Symmetric Relations and Cardinality-Bounded Multisets in Database Systems. - Kenneth A. Ross; Julia Stoyanovich (VLDB, 2004)

A Faceted Query Engine Applied to Archaeology. - Kenneth A. Ross; Angel Janevski; Julia Stoyanovich (VLDB, 2005)

EntityAuthority: Semantically Enriched Graph-Based Authority Propagation. - Julia Stoyanovich; Srikanta J. Bedathur; Klaus Berberich; Gerhard Weikum (WebDB, 2007)

Leveraging Tagging to Model User Interests in del.icio.us. - Julia Stoyanovich; Sihem Amer-Yahia; Cameron Marlow; Cong Yu 001 (AAAI Spring Symposium: Social Information Processing, 2008)

Schema polynomials and applications. - Kenneth A. Ross; Julia Stoyanovich (EDBT, 2008)

From del.icio.us to x.qui.site: recommendations in social tagging sites. - Sihem Amer-Yahia; Alban Galland; Julia Stoyanovich; Cong Yu 001 (SIGMOD Conference, 2008)

MutaGeneSys: estimating individual disease susceptibility based on genome-wide SNP array data. - Julia Stoyanovich; Itsik Pe'er (Bioinform., 2008)

Efficient network aware search in collaborative tagging sites. - Sihem Amer-Yahia; Michael Benedikt; Laks V. S. Lakshmanan; Julia Stoyanovich (Proc. VLDB Endow., 2008)

Rank-aware clustering of structured datasets. - Julia Stoyanovich; Sihem Amer-Yahia (CIKM, 2009)

Semantic ranking and result visualization for life sciences publications. - Julia Stoyanovich; William Mee; Kenneth A. Ross (ICDE, 2010)

Keyword Search in Workflow Repositories with Access Control. - Susan B. Davidson; Soohyun Lee; Julia Stoyanovich (AMW, 2011)

Enabling Privacy in Provenance-Aware Workflow Systems. - Susan B. Davidson; Sanjeev Khanna; Val Tannen; Sudeepa Roy 001; Yi Chen 001; Tova Milo; Julia Stoyanovich (CIDR, 2011)

Making interval-based clustering rank-aware. - Julia Stoyanovich; Sihem Amer-Yahia; Tova Milo (EDBT, 2011)

Deriving probabilistic databases with inference ensembles. - Julia Stoyanovich; Susan B. Davidson; Tova Milo; Val Tannen (ICDE, 2011)

On provenance and privacy. - Susan B. Davidson; Sanjeev Khanna; Sudeepa Roy 001; Julia Stoyanovich; Val Tannen; Yi Chen 001 (ICDT, 2011)

SkylineSearch: semantic ranking and result visualization for pubmed. - Julia Stoyanovich; Mayur Lodha; William Mee; Kenneth A. Ross (SIGMOD Conference, 2011)

AnnotCompute: annotation-based exploration and meta-analysis of genomics experiments. - Jie Zheng 001; Julia Stoyanovich; Elisabetta Manduchi; Junmin Liu; Christian J. Stoeckert Jr. (Database J. Biol. Databases Curation, 2011)

Putting Lipstick on Pig: Enabling Database-style Workflow Provenance. - Yael Amsterdamer; Susan B. Davidson; Daniel Deutch; Tova Milo; Julia Stoyanovich; Val Tannen (Proc. VLDB Endow., 2011)

Viewing the Web as a Distributed Knowledge Base. - Serge Abiteboul; Émilien Antoine; Julia Stoyanovich (ICDE, 2012)

Understanding the Structure of Ranked Data. - Julia Stoyanovich (CIDR, 2013)

Understanding Local Structure in Ranked Datasets. - Julia Stoyanovich; Sihem Amer-Yahia; Susan B. Davidson; Marie Jacob; Tova Milo (CIDR, 2013)

Learning Feature Weights from Positive Cases. - Sidath Gunawardena; Rosina O. Weber; Julia Stoyanovich (ICCBR, 2013)

Rule-based application development using Webdamlog. - Serge Abiteboul; Émilien Antoine; Gerome Miklau; Julia Stoyanovich; Jules Testard (SIGMOD Conference, 2013)

Search and result presentation in scientific workflow repositories. - Susan B. Davidson; Xiaocheng Huang; Julia Stoyanovich; Xiaojie Yuan (SSDBM, 2013)

