Asia J. Biega is a tenure-track faculty member (W2) at the Max Planck Institute for Security and Privacy (MPI-SP) leading the Responsible Computing group. Through interdisciplinary collaborations, she designs legally, ethically, and socially responsible information and social computing systems and studies how they interact with and influence their users.
Before joining MPI-SP, Asia worked at Microsoft Research Montréal in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) Group. She completed her PhD at the Max Planck Institute for Informatics and the Max Planck Institute for Software Systems. She has published her work in leading information retrieval, Web, and data mining venues, and has been serving on the program committees of conferences such as SIGIR, WSDM, KDD, AAAI, and FAT*/FAccT. She has co-organized the NIST TREC Fair Ranking track, and a FAT* panel on technology refusal. Beyond academia, her perspectives and methodological approaches are informed by an industrial experience, including work on privacy infrastructure at Google and consulting for Microsoft product teams on issues related to FATE and privacy.
OPENINGS IN THE RESPONSIBLE COMPUTING GROUP
I am hiring for my group at MPI-SP:
Responsible Computing Group at MPI-SP
I lead the Responsible Computing group at the Max Planck Institute for Security and Privacy (MPI-SP). We study online socio-technical systems—the algorithms, the people, the legal regulations, the interfaces and the data. We seek to understand both the influence online systems have on user behavior, cognition, and well-being, as well as the impacts of user biases and preferences on the functioning of those systems. We explore computational interpretations of legal requirements as well as concepts from social sciences and humanities to enhance our understanding of the interplay between people and online systems and develop novel technical solutions mitigating systemic and individual harms. Our work is often grounded in interdisciplinary collaborations, allowing us not only to make technical contributions in Computer Science, but also lend our computing expertise to inform research in other fields.
Our current focus is on responsible computing principles for information access and social computing systems (including search, recommendation, assistive typing, sharing economy, crowdsourcing or social media systems). We publish our work at top-tier conferences in the areas of Web & Information Retrieval, Social Computing, and Computing & Society.
Topics we’re currently working on:
- Operationalizing concepts from data protection laws such as GDPR (data minimization, fairness, privacy, accountability, transparency).
- Modeling of human biases in the context information access and social computing systems.
- Measurement methodologies to quantify the harms and the impacts of information access and social computing systems on user behavior, beliefs, cognition, and well-being.
MPI-SP is the newest institute within the broader landscape of Computer Science research at the Max Planck Society. The institute’s mission is to study and develop the technical foundations and interdisciplinary aspects of security, privacy, and responsible computing. We conduct cutting-edge basic research and train the next generation of scientific and industrial leaders in an environment that encourages collaboration and thinking outside the box.
- Reviving Purpose Limitation and Data Minimisation in Personalisation, Profiling and Decision-Making Systems
Michèle Finck, Asia J. Biega
- Estimation of Fair Ranking Metrics with Incomplete Judgments
Omer Kirnap, Fernando Diaz, Asia J. Biega, Michael D. Ekstrand, Ben Carterette, Emine Yilmaz
(WWW 2021) The Web Conference 2021
- Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz and Michèle Finck
(SIGIR 2020) The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
- On the Desiderata for Online Altruism: Nudging for Equitable Donations
Nuno Mota, Abhijnan Chakraborty, Asia J. Biega, Krishna P. Gummadi, Hoda Heidari
(CSCW 2020) The 23rd ACM Conference on Computer-Supported Cooperative Work and Social Computing
