David Vazquez

Manager 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. João Monteiro, Pau Rodriguez, Pierre-André Noël, Issam H. Laradji, David Vazquez. At International Conference of Learning Representations (ICLR), 2023.

Flaky Performances when Pretraining on Relational Databases. Shengchao Liu, David Vazquez, Jian Tang, Pierre-André Noël. At AAAI-23 Student Abstract and Poster Program, 2023.

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

OCR-VQGAN: Taming Text-within-Image Generation. Juan A. Rodriguez, David Vazquez, Marco Pedersoli, Issam H. Laradji, Pau Rodriguez. At Winter Conference on Applications of Computer Vision (WACV), 2023.

Haptics-based Curiosity for Sparse-reward Tasks. Sai Rajeswar, Cyril Ibrahim, Nitin Surya, Florian Golemo, David Vazquez, Aaron Courville, Pedro O. Pinheiro. At Conference on Robot Learning (CoRL), 2022.

Constraining Low-level Representations to Define Effective Confidence Scores. João Monteiro, Pau Rodriguez, Pierre-André Noël, Issam H. Laradji, David Vazquez. At Workshop at the Neural Information Processing Systems (NeurIPS), 2022.

Contrastive Self-supervision Defines General-Purpose Similarity Functions. Charles Guille-Escuret, Pau Rodriguez, David Vazquez, Ioannis Mitliagkas, João Monteiro. At Workshop at the Neural Information Processing Systems (NeurIPS), 2022.

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.

Consistency-CAM: Towards Improved Weakly Supervised Semantic Segmentation. Sai Rajeswar Mudumba, Issam H. Laradji, Pau Rodriguez, David Vazquez, Aaron Courville. At British Machine Vision Conference (BMVC), 2022.

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. Gaurav Sahu, Pau Rodriguez, Issam H. Laradji, Parmida Atighhehchian, David Vazquez, Dzmitry Bahdanau. At Montreal AI Symposium (MAIS), 2022.

Explainable, Sensible and Virtuous Workplace Chatbots. Gabriel Huang, Valérie Bécaert, David Vazquez. At Montreal AI Symposium (MAIS), 2022.

Leveraging Activation Patterns to Define Classifiers Able to Detect and Reject Anomalies. João Monteiro, Pau Rodriguez, Pierre-André Noël, Issam H. Laradji, David Vazquez. At Montreal AI Symposium (MAIS), 2022.

S-LLM: Semi-Supervised Large Language Model for Chat Summarization. Issam H. Laradji, Sathwik Tejaswi Madhusudhan, Orlando Marquez, Pau Rodriguez, David Vazquez. At Montreal AI Symposium (MAIS), 2022.

Overcoming challenges in leveraging GANs for few-shot data augmentation. Christopher Beckham, Issam H. Laradji, Pau Rodriguez, David Vazquez, Derek Nowrouzezahrai, Christopher Pal. At 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. Shengchao Liu, David Vazquez, Jian Tang, Pierre-André Noël. At Workshop at the International Conference on Machine Learning (ICML), 2022.

Multi-label Iterated Learning for Image Classification with Label Ambiguity. Sai Rajeswar Mudumba, Pau Rodriguez, Soumye Singhal, David Vazquez, Aaron Courville. At Computer Vision and Pattern Recognition (CVPR), 2022.

Data Augmentation for Intent Classification with Off-the-shelf Large Language Models. Gaurav Sahu, Pau Rodriguez, Parmida Atighhehchian, Issam H. Laradji, David Vazquez, Dzmitry Bahdanau. At Workshop at the Annual Meetings of the Association for Computational Linguistics (ACL), 2022.

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.

Object-centric Compositional Imagination for Visual Abstract Reasoning. Rim Assouel, Perouz Taslakian, David Vazquez, Pau Rodriguez, Yoshua Bengio. At Workshop at the International Conference on Learning Representations (ICLR), 2022.

Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. Alexandre Lacoste, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, Pau Rodriguez, David Vazquez, Evan D. Sherwin. At Workshop at the Neural Information Processing Systems (NeurIPS), 2021.

A Survey of Self-Supervised and Few-Shot Object Detection. Gabriel Huang, Issam H. Laradji, David Vazquez, Simon Lacoste-Julien, Pau Rodriguez. At IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021.

A Deep Learning Localization Method for Measuring Abdominal Muscle Dimensions in Ultrasound Images. Alzayat Saleh, Issam H. Laradji, Corey Lammie, David Vazquez, Carol A Flavell, Mostafa Rahimi Azghadi. At IEEE Journal of Biomedical and Health Informatics, 2021.

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. Pau Rodriguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vazquez. At International Conference on Computer Vision (ICCV), 2021.

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. Oscar Manas, Alexandre Lacoste, Xavier Giro-i-Nieto, David Vazquez, Pau Rodriguez. At International Conference on Computer Vision (ICCV), 2021.

SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction. Issam H. Laradji, Pau Rodriguez, David Vazquez, Derek Nowrouzezahrai. At Workshop at the International Conference on Computer Vision (ICCV), 2021.

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3D Perception with Slanted Stixels on GPU. Daniel Hernandez, Antonio Espinosa, David Vazquez, Antonio M. Lopez, Juan C. Moure. At IEEE Transactions on Parallel and Distributed Systems, 2021.