Learning to explore scientific workflow repositories. - Julia Stoyanovich; Paramveer S. Dhillon; Susan B. Davidson; Brian Lyons (SSDBM, 2013)

Introducing Access Control in Webdamlog. - Serge Abiteboul; Émilien Antoine; Gerome Miklau; Julia Stoyanovich; Vera Zaychik Moffitt (CoRR, 2013)

The Webdamlog System Managing Distributed Knowledge on the Web - Serge Abiteboul; Émilien Antoine; Julia Stoyanovich (CoRR, 2013)

A System for Management and Analysis of Preference Data. - Marie Jacob; Benny Kimelfeld; Julia Stoyanovich (Proc. VLDB Endow., 2014)

Collaborative Access Control in WebdamLog. - Vera Zaychik Moffitt; Julia Stoyanovich; Serge Abiteboul; Gerome Miklau (SIGMOD Conference, 2015)

The elephant in the room: getting value from Big Data. - Serge Abiteboul; Xin Luna Dong; Oren Etzioni; Divesh Srivastava; Gerhard Weikum; Julia Stoyanovich; Fabian M. Suchanek (WebDB, 2015)

Analyzing Crowd Rankings. - Julia Stoyanovich; Marie Jacob; Xuemei Gong (WebDB, 2015)

Data Responsibly: Fairness, Neutrality and Transparency in Data Analysis. - Julia Stoyanovich; Serge Abiteboul; Gerome Miklau (EDBT, 2016)

Workload-driven learning of mallows mixtures with pairwise preference data. - Julia Stoyanovich; Lovro Ilijasic; Haoyue Ping (WebDB, 2016)

Towards a Distributed Infrastructure for Evolving Graph Analytics. - Vera Zaychik Moffitt; Julia Stoyanovich (WWW (Companion Volume), 2016)

Portal: A Query Language for Evolving Graphs. - Vera Zaychik Moffitt; Julia Stoyanovich (CoRR, 2016)

Data, Responsibly (Dagstuhl Seminar 16291). - Serge Abiteboul; Gerome Miklau; Julia Stoyanovich; Gerhard Weikum (Dagstuhl Reports, 2016)

Research Directions for Principles of Data Management (Abridged). - Serge Abiteboul; Marcelo Arenas; Pablo Barceló; Meghyn Bienvenu; Diego Calvanese; Claire David; Richard Hull 001; Eyke Hüllermeier; Benny Kimelfeld; Leonid Libkin; Wim Martens; Tova Milo; et al. (SIGMOD Rec., 2016)

A Database Framework for Probabilistic Preferences. - Batya Kenig; Benny Kimelfeld; Haoyue Ping; Julia Stoyanovich (AMW, 2017)

Temporal graph algebra. - Vera Zaychik Moffitt; Julia Stoyanovich (DBPL, 2017)

Towards sequenced semantics for evolving graphs. - Vera Zaychik Moffitt; Julia Stoyanovich (EDBT, 2017)

Querying Probabilistic Preferences in Databases. - Batya Kenig; Benny Kimelfeld; Haoyue Ping; Julia Stoyanovich (PODS, 2017)

DataSynthesizer: Privacy-Preserving Synthetic Datasets. - Haoyue Ping; Julia Stoyanovich; Bill Howe (SSDBM, 2017)

Fides: Towards a Platform for Responsible Data Science. - Julia Stoyanovich; Bill Howe; Serge Abiteboul; Gerome Miklau; Arnaud Sahuguet; Gerhard Weikum (SSDBM, 2017)

Measuring Fairness in Ranked Outputs. - Ke Yang 003; Julia Stoyanovich (SSDBM, 2017)

Diversity in Big Data: A Review. - Marina Drosou; H. V. Jagadish; Evaggelia Pitoura; Julia Stoyanovich (Big Data, 2017)

Synthetic Data for Social Good. - Bill Howe; Julia Stoyanovich; Haoyue Ping; Bernease Herman; Matt Gee (CoRR, 2017)

Probabilistic Inference Over Repeated Insertion Models. - Batya Kenig; Lovro Ilijasic; Haoyue Ping; Benny Kimelfeld; Julia Stoyanovich (AAAI, 2018)

Online Set Selection with Fairness and Diversity Constraints. - Julia Stoyanovich; Ke Yang 003; H. V. Jagadish (EDBT, 2018)