- Evaluating Stochastic Rankings with Expected Exposure
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, Ben Carterette
(CIKM 2020) The 29th ACM International Conference on Information and Knowledge Management
Best Paper Award Nominee
- Towards Query Logs for Privacy Studies: On Deriving Search Queries from Questions
Asia J. Biega, Jana Schmidt, Rishiraj Saha Roy
(ECIR 2020) The 42nd European Conference on Information Retrieval, short paper
[PDF] [Extended version]
- Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform
Tom Sühr, Asia J. Biega, Meike Zehlike, Krishna P. Gummadi, Abhijnan Chakraborty
(KDD 2019) The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
- On the Impact of Choice Architectures on Inequality in Online Donation Platforms
Abhijnan Chakraborty, Nuno Mota, Asia J. Biega, Krishna P. Gummadi and Hoda Heidari
(WWW 2019) The Web Conference 2019, short paper
- Enhancing Privacy and Fairness in Search Systems
(PhD Thesis) Saarland University
- Equity of Attention: Amortizing Individual Fairness in Rankings
Asia J. Biega, Krishna P. Gummadi, Gerhard Weikum
(SIGIR 2018) The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval
- Learning to Un-Rank: Quantifying Search Exposure for Users in Online Communities
Asia J. Biega, Azin Ghazimatin, Hakan Ferhatosmanoglu, Krishna P. Gummadi, Gerhard Weikum
(CIKM 2017) The 26th ACM International Conference on Information and Knowledge Management
- Privacy of Hidden Profiles: Utility-Preserving Profile Removal in Online Forums
Sedigheh Eslami, Asia J. Biega, Rishiraj Saha Roy, Gerhard Weikum
(CIKM 2017) The 26th ACM International Conference on Information and Knowledge Management, short paper
- Fair Sharing for Sharing Economy Platforms
Abhijnan Chakraborty, Asia J. Biega, Aniko Hannak, Krishna P. Gummadi
(FATREC@RECSYS 2017) The FATREC Workshop on Responsible Recommendation
- Privacy through Solidarity: A User-Utility-Preserving Framework to Counter Profiling
Asia J. Biega, Rishiraj Saha Roy, Gerhard Weikum
(SIGIR 2017) The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
- R-Susceptibility: An IR-Centric Approach to Assessing Privacy Risks for Users in Online Communities
Joanna Asia Biega, Krishna P. Gummadi, Ida Mele, Dragan Milchevski, Christos Tryfonopoulos, Gerhard Weikum
(SIGIR 2016) The 39th International ACM SIGIR Conference on Research and Development in Information Retrieval
- YAGO: A Multilingual Knowledge Base from Wikipedia, Wordnet, and Geonames
Thomas Rebele, Fabian M. Suchanek, Johannes Hoffart, Joanna Asia Biega, Erdal Kuzey, Gerhard Weikum
(ISWC 2016) The 15th International Semantic Web Conference, short paper
- IBEX: Harvesting Entities from the Web Using Unique Identifiers
Aliaksandr Tailaika, Joanna Biega, Antoine Amarilli, Fabian M. Suchanek
(WebDB@SIGMOD 2015) The 18th International Workshop on the Web and Databases
[PDF] [Technical report]
- YAGO3: A Knowledge Base from Multilingual Wikipedias
Farzaneh Mahdisoltani, Joanna Biega, Fabian M. Suchanek
(CIDR 2015) The 7th Biennial Conference on Innovative Data Systems Research
- Probabilistic Prediction of Privacy Risks in User Search Histories
Joanna Biega, Ida Mele, Gerhard Weikum
(PSBD@CIKM 2014) The 1st International Workshop on Privacy and Security of Big Data
- Mining History with Le Monde
Thomas Huet, Joanna Biega, Fabian M. Suchanek
(AKBC@CIKM 2013) The 3rd Workshop on Automated Knowledge Base Construction
- Inside YAGO2s: A Transparent Information Extraction Architecture
Joanna Biega, Erdal Kuzey, Fabian M. Suchanek
(WWW 2013 - demo) The 22nd International World Wide Web Conference
- Overview of the TREC 2019 Fair Ranking Track
Asia J. Biega, Fernando Diaz, Michael D. Ekstrand, Sebastian Kohlmeier
(TREC 2019) The 28th Text REtrieval Conference Proceedings
- FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval
Olteanu et al.
(SIGIR Forum) December 2019, Volume 53 Number 2, pp 20–43
- Report on the First HIPstIR Workshop on the Future of Information Retrieval
Dietz et al.
(SIGIR Forum) December 2019, Volume 53 Number 2, pp 62–75
Mentoring and Advising
- Divya Shanmugam (MIT), research internship, 2020.
