Miri Zilka

I am 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. I work on Trustworthy Machine Learning, with a focus on the deployment of algorithmic tools in criminal justice. As part of my Leverhulme fellowship, I am developing a human-centric framework for evaluating and mitigating risk in causal models.

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.

News

• 08/2023: Two papers accepted @ EAMMO2023

• 05/2023: Paper on detecting harmful communication strategies accepted @ AIES2023

• 04/2023: Paper on the progression of disparities within the criminal justice system accepted @ FAccT2023

• 03 /2023: Chatted on AI: 'Risks to society'  with James Reynolds @ OS on BBC World Service. 

• 12/2022: Delighted to participate in the panel discussion: What’s Not Said in Papers: Advice for a Meaningful Career in Machine Learning at Neurips @ Cambridge

• 11/22:  Excited to speak @ Royal Institute of Philosophy's Public Lecture series on Philosophy of Crime and Policing

• 9/2022: A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets @ NeurIPS2022

Selected publications

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

9. 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.

10. 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.

11. 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.

12. 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.

13. Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study

    • M. Zilka*, H. Sargeant*, and A. Weller. AAAI/ACM Conference on AI, Ethics and Society (AIES), 2022.

14. Racial Disparities in the Enforcement of Marijuana Violations in the US

    • B. Butcher*, C. Robinson*,  M. Zilka*, R. Fogliato, C. Ashurst, and A. Weller. AAAI/ACM Conference on AI, Ethics and Society (AIES), 2022.

15. An Algorithmic Framework for Positive Action

    • O. Thomas, M. Zilka, and A. Weller, N. Quadrianto. ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2021. [selected for oral presentation]

16. A Psychology-Driven Computational Analysis of Political Interviews

    • D. Cook, M. Zilka, S. Maskell, and L. Alison. Interspeech, 2021.

17. Weak Intermolecular CH···N Hydrogen Bonding: Determination of 13CH–15N Hydrogen-Bond Mediated J Couplings by Solid-State NMR Spectroscopy and First-Principles Calculations

    • A.L. Webber, J.R. Yates, M. Zilka, S. Sturnio, L.C. Uldry, E.K. Corlett, C.J. Pickard, M. Pérez-Torralba, M.A. Garcia, D.S. Maria, R.M. Claramunt, and S.P. Brown. The Journal of Physical Chemistry A, 2019.

18. Reducing the computational cost of NMR crystallography of organic powders at natural isotopic abundance with the help of 13C‐13C dipolar couplings

    • P. Thureau, S. Sturniolo, M. Zilka, F. Ziarelli, d. Viel, J.R. Yates, and G. Mollica. Magnetic Resonance in Chemistry, 2019.

19. An NMR Crystallography Investigation of Furosemide

    • M. Zilka, S.P. Brown, and J.R. Yates. Magnetic Resonance in Chemistry, 2019.

20. Visualising Packing Interactions in Solid-State NMR: Concepts and Applications

    • M. Zilka, S. Sturniolo, S.P. Brown, and J.R. Yates.  The Journal of Chemical Physics, 2017.

21. Ab-Initio Random Structure Searching of Organic Molecular Solids: Assessment and Validation Against Experimental Data

    • M. Zilka, D. V. Dudenko, C. E. Hughes, P.A. Williams, S. Sturniolo, T. W. Franks, C. J. Pickard, J.R. Yates, K. D. M. Harris, Kenneth, and S.P. Brown. Physical Chemistry Chemical Physics, 2017.

22. Visualization and Processing of Computed Solid-State NMR Parameters: MagresView and MagresPython

    • S. Sturniolo, T.F. Green, R.M. Hanson, M. Zilka, K.Refson, P. Hodgkinson, S. P. Brown, and J. R. Yates. Solid State Nuclear Magnetic Resonance, 2016.

23. 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

    • R. E. Shamur, M. Zilka, T. Hassner, V. China, A. Liberzon, and R. Holzman. Journal of Experimental Biology, 2016.

24. Hydrodynamic Constraints of Suction Feeding in Low Reynolds Numbers, and the Critical Period of Larval Fishes

    • R. Holzman, V. China, S. Yaniv, and M. Zilka. Integrative and Comparative Biology, 2015.

25. The Star Formation History of the Milky Way’s Nuclear Star Cluster

    • O. Pfuhl, T. K. Fritz, M. Zilka, H. Maness, F. Eisenhauer, R. Genzel, S. Gillessen, T. Ott, K. Dodds-Eden, and A. Sternberg. The Astrophysical Journal, 2011

26. An Extremtely Top-Heavy Initial Mass Function in the Galactic Center Stellar Disks

    • H. Bartko, F. Martins, S. Trippe, T. K. Fritz, R. Genzel, T. Ott, F. Eisenhauer, S. Gillessen, T. Paumard, T. Alexander, K. DoddsEden, O. Gerhard, Y. Levin, L. Mascetti, S. Nayakshin, H. B. Perets, G. Perrin, O. Pfuhl, M. J. Reid, D. Rouan, M. Zilka, and A. Sternberg. The Astrophysical Journal, 2009.