Computational Social Choice Meets Databases. - Benny Kimelfeld; Phokion G. Kolaitis; Julia Stoyanovich (IJCAI, 2018)

Generating Evolving Property Graphs with Attribute-Aware Preferential Attachment. - Amir Aghasadeghi; Julia Stoyanovich (DBTest@SIGMOD, 2018)

A Query Engine for Probabilistic Preferences. - Uzi Cohen; Batya Kenig; Haoyue Ping; Benny Kimelfeld; Julia Stoyanovich (SIGMOD Conference, 2018)

Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management. - Julia Stoyanovich; Bill Howe; H. V. Jagadish (SIGMOD Conference, 2018)

A Nutritional Label for Rankings. - Ke Yang 003; Julia Stoyanovich; Abolfazl Asudeh; Bill Howe; H. V. Jagadish; Gerome Miklau (SIGMOD Conference, 2018)

MobilityMirror: Bias-Adjusted Transportation Datasets. - Luke Rodriguez; Babak Salimi; Haoyue Ping; Julia Stoyanovich; Bill Howe (BiDU@VLDB, 2018)

Zooming in on NYC Taxi Data with Portal. - Julia Stoyanovich; Matthew Gilbride; Vera Zaychik Moffitt (BiDu-Posters@VLDB, 2018)

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 001; Eyke Hüllermeier; Benny Kimelfeld; Leonid Libkin; Wim Martens; Tova Milo; et al. (Dagstuhl Manifestos, 2018)

On Obtaining Stable Rankings. - Abolfazl Asudeh; H. V. Jagadish; Gerome Miklau; Julia Stoyanovich (Proc. VLDB Endow., 2018)

Panel: A Debate on Data and Algorithmic Ethics. - Julia Stoyanovich; Bill Howe; H. V. Jagadish; Gerome Miklau (Proc. VLDB Endow., 2018)

TransFAT: Translating Fairness, Accountably and Transparency into Data Science Practice. - Julia Stoyanovich (PIE@CAiSE, 2019)

MithraLabel: Flexible Dataset Nutritional Labels for Responsible Data Science. - Chenkai Sun; Abolfazl Asudeh; H. V. Jagadish; Bill Howe; Julia Stoyanovich (CIKM, 2019)

Balanced Ranking with Diversity Constraints. - Ke Yang 003; Vasilis Gkatzelis; Julia Stoyanovich (IJCAI, 2019)

Designing Fair Ranking Schemes. - Abolfazl Asudeh; H. V. Jagadish; Julia Stoyanovich; Gautam Das 001 (SIGMOD Conference, 2019)

MithraRanking: A System for Responsible Ranking Design. - Yifan Guan; Abolfazl Asudeh; Pranav Mayuram; H. V. Jagadish; Julia Stoyanovich; Gerome Miklau; Gautam Das 001 (SIGMOD Conference, 2019)

The Responsibility Challenge for Data. - H. V. Jagadish; Francesco Bonchi; Tina Eliassi-Rad; Lise Getoor; Krishna P. Gummadi; Julia Stoyanovich (SIGMOD Conference, 2019)

Towards Responsible Data-driven Decision Making in Score-Based Systems. - Abolfazl Asudeh; H. V. Jagadish; Julia Stoyanovich (IEEE Data Eng. Bull., 2019)

Nutritional Labels for Data and Models. - Julia Stoyanovich; Bill Howe (IEEE Data Eng. Bull., 2019)

Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation. - Serge Abiteboul; Julia Stoyanovich (ACM J. Data Inf. Qual., 2019)

Zooming Out on an Evolving Graph. - Amir Aghasadeghi; Vera Zaychik Moffitt; Sebastian Schelter; Julia Stoyanovich (EDBT, 2020)

FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions. - Sebastian Schelter; Yuxuan He; Jatin Khilnani; Julia Stoyanovich (EDBT, 2020)

Causal intersectionality for fair ranking. - Ke Yang 003; Joshua R. Loftus; Julia Stoyanovich (CoRR, 2020)

Taming Technical Bias in Machine Learning Pipelines. - Sebastian Schelter; Julia Stoyanovich (IEEE Data Eng. Bull., 2020)

The imperative of interpretable machines. - Julia Stoyanovich; Jay J. Van Bavel; Tessa V. West (Nat. Mach. Intell., 2020)

Responsible Data Management. - Julia Stoyanovich; Bill Howe; H. V. Jagadish (Proc. VLDB Endow., 2020)

