Scholar
Shangqian Gao
Google Scholar ID: 9mNI83oAAAAJ
Florida State University
Citations & Impact
Citations
1,383
H-index
20
i10-index
31
Publications
20
Co-authors
15
list available
Publications
Resume (English only)
Academic Achievements
- Published extensively in top-tier venues including NeurIPS, ICLR, CVPR, ICCV, ECCV, AAAI, EMNLP, NAACL, WACV, TPAMI, and JMLR
- Four papers accepted by NeurIPS 2025 on diffusion model compression, bias mitigation, LLM routing, and federated learning; one paper on controlling memorization accepted by EMNLP 2025
- Serving as Area Chair for ICLR 2026 and NeurIPS 2025
- One paper on unlearning for compressed diffusion models accepted by CVPR 2025
- Two papers accepted by ICLR 2025 (LLM compression and prompt-based expert routing for text-to-image diffusion models); one paper on depth pruning for LLMs accepted by NAACL 2025
- One paper on LLM memorization accepted by EMNLP 2024; one on dimension-independent structural pruning for LLMs accepted by NeurIPS 2024
- Four papers accepted by CVPR 2024; one each by AAAI 2024 and NAACL 2024
- Publications in ICCV 2023, EMNLP 2023, WACV 2024, ICLR 2023, PAMI, and AAAI 2023
- Accepted papers at NeurIPS 2022 and ECCV 2022 (three papers); served as reviewer for CVPR 2023, ICLR 2023, and NeurIPS 2022
Background
- Assistant Professor in the Department of Computer Science at Florida State University
- Research interests include: Efficient Machine Learning (model compression for DNNs and LLMs, differentiable neural architecture search)
- Efficient and Safe Cross-Modal Learning (adversarial attack and defense on cross-modal data, efficient vision-language transformers and cross-modal DNNs)
- Policy Gradient Methods for Reinforcement Learning (variance-reduced policy gradient methods based on momentum techniques and mirror descent)
- Zeroth-order optimization methods, fairness in deep learning, and interpretation-guided models
