黄建强，中国科学院计算机网络信息中心研究员，博士生导师。新加坡南洋理工大学博士。研究方向是构建面向科学智能领域的AI算法与系统，应用在生命科学与材料等学科领域。曾担任科技创新 2030-“新一代人工智能”重大项目课题负责人,获得浙江省科技进步一等奖，获得中国电子学会优秀科技工作者（全国100名），发表国际论文60余篇。
研究面向科学智能领域的AI算法与系统，构建模型即服务的新一代科学智能服务平台。以模型即服务的方式，组织科学数据与AI驱动的科研信息基础设施研制，推进AI在生命科学与材料等学科领域的应用，促进基于新科研范式的重大科技成果产出。
曾担任科技创新 2030-“新一代人工智能”重大项目课题负责人,获得浙江省科技进步一等奖。
以下是黄建强的 Google Scholar 个人主页地址：
https://scholar.google.com.hk/citations?user=UqAybqgAAAAJ&hl=en
[1]K Tang, J Huang, H Zhang, Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect, NeurIPS 2020, 33: pp. 1513-1524.
[2]T Wang, J Huang, H Zhang, Q Sun, Visual Commonsense R-CNN, IEEE/CVF Conference on Computer Vision and Pattern Recognition CVPR 2020: pp. 10760-10770
[3]J Huang, Y Qin, J Qi, H Zhang, Deconfounded Visual Grounding, AAAI 2022 Oral, 36(1), pp. 998-1006
[4]T Wang, Z Yue, J Huang, Q Sun, H Zhang, Self-supervised learning disentangled group representation as feature, NeurIPS 2021, 34: pp. 18225-18240.
[5]J E, M Li, J Huang, CrowdAtlas: Estimating Crowd Distribution within the Urban Rail Transit System. ICDE 2021: pp. 2219-2224
[6]K Liu, P Tong, M Li, Y Wu, J Huang, ST4ML: Machine Learning Oriented Spatio-Temporal Data Processing at Scale. ACM SIGMOD'23/ Proceedings of the ACM on Management of Data, Vol. 1, Issue 1, Article 87, May 2023, pp. 1-24
[7]Yong, H., Huang, J., Hua, X., & Zhang, L. (2020). Gradient centralization: A new optimization technique for deep neural networks. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I 16 (pp. 635-652). Springer International Publishing.
[8]K Tang, Y Niu, J Huang, J Shi, H Zhang，Unbiased scene graph generation from biased training, CVPR 2020, pp. 3716-3725
[9]J Qi, Y Niu, J Huang, H Zhang, Two Causal Principles for Improving Visual Dialog. CVPR 2020, pp. 10860-10869
[10] C He, H Zeng, J Huang, XS Hua, L Zhang. Structure aware single-stage 3d object detection from point cloud. CVPR 2020.