Supporting Hard Queries over Probabilistic Preferences. - Haoyue Ping; Julia Stoyanovich; Benny Kimelfeld (Proc. VLDB Endow., 2020)

Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines. - Stefan Grafberger; Julia Stoyanovich; Sebastian Schelter (CIDR, 2021)

Disaggregated Interventions to Reduce Inequality. - Lucius Bynum; Joshua R. Loftus; Julia Stoyanovich (EAAMO, 2021)

Causal Intersectionality and Fair Ranking. - Ke Yang 003; Joshua R. Loftus; Julia Stoyanovich (FORC, 2021)

Comparing Apples and Oranges: Fairness and Diversity in Ranking (Invited Talk). - Julia Stoyanovich (ICDT, 2021)

MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines. - Stefan Grafberger; Shubha Guha; Julia Stoyanovich; Sebastian Schelter (SIGMOD Conference, 2021)

Fairness in Ranking: A Survey. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (CoRR, 2021)

Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy. - Falaah Arif Khan; Eleni Manis; Julia Stoyanovich (CoRR, 2021)

Impact Remediation: Optimal Interventions to Reduce Inequality. - Lucius E. J. Bynum; Joshua R. Loftus; Julia Stoyanovich (CoRR, 2021)

Temporal Regular Path Queries: Syntax, Semantics, and Complexity. - Marcelo Arenas; Pedro Bahamondes; Julia Stoyanovich (CoRR, 2021)

COVID-19 Brings Data Equity Challenges to the Fore. - H. V. Jagadish; Julia Stoyanovich; Bill Howe (Digit. Gov. Res. Pract., 2021)

AI reflections in 2020. - Anna Jobin; Kingson Man; Antonio Damasio; Georgios Kaissis; Rickmer Braren; Julia Stoyanovich; Jay J. Van Bavel; Tessa V. West; Brent D. Mittelstadt 002; Jason Eshraghian; Marta R. Costa-jussà; Asaf Tzachor; et al. (Nat. Mach. Intell., 2021)

Algorithmic Techniques for Necessary and Possible Winners. - Vishal Chakraborty; Theo Delemazure; Benny Kimelfeld; Phokion G. Kolaitis; Kunal Relia; Julia Stoyanovich (Trans. Data Sci., 2021)

Resume Format, LinkedIn URLs 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; Julia Stoyanovich (AIES, 2022)

Teaching Responsible Data Science. - Julia Stoyanovich (DataEd@SIGMOD, 2022)

Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines. - Falaah Arif Khan; Eleni Manis; Julia Stoyanovich (EAAMO, 2022)

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; Julia Stoyanovich (FAccT, 2022)

Temporal Regular Path Queries. - Marcelo Arenas; Pedro Bahamondes; Amir Aghasadeghi; Julia Stoyanovich (ICDE, 2022)

Teaching Responsible Data Science: Charting New Pedagogical Territory. - Armanda Lewis; Julia Stoyanovich (Int. J. Artif. Intell. Educ., 2022)

Responsible data management. - Julia Stoyanovich; Serge Abiteboul; Bill Howe; H. V. Jagadish; Sebastian Schelter (Commun. ACM, 2022)

External Stability Auditing to Test the Validity of Personality Prediction in AI Hiring. - Alene K. Rhea; Kelsey Markey; Lauren D'Arinzo; Hilke Schellmann; Mona Sloane; Paul Squires; Julia Stoyanovich (CoRR, 2022)

Spending Privacy Budget Fairly and Wisely. - Lucas Rosenblatt; Joshua Allen; Julia Stoyanovich (CoRR, 2022)

Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance. - Andrew Bell; Oded Nov; Julia Stoyanovich (CoRR, 2022)

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. - Lucas Rosenblatt; Anastasia Holovenko; Taras Rumezhak; Andrii Stadnik; Bernease Herman; Julia Stoyanovich; Bill Howe (CoRR, 2022)

Rankers, Rankees, & Rankings: Peeking into the Pandora's Box from a Socio-Technical Perspective. - Jun Yuan; Julia Stoyanovich; Aritra Dasgupta 001 (CoRR, 2022)

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; Julia Stoyanovich (Data Min. Knowl. Discov., 2022)

The Many Facets of Data Equity. - H. V. Jagadish; Julia Stoyanovich; Bill Howe (ACM J. Data Inf. Qual., 2022)

