Picture of Hugo Cisneros

Machine Leaning Engineer

33 rue Faubourg Saint-Antoine

75011 Paris, France
[email protected]

Short Bio

I am a Machine Learning engineer at Inicio. Incio is a company identifying high-potential land for the development of photovoltaic projects. My job is to leverage ML algorithms to extract data from various sources. I also work a lot with GIS tools.

Previously, I was a PhD student at the Czech Institute for Informatics, Robotics and Cybernetics (CIIRC, CTU in Prague), part of the Impact Project, and the Willow team, of INRIA and ENS. I conducted my PhD under the supervision of Tomas Mikolov (CIIRC, CTU in Prague) and Josef Sivic (CIIRC, Inria and ENS Paris). Before that, I got a Master’s degree in Mathematics, Vision, and Machine learning from École Normale Supérieure Paris-Saclay, and a Master’s degree in Engineering with a major in Computer Science at Mines ParisTech.

My research focused on the development of unsupervised machine learning algorithms capable of innovation and adaptation. I studied complex systems like cellular automata and open-ended evolution.

I am generally interested in the emergence and growth of complexity in dynamical systems and how this could lead to open-ended evolving systems. During my PhD, I have studied cellular automata and their continuous extensions as they are general and simple yet capable of surprisingly complex emergent behaviors.



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Preserving Semantics in Textual Adversarial Attacks
In ECAI 2023, 2023.
A simple sentence encoder based on multiple words level embeddings to improve the quality of textual adversarial attacks. Improves the quality of attacks compared to other semantic similarity metrics such as Universal Sentence Encoder or BERTScore.
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Benchmarking Learning Efficiency in Deep Reservoir Computing
In Proceeding of the 1st Conference on Lifelong Learning Agents (CoLLAs), 2022.
Defines a metric of learning efficiency for machine learning models and a benchmark of progressively more difficult language tasks for measuring learning efficiency.
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Visualizing computation in large-scale cellular automata
In Artificial Life Conference Proceedings, 2020.
Introduces novel reduction methods for processing large-scale complex systems. This enables discovering interesting patterns at multiple scales.
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Evolving Structures in Complex Systems
In Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence, SSCI, 2019.
Introduces a new metric of increasing complexity for cellular automata and other systems.