Scholar
Fabio Massimo Zennaro
Google Scholar ID: st6ngd8AAAAJ
University of Bergen
Citations & Impact
Citations
489
H-index
11
i10-index
12
Publications
20
Co-authors
9
list available
Publications
Resume (English only)
Academic Achievements
- - Paper 'Interventionally Consistent Surrogates for Agent-based Simulators' published in NeurIPS 2024
- - Paper 'Causally Abstracted Multi-armed Bandits' published in UAI 2024 and presented orally
- - Paper 'Causal Optimal Transport of Abstractions' published in CLeaR 2024
- - Paper 'Abstraction between Structural Causal Models: A Review of Definitions and Properties' published in UAI 2022 Workshop on Causal Representation Learning and received the best paper award
- - Paper 'Quantifying Consistency and Information Loss for Causal Abstraction Learning' published in IJCAI 2023
- - Paper 'Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions' published in CLeaR 2023 and presented orally (9% acceptance rate)
Research Experience
- - Post-doctoral research associate at the Warwick Machine Learning Group, leading research on machine learning, causality, and abstraction
- - Post-doctoral researcher at the Information and Cyber Security group at the University of Oslo, researching reinforcement learning, computer security, and uncertainty
- - PhD student at the University of Manchester, studying unsupervised learning and information theoretic learning
Education
- - PhD: University of Manchester, supervised by Prof. Ke Chen, focused on unsupervised learning and information theoretic learning
- - First Postdoc: University of Oslo, Information and Cyber Security group, supervised by Prof. Audun Josang, researched reinforcement learning, computer security, and uncertainty
- - Second Postdoc: University of Warwick, Machine Learning Group, led research on machine learning, causality, and abstraction under Prof. Theo Damoulas
Background
- Currently a tenure-track associate professor in the Machine Learning Group at the University of Bergen and an honorary associate professor at the University of Warwick. Research interests focus on structural causal models and causal abstraction, as well as methodologies for learning and exploiting abstraction in machine learning and reinforcement learning. Also interested in the systematization of machine learning and its intersections with physics, politics, economics, and philosophy.
Miscellany
- Delivered talks on topics such as causal models, reinforcement learning applications, and information bottleneck at Kyoto University, OsloMet AI Seminar, ECML Workshop on AI for Social Good (SoGood), and ROBIN Seminar.
