ServiceNow Research

David Vazquez

David Vazquez

Director of Research Programs

Research Management

Leadership team

Leadership team

David is the Manager of Research Programs at ServiceNow Research. He has degrees in Software Engineering from the Universidade de A Coruña (UDC) and Computer Science from the Autonomous University of Barcelona (UAB), which includes a Masters in Computer Vision and Artificial Intelligence and a PhD in Computer Science. He then completed a postdoc at the Computer Vision Center (CVC), as well as a postdoc between CVC and Montreal Institute of Learning Algorithm (MILA). Previously, he worked in Computer Vision applied to the automotive industry. Notably, he worked on Advanced Driver Assistance Systems (ADAS), with a focus on pedestrian detection where he created a driving simulator and adapted it using Domain Adaptation to work in the real world. David also contributed to the creation of an Autonomous Driving simulator and a real Autonomous Vehicle prototype, working mainly on the perception system of the vehicle (Object detection, Semantic Segmentation, 3D reconstruction, SLAM, etc.).

Interests
  • Machine Learning
  • Computer Vision
  • Natural Language Processing
  • Intent Classification
  • Low Supervision

Publications

Workflow discovery in low data regimes. Workshop at the International Conference on Machine Learning (ICML),  2023.

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Object-centric Compositional Imagination for Visual Abstract Reasoning. Workshop at the International Conference on Learning Representations (ICLR),  2022.

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Knowledge Hypergraphs: Prediction Beyond Binary Relations. International Join Conference on Artificial Intelligence (IJCAI),  2020.

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Knowledge Hypergraphs: Prediction Beyond Binary Relations. Workshop at the Association for the Advancement of Artificial Intelligence (AAAI),  2020.

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Fourier-CPPNs for Image Synthesis. Workshop at the International Conference on Computer Vision (ICCV),  2019.

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Learning to Remove Rain in Traffic Surveillance by Using Synthetic Data. International Conference on Computer Vision Theory and Applications (VISIGRAPP),  2018.

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