PhD in Artificial Intelligence · Oregon State University | Research Trainee @ RIKEN AIP
Matteo Ceriscioli
I am a PhD student in Artificial Intelligence at Oregon State University, working with Prof. Karthika Mohan in the Causal Intelligence and Reasoning Laboratory and a Research Trainee at RIKEN AIP in Japan, working in the Causal Inference team led by Prof. Shohei Shimizu. My objective is to develop the foundations for robust and reliable AI systems that understand the world, are able to adapt to changes, and operate safely.
"Robust AI doesn't just react to change, it learns the rules behind it."
Earlier, I interned at Vodafone Germany in the Deep Insights Consumer Data Science team, under the supervision of Dr. Rolf Bardeli, where I developed causal reasoning tools and designed Graph Neural Networks for community detection tasks as part of my Master's degree in Artificial Intelligence and Data Science at the Heinrich-Heine University Düsseldorf, with Prof. Paul Swoboda as my thesis supervisor. Before that, I completed my Bachelor's degree in Mathematics at the University of Trento, Italy, where I wrote a thesis on Hopfield networks under the supervision of Prof. Alberto Montresor.
You can find a recent interview for AIHub about my research here.
Publications
Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings
@misc{ceriscioli2026generalizingidentifiabilityresultscausal,
title={Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings},
author={Matteo Ceriscioli and Shohei Shimizu and Mallika Gupta and Karthika Mohan},
year={2026},
eprint={2610.19211},
archivePrefix={arXiv},
primaryClass={stat.ML},
url={https://arxiv.org/abs/2610.19211},
}
Planning under Distribution Shifts with Causal POMDPs
@inproceedings{ceriscioli2026planning,
author = {Ceriscioli, M. and Mohan, K.},
title = {Planning Under Distribution Shifts with Causal {POMDPs}},
booktitle = {Proceedings of the International Conference on Automated Planning and Scheduling},
volume = {36},
number = {1},
pages = {367--371},
year = {2026},
doi = {10.1609/icaps.v36i1.42847},
url = {https://doi.org/10.1609/icaps.v36i1.42847}
}
Eliciting Causal Knowledge from Agents
@inproceedings{ceriscioli2026eliciting,
author = {Ceriscioli, M.},
title = {Eliciting Causal Knowledge from Agents},
booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
volume = {40},
number = {48},
pages = {41036--41037},
year = {2026},
doi = {10.1609/aaai.v40i48.42144},
url = {https://doi.org/10.1609/aaai.v40i48.42144}
}
Discovering Linear Non-Gaussian Models for All Categories of Missing Data (Student Abstract)
@inproceedings{ceriscioli2026discovering,
author = {Ceriscioli, M. and Shimizu, S. and Mohan, K.},
title = {Discovering Linear Non-{G}aussian Models for All Categories of Missing Data (Student Abstract)},
booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
volume = {40},
number = {48},
pages = {41151--41153},
year = {2026},
doi = {10.1609/aaai.v40i48.42195},
url = {https://doi.org/10.1609/aaai.v40i48.42195}
}
Agents Robust to Distribution Shifts Learn Causal World Models Even Under Mediation
@inproceedings{
ceriscioli2025agents,
title={Agents Robust to Distribution Shifts Learn Causal World Models Even Under Mediation},
author={Matteo Ceriscioli and Karthika Mohan},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
year={2025},
url={https://openreview.net/forum?id=JvHif4fyeP}
}
Causal Discovery via Adaptive Agents in Multi-Agent and Sequential Decision Tasks
@inproceedings{
ceriscioli2025causal,
title={Causal Discovery via Adaptive Agents in Multi-Agent and Sequential Decision Tasks},
author={Matteo Ceriscioli and Karthika Mohan},
booktitle={The Seventeenth Workshop on Adaptive and Learning Agents},
year={2025},
url={https://openreview.net/forum?id=CcyLwtPfat}
}
Causal Discovery with Adaptable AI Agents
@inproceedings{
ceriscioli2025causal,
title={Causal Discovery with Adaptable {AI} Agents},
author={Matteo Ceriscioli and Karthika Mohan},
booktitle={AAAI 2025 Workshop on Artificial Intelligence with Causal Techniques},
year={2025},
url={https://openreview.net/forum?id=FY5RYxJCQJ}
}
Talks
Planning Under Distribution Shifts with Causal POMDPs.
• The 36th International Conference on Automated Planning and Reasoning (ICAPS-26), 30th June 2026.
Eliciting Causal Knowledge from Agents.
• The 40th Annual AAAI Conference on Artificial Intelligence (AAAI-26) Doctoral Consortium, 21st January 2026.
Robust AI doesn't just react to change, it learns the rules behind it.
• Institute of Scientific and Industrial Research (SANKEN), Osaka University, 20th June 2025.
• The 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-25) W1: Adaptive and Learning Agents, 19th May 2025.
• Oregon State University AI Week, 30th April 2025.
Service
Causal Intelligence Association at Oregon State University.
6th edition of the Annual Conference on Causal Learning and Reasoning (CLeaR-27).
30th edition of the Annual Conference on Artificial Intelligence and Statistics (AISTATS-27).
40th edition of the Annual Conference on Neural Information Processing Systems (NeurIPS-26). Recognized as a top reviewer (top 8%).
18th edition of the Adaptive and Learning Agents workshop (ALA) at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS-26), reviewing and evaluating submissions.
2nd edition of the Causal Neurosymbolic AI workshop (Causal-NeSy) at the European Semantic Web Conference (ESWC-26), reviewing and evaluating submissions.
Neurocomputing, an international peer-reviewed journal published by Elsevier, featuring research on neural computation, machine learning, and computational intelligence.
Behaviormetrika, an international peer-reviewed journal of the Behaviormetric Society of Japan, publishing research in data science and statistical modeling.
39th edition of the Annual Conference on Neural Information Processing Systems (NeurIPS-25). December 1–8, 2025. San Diego, California, USA.
39th edition of the Annual AAAI Conference on Artificial Intelligence (AAAI-25). February 25 – March 4, 2025. Philadelphia, Pennsylvania, USA.
Let's Connect.
Open to research collaborations and interesting conversations about causality and AI.