MithraRanking: A System for Responsible Ranking Design. SIGMOD Conference (2019)
Abolfazl Asudeh, H. V. Jagadish, Julia Stoyanovich, Gautam Das
Designing Fair Ranking Schemes. SIGMOD Conference (2019)
Julia Stoyanovich, Armanda Lewis
Teaching Responsible Data Science: Charting New Pedagogical Territory. CoRR (2019)
Julia Stoyanovich, Bill Howe
Nutritional Labels for Data and Models. IEEE Data Eng. Bull. 42 (3) (2019)
Julia Stoyanovich, Matthew Gilbride, Vera Zaychik Moffitt
Zooming in on NYC Taxi Data with Portal. BiDu-Posters@VLDB (2018)
Julia Stoyanovich, Bill Howe, H. V. Jagadish
Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management. SIGMOD Conference (2018)
Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, Julia Stoyanovich
On Obtaining Stable Rankings. Proc. VLDB Endow. 12 (3) (2018)
Benny Kimelfeld, Phokion G. Kolaitis, Julia Stoyanovich
Computational Social Choice Meets Databases. CoRR (2018)
Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau
A Nutritional Label for Rankings. SIGMOD Conference (2018)
Uzi Cohen, Batya Kenig, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich
A Query Engine for Probabilistic Preferences. SIGMOD Conference (2018)
Amir Aghasadeghi, Julia Stoyanovich
Generating Evolving Property Graphs with Attribute-Aware Preferential Attachment. DBTest@SIGMOD (2018)
Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, Julia Stoyanovich
On Obtaining Stable Rankings. CoRR (2018)
Batya Kenig, Lovro Ilijasic, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich
Probabilistic Inference Over Repeated Insertion Models. AAAI (2018)
Julia Stoyanovich, Ke Yang, H. V. Jagadish
Online Set Selection with Fairness and Diversity Constraints. EDBT (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Julia Stoyanovich