Scholar
David Acuna
Google Scholar ID: 9aFd9dEAAAAJ
University of Toronto, NVIDIA
Citations & Impact
Citations
4,380
H-index
22
i10-index
31
Publications
20
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- Recipient of the 2020 Microsoft Ada Lovelace Fellowship.
- Multiple papers accepted to top-tier conferences including NeurIPS, CVPR, ICCV, EMNLP, ECCV, ICLR, AISTATS, ICML, TMLR, CoLM, and ICRA.
- Several papers selected for oral presentations (e.g., CVPR 2020 Oral, CVPR 2019 Oral).
- CVPR 2019 paper 'STEAL' featured in media outlets such as VentureBeat and NVIDIA Developer Center.
- Polygon-RNN++ and 'Training DeepNets with Synth Data' recognized by MIT DeepLearning as Breakthrough Developments of 2017–2018 and listed among 'the 10 coolest papers from CVPR 2018' by TowardsDataScience.
Background
- Currently a Senior Research Scientist at NVIDIA Research in the Language and Cognition Research Group, working with Yejin Choi.
- Research focuses on reasoning models, with emphasis on synthetic data, inference-time scaling, agents, reinforcement learning (RL), and the role of data synthesis and reasoning in the path toward AGI and Physical AI.
- Particularly interested in optimal strategies for adapting foundation models to deliver enterprise value.
- Past work includes synthetic data generation and domain adaptation for visual learning.
- Broad research interests span representation learning, model adaptation, controllable generation, synthetic data, optimization, generative modeling, scene understanding, and low-level vision.