Data distribution debugging in machine learning pipelines. - Stefan Grafberger; Paul Groth; Julia Stoyanovich; Sebastian Schelter (VLDB J., 2022)

Developing data capability with non-profit organisations using participatory methods. - Anthony McCosker; Xiaofang Yao; Kath Albury; Alexia Maddox; Jane Farmer; Julia Stoyanovich (Big Data Soc., 2022)

Counterfactuals for the Future. - Lucius E. J. Bynum; Joshua R. Loftus; Julia Stoyanovich (AAAI, 2023)

The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization's Algorithms. - Andrew Bell; Oded Nov; Julia Stoyanovich (CHI Extended Abstracts, 2023)

Setting the Right Expectations: Algorithmic Recourse Over Time. - João Fonseca; Andrew Bell; Carlo Abrate; Francesco Bonchi; Julia Stoyanovich (EAAMO, 2023)

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. - Andrew Bell; Lucius Bynum; Nazarii Drushchak; Tetiana Zakharchenko; Lucas Rosenblatt; Julia Stoyanovich (FAccT, 2023)

Subset Modelling: A Domain Partitioning Strategy for Data-efficient Machine-Learning. - Vítor Ribeiro; Eduardo H. M. Pena; Raphael de Freitas Saldanha; Reza Akbarinia; Patrick Valduriez; Falaah Arif Khan; Julia Stoyanovich; Fábio Porto 001 (SBBD, 2023)

Responsible Data Management. - Julia Stoyanovich (SEBD, 2023)

Personal Data for Personal Use: Vision or Reality? - Xin Luna Dong; Bo Li 026; Julia Stoyanovich; Anthony Kum Hoe Tung; Gerhard Weikum; Alon Y. Halevy; Wang-Chiew Tan (SIGMOD Conference Companion, 2023)

Fairness in Ranking: From Values to Technical Choices and Back. - Julia Stoyanovich; Meike Zehlike; Ke Yang 003 (SIGMOD Conference Companion, 2023)

Tutorials at The Web Conference 2023. - Valeria Fionda; Olaf Hartig; Reyhaneh Abdolazimi; Sihem Amer-Yahia; Hongzhi Chen; Xiao Chen 016; Peng Cui 001; Jeffrey Dalton 001; Xin Luna Dong; Lisette Espín-Noboa; Wenqi Fan; Manuela Fritz; et al. (WWW (Companion Volume), 2023)

On Fairness and Stability: Is Estimator Variance a Friend or a Foe? - Falaah Arif Khan; Denys Herasymuk; Julia Stoyanovich (CoRR, 2023)

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. - Andrew Bell; Lucius Bynum; Nazarii Drushchak; Tetiana Herasymova; Lucas Rosenblatt; Julia Stoyanovich (CoRR, 2023)

The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction. - Falaah Arif Khan; Julia Stoyanovich (CoRR, 2023)

Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (ACM Comput. Surv., 2023)

Fairness in Ranking, Part I: Score-Based Ranking. - Meike Zehlike; Ke Yang 003; Julia Stoyanovich (ACM Comput. Surv., 2023)

Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences. - Haoyue Ping; Julia Stoyanovich (Proc. ACM Manag. Data, 2023)

Query Refinement for Diversity Constraint Satisfaction. - Jinyang Li 008; Yuval Moskovitch; Julia Stoyanovich; H. V. Jagadish (Proc. VLDB Endow., 2023)

ERICA: Query Refinement for Diversity Constraint Satisfaction. - Jinyang Li 008; Alon Silberstein; Yuval Moskovitch; Julia Stoyanovich; H. V. Jagadish (Proc. VLDB Endow., 2023)

Responsible AI literacy: A stakeholder-first approach. - Daniel Dominguez Figaredo; Julia Stoyanovich (Big Data Soc., 2023)

Introducing contextual transparency for automated decision systems. - Mona Sloane; Ian Solano-Kamaiko; Jun Yuan; Aritra Dasgupta 001; Julia Stoyanovich (Nat. Mac. Intell., 2023)

A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. - Lucas Rosenblatt; Julia Stoyanovich; Christopher Musco (AAAI, 2024)

Making Transparency Influencers: A Case Study of an Educational Approach to Improve Responsible AI Practices in News and Media. - Andrew Bell; Julia Stoyanovich (CHI Extended Abstracts, 2024)