- Maria Antoniak (Cornell), research internship, 2020.
- Ruohan Li (CMU), remote research project, 2020.
- Jianxiang Li (CMU), remote research project, 2020.
- Tom Sühr (TU Berlin), research internship, 2018-2019.
- Jana Schmidt (Saarland University), BSc thesis, 2018.
- Sedigheh Eslami (Saarland University) MSc thesis, 2016-2017.
Invited talks and panels
- [upcoming] UMass Amherst, CIIR Talk Series, remote, April 2021
- [upcoming] ELLIS Workshop on the Foundations of Algorithmic Fairness, remote, March 2021
- Max Planck Intersectional Symposium on Computing and Society, remote, January 2021
- University of Colorado Boulder, INFO Seminar Series, remote, October 2020
- Georgetown University, CS Colloquium, remote, October 2020
- Panel: Career paths in industry, Mila -- Quebec AI Institute, Canada, remote, October 2020
- ECCV Workshop: The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security, remote, August 2020
- Panel: Women in IR, SIGIR 2020, remote, July 2020
- TU Munich, Germany, February 2020
- Fairness, Accountability, and Transparency Seminars and Hackfest, UPF Barcelona, Spain, January 2020
- University of Amsterdam, The Netherlands, December 2019
- Microsoft Munich, Germany, July 2019
- LMU Munich, Germany, March 2019
- L3S Research Center, Hannover, Germany, January 2019
- Microsoft Research AI Breakthroughs, Redmond, USA, September 2018
- Microsoft Research Montreal, Canada, August 2018
- Wikimedia Foundation, remote, August 2018
- Panel: How to mentor women in IR? What works, what doesn't, and why?
Women in IR @ SIGIR 2018, Ann Arbor, Michigan, USA, July, 2018
- Microsoft Research Cambridge, UK, February 2018
- Google Zurich, Switzerland, September 2017
- UMass Amherst, Massachusetts, USA, November 2015
- Plenary discussion at FAT* 2020 on When Not to Design, Build, or Deploy
- Fair Ranking track at TREC: 2019, 2020
- SIGIR 2020-2021: ACM SIGIR Conference on Research and Development in Information Retrieval
- AAAI 2021: AAAI Conference on Artifical Intelligence
- WSDM 2021: ACM WSDM Conference on Web Search and Data Mining
- KDD 2020 (research track): ACM SIGKDD Conference on Knowledge Discovery and Data Mining
- SIGIR 2019: ACM SIGIR Conference on Research and Development in Information Retrieval
- FAT*/FAccT 2019, 2021: ACM Conference on Fairness, Accountability, and Transparency
- SDM 2019-2020: SIAM International Conference on Data Mining
- CIKM 2019 (long+short papers): ACM International Conference on Information and Knowledge Management
- ECIR 2020 Best Paper Awards Committee (Industry Impact Award)
- NeurIPS 2020 Navigating the Broader Impacts of AI Research
- RecSys 2020 The 3rd FAccTRec Workshop on Responsible Recommendation
- ECIR 2020 International Workshop on Algorithmic Bias in Search and Recommendation
- ICLR 2020 Towards Trustworthy ML: Rethinking Security and Privacy for ML
- SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in IR
- KDD 2019 Workshop on Learning and Mining for Cybersecurity
- Information Systems, 2017
- ACM Transactions on the Web (TWEB), 2016
- [upcoming] Lecturer at CMMRS 2021: The Cornell, Maryland, and Max Planck Pre-Doctoral Research School on Emerging Research Trends in Computer Science, August 2021
- Coordinator for Information Retrieval and Data Mining , WS 2017/18.
- Teaching Assistant for Information Retrieval and Data Mining, WS 2015/16.
- Teaching Assistant for the Data Mining with R workshop for high school students, Saarland University, Forschungstage Informatik 2016.
- Guest speaker on the Consequential podcast: S3E9 - Is information democratized?
- Expert roundtable on the governance of facial recognition technology in Canada: report
- NIST press release about the TREC Fair Ranking track: To Measure Bias in Data, NIST Initiates ‘Fair Ranking’ Research Effort