David Vazquez
Director of Research Programs
Research Management
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
Constraining Representations Yields Models That Know What They Don't Know.
International Conference of Learning Representations (ICLR),
2023.
FigGen: Text to Scientific Figure Generation.
International Conference of Learning Representations (ICLR),
2023.
Knowledge Hypergraph Embedding Meets Relational Algebra.
Journal of Machine Learning Research,
2023.
Workflow discovery in low data regimes.
Transactions on Machine Learning Research,
2023.
Flaky Performances when Pretraining on Relational Databases.
AAAI-23 Student Abstract and Poster Program,
2023.
Leveraging Human Preferences to Master Poetry.
AAAI Workshops,
2023.
OCR-VQGAN: Taming Text-within-Image Generation.
Winter Conference on Applications of Computer Vision (WACV),
2023.
Haptics-based Curiosity for Sparse-reward Tasks.
Conference on Robot Learning (CoRL),
2022.
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding.
ArXiv,
2022.
Constraining Low-level Representations to Define Effective Confidence Scores.
Workshop at the Neural Information Processing Systems (NeurIPS),
2022.
Contrastive Self-supervision Defines General-Purpose Similarity Functions.
Workshop at the Neural Information Processing Systems (NeurIPS),
2022.
Implicit Offline Reinforcement Learning via Supervised Learning.
Workshop at the Neural Information Processing Systems (NeurIPS),
2022.
Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation.
British Machine Vision Conference (BMVC),
2022.
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models.
Montreal AI Symposium (MAIS),
2022.
Explainable, Sensible and Virtuous Workplace Chatbots.
Montreal AI Symposium (MAIS),
2022.
Leveraging Activation Patterns to Define Classifiers Able to Detect and Reject Anomalies.
Montreal AI Symposium (MAIS),
2022.
S-LLM: Semi-Supervised Large Language Model for Chat Summarization.
Montreal AI Symposium (MAIS),
2022.
Overcoming challenges in leveraging GANs for few-shot data augmentation.
Workshop at the Conference on Lifelong Learning Agents (CoLLAs),
2022.
Flaky Performances when Pre-Training on Relational Databases with a Plan for Future Characterization Efforts.
Workshop at the International Conference on Machine Learning (ICML),
2022.
Multi-label Iterated Learning for Image Classification with Label Ambiguity.
Computer Vision and Pattern Recognition (CVPR),
2022.
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models.
Workshop at the Annual Meetings of the Association for Computational Linguistics (ACL),
2022.
A Probabilistic Perspective on Reinforcement Learning via Supervised Learning.
Workshop at the International Conference on Learning Representations (ICLR),
2022.
Object-centric Compositional Imagination for Visual Abstract Reasoning.
Workshop at the International Conference on Learning Representations (ICLR),
2022.
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark.
Workshop at the Neural Information Processing Systems (NeurIPS),
2021.
A Survey of Self-Supervised and Few-Shot Object Detection.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
2021.
A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images.
IEEE Journal of Biomedical and Health Informatics,
2021.
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations.
International Conference on Computer Vision (ICCV),
2021.
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data.
International Conference on Computer Vision (ICCV),
2021.
SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction.
Workshop at the International Conference on Computer Vision (ICCV),
2021.
3D Perception with Slanted Stixels on GPU.
IEEE Transactions on Parallel and Distributed Systems,
2021.
Weakly Supervised Underwater Fish Segmentation Using Affinity LCFCN.
Nature Scientific Reports,
2021.
A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images.
Winter Conference on Applications of Computer Vision (WACV),
2021.
Learning Data Augmentation with Online Bilevel Optimization for Image Classification.
Winter Conference on Applications of Computer Vision (WACV),
2021.
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery.
Workshop at the Neural Information Processing Systems (NeurIPS),
2020.
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.
Conference on Neural Information Processing Systems (NeurIPS),
2020.
Synbols: Probing Learning Algorithms with Synthetic Datasets.
Conference on Neural Information Processing Systems (NeurIPS),
2020.
LOOC: Localize Overlapping Objects with Count Supervision.
International Conference on Image Processing (ICIP),
2020.
Proposal-based Instance Segmentation with Point Supervision.
International Conference on Image Processing (ICIP),
2020.
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions.
Artificial Intelligence Journal,
2020.
Knowledge Hypergraphs: Prediction Beyond Binary Relations.
International Join Conference on Artificial Intelligence (IJCAI),
2020.
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.
Workshop at the Conference on Computer Vision and Pattern Recognition (CVPR),
2020.
Knowledge Hypergraphs: Prediction Beyond Binary Relations.
Workshop at the Association for the Advancement of Artificial Intelligence (AAAI),
2020.
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis.
Nature Scientific Reports,
2020.
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation.
Women in Machine Learning (WiML),
2019.
Knowledge Hypergraphs: Prediction Beyond Binary Relations.
Women in Machine Learning (WiML),
2019.
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation.
Workshop at the International Conference on Computer Vision (ICCV),
2019.
Fourier-CPPNs for Image Synthesis.
Workshop at the International Conference on Computer Vision (ICCV),
2019.
Where are the Masks: Instance Segmentation with Image-level Supervision.
Britsh Machine Vision Conference (BMVC),
2019.
Context-Aware Visual Compatibility Prediction.
Computer Vision and Pattern Recognition (CVPR),
2019.
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation.
International Journal in Computer Vision (IJCV),
2019.
Adversarial Learning of General Transformations for Data Augmentation.
Workshop at the International Conference on Learning Representations (ICLR),
2019.
Where are the Blobs: Counting by Localization with Point Supervision.
European Conference on Computer Vision (ECCV),
2018.
Synbols: Probing Learning Algorithms with Synthetic Datasets.
Montreal AI Symposium (MAIS),
2018.
Slanted Stixels: A way to represent steep streets.
International Journal in Computer Vision (IJCV),
2018.
Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation.
Workshop at the International Conference on Learning Representations (ICLR),
2018.
Learning to Remove Rain in Traffic Surveillance by Using Synthetic Data.
International Conference on Computer Vision Theory and Applications (VISIGRAPP),
2018.