A New Paradigm for Counterfactual Reasoning in Fairness and Recourse. - Lucius E. J. Bynum; Joshua R. Loftus; Julia Stoyanovich (IJCAI, 2024)

The Game Of Recourse: Simulating Algorithmic Recourse over Time to Improve Its Reliability and Fairness. - Andrew Bell; João Fonseca; Julia Stoyanovich (SIGMOD Conference Companion, 2024)

Responsible Model Selection with Virny and VirnyView. - Denys Herasymuk; Falaah Arif Khan; Julia Stoyanovich (SIGMOD Conference Companion, 2024)

Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity. - Andrew Bell; João Fonseca; Carlo Abrate; Francesco Bonchi; Julia Stoyanovich (CoRR, 2024)

ShaRP: Explaining Rankings with Shapley Values. - Venetia Pliatsika; João Fonseca; Tilun Wang; Julia Stoyanovich (CoRR, 2024)

Still More Shades of Null: A Benchmark for Responsible Missing Value Imputation. - Falaah Arif Khan; Denys Herasymuk; Nazar Protsiv; Julia Stoyanovich (CoRR, 2024)

Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives. - Lucas Rosenblatt; Bill Howe; Julia Stoyanovich (CoRR, 2024)

Query Refinement for Diverse Top-k Selection. - Felix S. Campbell; Alon Silberstein; Julia Stoyanovich; Yuval Moskovitch (Proc. ACM Manag. Data, 2024)

Temporal graph patterns by timed automata. - Amir Aghasadeghi; Jan Van den Bussche; Julia Stoyanovich (VLDB J., 2024)

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; Julia Stoyanovich (SIGMOD Rec., 2024)

Rodeo: Making Refinements for Diverse Top-k Queries. - Felix S. Campbell; Julia Stoyanovich; Yuval Moskovitch (Proc. VLDB Endow., 2024)

Automated Data Cleaning can Hurt Fairness in Machine Learning-Based Decision Making. - Shubha Guha; Falaah Arif Khan; Julia Stoyanovich; Sebastian Schelter (IEEE Trans. Knowl. Data Eng., 2024)

Making Transparency Advocates: An Educational Approach Towards Better Algorithmic Transparency in Practice. - Andrew Bell; Julia Stoyanovich (AAAI, 2025)

We Are AI: Taking Control of Technology. - Julia Stoyanovich; Armanda Lewis; Eric Corbett; Lucius E. J. Bynum; Lucas Rosenblatt; Falaah Arif Khan (AAAI, 2025)

Using Case Studies to Teach Responsible AI to Industry Practitioners. - Julia Stoyanovich; Rodrigo Kreis de Paula; Armanda Lewis; Chloe Zheng (AAAI, 2025)

SHAP-based Explanations are Sensitive to Feature Representation. - Hyunseung Hwang; Andrew Bell; João Fonseca; Venetia Pliatsika; Julia Stoyanovich; Steven Euijong Whang (FAccT, 2025)

CREDAL: Close Reading of Data Models. - George Fletcher 001; Olha Nahurna; Matvii Prytula; Julia Stoyanovich (HILDA@SIGMOD, 2025)

ONION: A Multi-Layered Framework for Participatory ER Design. - Viktoriia Makovska; George Fletcher 001; Julia Stoyanovich (HILDA@SIGMOD, 2025)

Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs. - João Fonseca; Andrew Bell; Julia Stoyanovich (CoRR, 2025)

"Would You Want an AI Tutor?" Understanding Stakeholder Perceptions of LLM-based Chatbots in the Classroom. - Caterina Fuligni; Daniel Dominguez Figaredo; Julia Stoyanovich (CoRR, 2025)

The Cambridge Report on Database Research. - Anastasia Ailamaki; Samuel Madden 001; Daniel Abadi; Gustavo Alonso; Sihem Amer-Yahia; Magdalena Balazinska; Philip A. Bernstein; Peter A. Boncz; Michael J. Cafarella; Surajit Chaudhuri; Susan B. Davidson; David J. DeWitt; et al. (CoRR, 2025)

Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data. - Shlomi Hod; Lucas Rosenblatt; Julia Stoyanovich (CoRR, 2025)

VirnyFlow: A Design Space for Responsible Model Development. - Denys Herasymuk; Nazar Protsiv; Julia Stoyanovich (CoRR, 2025)