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@hugcis
Created March 8, 2023 09:29
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Resume source markdown+HTML in my personal website
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Hugo Cisneros' resume

Resume

For a PDF version, see here


Personal Data


Work Experience

Apr - Sep 2019

CIIRC (Czech Institute of Informatics, Robotics and Cybernetics) Research Intern, Prague

Under the supervision of Tomas Mikolov (Facebook AI). Studied emergence, complexity and spontaneous organization in complex systems and their applications to Artificial intelligence. Resulted in a conference paper.

Mar - Sep 2018

INRIA and CNRS (LIMSI) Research Intern, Paris

Under the supervision of Xavier Tannier and Ioana Manolescu. Built a software for extracting and integrating multiple data sources with NLP and data processing algorithms for data journalism. Worked with journalists from Le Monde (Les Decodeurs) on automating their data processing pipelines and using NLP for their investigations. Reviewed literature on machine learning in graphs, automatic knowledge base construction and natural language processing for fact checking.

Jun - Sep 2017 and (Part-time) Oct 2017 - Mar 2018

Aiden.ai (start-up, acquired by Twitter) Software engineering and Machine Learning Research Intern, London

Worked on building an AI powered virtual colleague for Marketing analysts based on Natural Language Processing. Participated in implementing the chat interface and the Natural Language recognition system with Javascript. Implemented Machine learning algorithms with Python for predicting marketing data, classifying and clustering users. (Report)

Sep 2016 - Feb 2017

ENS Ulm, Kastler-Brossel Laboratory Research assistant, Paris

Light control and propagation in amplified multimode fibers (report)

Implemented and optimized finite elements simulations with Python and Matlab. Performed high performance computing on scientific calculation clusters. Worked with a PhD candidate on building a tool for optimizing the propagation of a light beam in optical fibers.

Education

Nov 2019 - Current

PhD Student INRIA Willow, CIIRC CTU , Paris & Prague

Unsupervised learning with Complex Systems and Evolution

Sep 2018 - Sep 2019

MVA Master in Machine Learning and Applied Mathematics, ENS Paris Saclay, Paris

Relevant Coursework: Convex Optimization, Probabilistic Graphical Models, Computer Vision, Reinforcement Learning, Deep Learning, Speech and Natural language processing, Kernel Methods, Biostatistics, Theoretical Foundations of Deep Learning. (GPA: 16.2 / 20)

Sep 2015 - Sep 2018

Master of Science in Engineering, Mines ParisTech, Paris

Specialization: Computer Science - (3.7 GPA) Relevant Coursework: Machine Learning, Probabilities, Statistics, Programming

Sep 2013 - Aug 2015

Preparatory class for Grandes Ecoles Lycée Stanislas (Paris) MPSI and MP*

Bachelor’s Degree in Mathematics and Physics, national competitive exam for entering engineering school.

Aug 2013

Scientific Baccalauréat (High school diploma in Maths, Physics and Life Sciences) - High distinction

Publications

Cisneros, H., Sivic, J. & Mikolov, T. Evolving Structures in Complex Systems. in 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 230–237 (IEEE, 2019).

Cisneros, H., Sivic, J. & Mikolov, T. Visualizing computation in large-scale cellular automata. Artificial Life Conference Proceedings 32, 239–247 (2020).

Cisneros, H., Mikolov, T. & Sivic, J. Benchmarking Learning Efficiency in Deep Reservoir Computing. Conference on Lifelong Learning Agents (2022).

Herel, D., Cisneros, H., & Mikolov, T. Preserving Semantics in Textual Adversarial Attacks. Pre-print. Under review (2022).

Projects

For a more complete list see my projects page

Jun-Aug 2018

Participated in the n2c2 shared task of Harvard Medical School Cohort Selection for Clinical Trials in a joint team from AP-HP and LIMSI. Implemented weakly-supervised and transfer learning methods for Medical NLP (Keras). Finished 2nd among 30 teams. (preprint)

Jan 2018

Built a Machine Learning based tool for discovering and matching similar arXiv papers based on similarity measures including word embeddings-based similarities of their abstract and co-authorship graph distance.

Feb 2017

Implemented a multi-currency blockchain in Python with a team of 9 people (Cryptography, network programming, team software development)


Languages

English: Fluent (TOEFL 115/120) Spanish: Intermediate
French: Mothertongue Japanese: School level

Programming Skills

Advanced:

Python (Tensorflow, Pytorch, Django), C, Rust, Matlab, Java, Javascript (Node.js, Typescript and Web), LaTeX

Basic:

Scala, Ruby, C++

Interests and Activities

  • Mathematics, Statistics and Probabilities
  • Technology, Open-Source, Programming
  • Running (weekly practise), Fencing, Piano, Guitar

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