Miri Zilka (original) (raw)

I am recruiting 1-2 PhD students this cycle. Please see information for prospective students.

I am an Assistant Professor in Responsible Machine Learning at the University of Cambridge. I specialised in ethical, human-centric, and trustworthy AI for high-stakes domains, such as criminal justice and social care, where algorithmic predictions have life-changing consequences, individuals cannot opt out, and protective legislation (e.g., GDPR) does not apply.

Previously, I was a Leverhulme Research Fellow in the Machine Learning Group at the University of Cambridge, a College Research Associate at King’s College, Cambridge, and an Associate Fellow at the Leverhulme Centre for the Future of Intelligence.

Before Cambridge, I was a Research Fellow in Machine Learning at the University of Sussex, focusing on fairness, equality, and access. I obtained a PhD in Analytical Science (Physics) from the University of Warwick, hold an M.Sc. in Physics, and a dual B.Sc. in Physics and Biology from Tel Aviv University.

  1. Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement
    • C. Kearney, J. Hron, H. Kosc, and M. Zilka. FAccT, 2024.
  2. Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
    • B. Butcher*, M. Zilka* , J. Hron, D. Cook, and A. Weller. ACM Journal on Responsible Computing, 2024.
  3. Evaluating Language Models for Mathematics through Interactions
    • K. M. Collins, A. Q Jiang, S. Frieder, L. Wong, M. Zilka, U. Bhatt, T. Lukasiewicz, Y. Wu, J. B. Tenenbaum,W. Hart, T. Gowers, W. Li, A. Weller, and M. Jamnik. PNAS, 2024.
  4. Media Coverage of Predictive Policing: Bias, Police Engagement, and the Future of Transparency
    • H. Camilleri, C. Ashurst, N. Jaisankar, A. Weller, and M. Zilka. EAAMO, 2023.
  5. Exploring Police Perspectives on Algorithmic Transparency: A Qualitative Analysis of Police Interviews in the UK
    • M. Zilka., C. Ashurst, L. Chambers, E. P. Goodman, P. Ugwudike, and M. Oswald. EAAMO, 2023.
  6. AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI
    • A. G. Yasar, A. Chong, E. Dong, T. K. Gilbert, S. Hladikova, R. Maio, C. Mougan, X. Shen, S. Singh, A. Stoica, S. Thais, and M. Zilka.

Generative AI + Law (GenLaw), hosted at ICML, 2023.

  1. Protecting Children from Online Exploitation: Can a trained model detect harmful communication strategies?
    • D. Cook*, M. Zilka*, H. DeSandre, S. Giles, and S. Maskell. AIES, 2023.
  2. The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments
    • M. Zilka, R. Fogliato, J. Hron, B. Butcher, C. Ashurst and A. Weller. FAccT, 2023.
  3. Conformal Prediction for Resource Prioritisation in Predicting Rare and Dangerous Outcomes
    • V. Babbar, U. Bhatt, M. Zilka, and A. Weller. NeurIPS 2022 Workshop on Human in the Loop Learning, 2022.
  4. A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets
    • M. Zilka*, B. Butcher*, and A. Weller. NeurIPS, Datasets and Benchmarks track, 2022.
  5. The UK Algorithmic Transparency Standard: A Qualitative Analysis of Police Perspectives
    • M. Oswald, L. Chambers, E. P. Goodman, P. Ugwudike, and M. Zilka. SSRN, 2022.
  6. Can We Automate the Analysis of Online Child Sexual Exploitation Discourse?
    • D. Cook, M. Zilka, H. DeSandre, S. Giles, A. Weller, and S. Maskell. arXiv, 2022.
  7. Differential Enforcement and the Progression of Disparities within the Criminal Justice System
    • M. Zilka, C. Ashurst, R. Fogliato, and A. Weller. ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022.
  8. Racial Disparities in Arrests for Drug Violations in the US: What Can We Learn from Publicly Available Data?
    • B. Butcher*, M. Zilka*, and A. Weller. ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022.
  9. A Framework for Human-in-the-Loop High-Precision Information Extraction from Text Documents
    • B. Butcher, M. Zilka, and A. Weller. ICML Workshop on Human-Machine Collaboration and Teaming, 2022.
  10. Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study
  1. Racial Disparities in the Enforcement of Marijuana Violations in the US
  1. An Algorithmic Framework for Positive Action
  1. A Psychology-Driven Computational Analysis of Political Interviews
  1. Weak Intermolecular CH···N Hydrogen Bonding: Determination of 13CH–15N Hydrogen-Bond Mediated J Couplings by Solid-State NMR Spectroscopy and First-Principles Calculations
  1. Reducing the computational cost of NMR crystallography of organic powders at natural isotopic abundance with the help of 13C‐13C dipolar couplings
  1. An NMR Crystallography Investigation of Furosemide
  1. Visualising Packing Interactions in Solid-State NMR: Concepts and Applications
  1. Ab-Initio Random Structure Searching of Organic Molecular Solids: Assessment and Validation Against Experimental Data
  1. Visualization and Processing of Computed Solid-State NMR Parameters: MagresView and MagresPython
  1. Automated Detection of Feeding Strikes by Larval Fish Using Continuous High-Speed Digital Video: a Novel Method to Extract Quantitative Data from Fast, Sparse Kinematic Events
  1. Hydrodynamic Constraints of Suction Feeding in Low Reynolds Numbers, and the Critical Period of Larval Fishes
  1. The Star Formation History of the Milky Way’s Nuclear Star Cluster
  1. An Extremtely Top-Heavy Initial Mass Function in the Galactic Center Stellar Disks