Rafael Pardinas

Applied Research Scientist

Human Machine Interaction Through Language

Rafael is an Applied Research Scientist at ServiceNow Research with an extensive background in software engineering and distributed systems. His current work focuses on fundamental and applied Machine Learning research.

Rafael holds a MSc. in Computer Science and a BSc. in Physics; the combination of which has provided a good foundation towards his current role in Reinforcement Learning and Natural Language Processing research. For the last two years, he has been mostly focusing on Deep Reinforcement Learning projects, specifically Offline RL, Policy Optimization, RL driven Energy-Based Models, and the intersection between RL and NLP.

Interests

Reinforcement Learning

Publications

Leveraging Human Preferences to Master Poetry. Rafael Pardinas, Gabriel Huang, David Vazquez, Alexandre Piche. At AAAI Workshops, 2023.

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Implicit Offline Reinforcement Learning via Supervised Learning. Alexandre Piche, Rafael Pardinas, David Vazquez, Igor Mordatch, Christopher Pal. At Workshop at the Neural Information Processing Systems (NeurIPS), 2022.

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A Probabilistic Perspective on Reinforcement Learning via Supervised Learning. Alexandre Piche, Rafael Pardinas, David Vazquez, Christopher Pal. At Workshop at the International Conference on Learning Representations (ICLR), 2022.

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LOOC: Localize Overlapping Objects with Count Supervision. Issam H. Laradji, Rafael Pardinas, Pau Rodriguez, David Vazquez. At International Conference on Image Processing (ICIP), 2020.

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Objects of violence: synthetic data for practical ML in human rights investigations. Lachlan Kermode, Jan Freyberg, Alican Akturk, Robert Trafford, Denis Kocetkov, Rafael Pardinas, Eyal Weizman, Julien Cornebise. At Workshop at the Neural Information Processing Systems (NeurIPS), 2019.

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