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Héctor Palacios

Research Scientist at Element AI

Hector Palacios is a research scientist specializing in NeuroSymbolic methods for Artificial Intelligence. He focuses on problems involving variable assignment, such as multi-labelled classification, and sequential decision-making scenarios like symbolic planning and task-oriented dialogue.1

Hector's research combines machine learning and symbolic reasoning with two main objectives:

  1. Enhancing pure machine learning methods by integrating symbolic reasoning, domain knowledge, context, and user preferences.
  2. Developing distributional methods with provable guarantees for higher efficiency.1

Recently, Hector worked as a research scientist at the ServiceNow Research Group after ElementAI's acquisition.13 He has since returned to academia, where he has received recognition for his work on AI reasoning and introduced innovative algorithms.1

Hector's recent achievements include:

  • A paper accepted at NeurIPS 2023 titled "Egocentric Planning for Scalable Embodied Task Achievement," which he presented in New Orleans on December 12, 2023.12
  • Publishing work on improving generalization in task-oriented dialogues and scaling up ML-based black-box planning.1

With his expertise in combining various AI techniques, from symbolic models to outputs of pre-trained machine learning models like LLMs, Hector continues to contribute to the field of AI research, particularly in areas such as NLP, vision models, and multi-labelled classification models.1

Highlights

Hector Javier Palacios Obituary February 3, 2024

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Héctor Palacios
Héctor Palacios, photo 1
Héctor Palacios, photo 2
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Location

Montreal, Quebec, Canada