Weakly Supervised Underwater Fish Segmentation Using Affinity LCFCN. Issam H. Laradji, Alzayat Saleh, Pau Rodriguez, Derek Nowrouzezahrai, Mostafa Rahimi Azghadi, David Vazquez. At Nature Scientific Reports, 2021.

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images. Issam H. Laradji, Pau Rodriguez, Oscar Manas, Keegan Lensink, Marco Law, Lironne Kurzman, David Vazquez, Derek Nowrouzezahrai, William A Parker. At Winter Conference on Applications of Computer Vision (WACV), 2021.

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Learning Data Augmentation with Online Bilevel Optimization for Image Classification. Saypraseuth Mounsaveng, Issam H. Laradji, Ismail Ben Ayed, David Vazquez, Marco Pedersoli. At Winter Conference on Applications of Computer Vision (WACV), 2021.

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. Issam H. Laradji, Pau Rodriguez, Alfredo Kalaitzis, David Vazquez, Ross Young, Ed Davey, Alexandre Lacoste. At Workshop at the Neural Information Processing Systems (NeurIPS), 2020.

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vazquez, Laurent Charlin. At Conference on Neural Information Processing Systems (NeurIPS), 2020.

Synbols: Probing Learning Algorithms with Synthetic Datasets. Alexandre Lacoste, Pau Rodriguez, Frederic Branchaud, Parmida Atighhehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vazquez. At Conference on Neural Information Processing Systems (NeurIPS), 2020.

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

Proposal-based Instance Segmentation with Point Supervision. Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vazquez, Mark Schmidt. At International Conference on Image Processing (ICIP), 2020.

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CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions. Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vazquez, German I. Parisi, Nikhil Churamani, Marc Pickett, Issam H. Laradji, Davide Maltoni. At Artificial Intelligence Journal, 2020.

Knowledge Hypergraphs: Prediction Beyond Binary Relations. Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole. At International Join Conference on Artificial Intelligence (IJCAI), 2020.

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vazquez, Laurent Charlin. At Workshop at the Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

Knowledge Hypergraphs: Prediction Beyond Binary Relations. Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole. At Workshop at the Association for the Advancement of Artificial Intelligence (AAAI), 2020.

A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis. Alzayat Saleh, Issam H. Laradji, Dmitry A Konovalov, Michael Bradley, David Vazquez, Marcus Sheaves. At Nature Scientific Reports, 2020.

Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation. Lironne Kurzman, David Vazquez, Issam H. Laradji. At Women in Machine Learning (WiML), 2019.

Knowledge Hypergraphs: Prediction Beyond Binary Relations. Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole. At Women in Machine Learning (WiML), 2019.

Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation. Lironne Kurzman, David Vazquez, Issam H. Laradji. At Workshop at the International Conference on Computer Vision (ICCV), 2019.

Fourier-CPPNs for Image Synthesis. Mattie Tesfaldet, Xavier Snelgrove, David Vazquez. At Workshop at the International Conference on Computer Vision (ICCV), 2019.

Where are the Masks: Instance Segmentation with Image-level Supervision. Issam H. Laradji, David Vazquez, Mark Schmidt. At Britsh Machine Vision Conference (BMVC), 2019.

Context-Aware Visual Compatibility Prediction. Guillem Cucurull, Perouz Taslakian, David Vazquez. At Computer Vision and Pattern Recognition (CVPR), 2019.

Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation. Sai Rajeswar Mudumba, Fahim Mannan, Florian Golemo, Jérôme Parent-Lévesque, David Vazquez, Derek Nowrouzezahrai, Aaron Courville. At International Journal in Computer Vision (IJCV), 2019.

Adversarial Learning of General Transformations for Data Augmentation. Saypraseuth Mounsaveng, David Vazquez, Ismail Ben Ayed, Marco Pedersoli. At Workshop at the International Conference on Learning Representations (ICLR), 2019.

Where are the Blobs: Counting by Localization with Point Supervision. Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vazquez, Mark Schmidt. At European Conference on Computer Vision (ECCV), 2018.

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Synbols: Probing Learning Algorithms with Synthetic Datasets. Alexandre Lacoste, Pau Rodriguez, Frédéric Branchaud-Charron, Parmida Atighhehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vazquez. At Montreal AI Symposium (MAIS), 2018.

Slanted Stixels: A way to represent steep streets. Daniel Hernandez, Lukas Schneider, Pau Cebrian, Antonio Espinosa, David Vazquez, Antonio M. Lopez, Uwe Franke, Marc Pollefeys, Juan C. Moure. At International Journal in Computer Vision (IJCV), 2018.

Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation. Lironne Kurzman, David Vazquez, Issam H. Laradji. At Workshop at the International Conference on Learning Representations (ICLR), 2018.

Learning to Remove Rain in Traffic Surveillance by Using Synthetic Data. Chris H. Bahnsen, David Vazquez, Antonio M. Lopez, Thomas B. Moeslun. At International Conference on Computer Vision Theory and Applications (VISIGRAPP), 2018.

3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding. Lorenzo Pellegrini, Chenchen Zhu, Fanyi Xiao, Zhicheng Yan, Antonio Carta, Matthias De Lange, Vincenzo Lomonaco, Roshan Sumbaly, Pau Rodriguez, David Vazquez. At ArXiv, 2017.

Workflow discovery in low data regimes. Amine El Hattami, Issam H. Laradji, Stefania Raimondo, David Vazquez, Pau Rodriguez, Christopher Pal. At Transactions on Machine Learning Research, 2017.