Mateo Espinosa Zarlenga

Mateo Espinosa Zarlenga

JRF @ Oxford | PhD @ Cambridge

Welcome to my site! I am Junior Research Fellow (JRF) in Computer Science at the University of Oxford (Trinity College). Prior to this position, I was a PhD candidate in Computer Science at the University of Cambridge, where I had the extreme luck to be supervised by Mateja Jamnik and to be supported by a Gates Cambridge scholarship (still waiting for my viva voce). As part of my research, I am interested in broadening the applications of artificial intelligence in critical tasks where understanding how these models make predictions, and not just what their predictions are, is crucial. Specifically, I am interested in so-called concept-based interpretability and its wider applications to human-in-the-loop systems (particularly on how concepts can be used to provide human-like feedback during deployment). If you would like to read more about this, please take a look at my research page.

In this site I'll be collecting my personal thoughts on what I am sure will be a seemingly random selection of topics. If you want to know more about my research or myself, feel free to shoot me an email with any questions and/or good jokes you may have. In the meantime, I hope you find some of the posts in this site both slightly entertaining and interesting for you!

Recent News

[November 2025] I started a Junior Research Fellowship (JRF) in Computer Science at Trinity College, Oxford.
[August 2025] Pietro Barbiero and I will be giving a talk on "Foundations of Interpretable Models" at the Neuro-Symbolic AI Summer School. This talk will be based on this paper!
[July 2025] I will be in Vancouver for ICML 2025 presenting two papers [1, 2]!
[Feburary 2025] I will be co-presenting a tutorial on Concept-based Interpretable Deep Learning at AAAI 2025. Come by if you are around!
[January 2025] We started a new online blog series and library (PyC) on Concept Learning. Check it out here!
[January 2025] Our work on Causal Concept Graph Models, lead by my amazing collaborators Gabriele Dominici and Pietro Barbiero, was accepted at ICLR 2025!
[October 2024] Our work on unsupervised bias mitigation was accepted at ECCV 2024 as an oral and nominated as Best Paper (within the top 15 papers)!
[August 2024] Our workshop on Human-Interpretable AI was accepted at KDD 2024.
[July 2024] One paper accepted at ICML 2024 where I will also be a co-organizer of the LatinX in AI (LXAI) Affinity Workshop.
[January 2024] Joined The Alan Turing Institute as a PhD enrichment student.
[October 2023] Joined Sony AI's AI Ethics team as a research intern.
[September 2023] Our Intervention-aware Concept Embedding Model (IntCEM) paper was accepted at NeurIPS 2023 as a spotlight (top ~3.06% of papers)!
[July 2023] Our Tabular Concept Bottleneck Model (TabCBM) paper was accepted at Transactions of Machine Learning Research (TMLR) and at ICML's 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH)
[April 2023] Our Deep Concept Reasoner (DCR) paper was accepted at ICML 2023 and at ICML's Differentiable Almost Everything Workshop!
[March 2023] Our paper on the effect of uncertainty for concept interventions was accepted at the AAAI/ACM Conference on AI, Ethics, and Society (AIES) 2023!
[November 2022] Our paper on metrics for measuring concept quality and leakage was accepted at AAAI 2023 as a spotlight presentation!
[September 2022] Our Concept Embedding Model (CEM) paper was accepted at NeurIPS 2022!
[December 2021] My MPhil thesis work was accepted at NeurIPS's Workshop on eXplainable AI approaches for debugging and diagnosis (XAI4Debugging@NeurIPS) as a spotlight presentation!
[June 2021] Awarded Gates Cambridge scholarship to study for a Computer Science PhD under the supervision of Professor Mateja Jamnik.
[June 2021] Graduated from my MPhil in Advanced Computer Science with distinction.
[October 2020] Amid the COVID-19 pandemic, I moved to Cambridge, UK for an MPhil in Advanced Computer Science at Cambridge's Computer Laboratory.
[July 2017] Joined Cerebras Systems as an early Machine Learning Engineer.
[June 2017] Completed my MEng in Computer Science from Cornell University graduating with the highest GPA of the cohort.
[December 2016] Completed my BA in Computer Science from Cornell University.

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