胡庆浩，副高，博士，中国科学院自动化研究所副研究员，中国图象图形学会会员、CSIG视觉大数据专委会委员。研究领域包括深度网络加速与压缩、类脑计算等方向，在TNNLS、TMM、CVPR、ECCV、AAAI等国际期刊和会议发表论文30余篇，主持国家自然科学基金青年基金、科技部2030新一代人工智能重大项目子课题、国家电网企业横向委托项目等科研项目，参与中科院战略先导、国家重点研发计划等研发项目

深度神经网络轻量化

1.面向移动计算的深度神经网络自动轻量化研究，国家自然科学基金青年科学基金项目 ，30万， 负责人
2.输变电设备可视缺陷识别模型前端化移植技术，企业委托，山东济南供电公司，238万，负责人
3.基于轻量化模型的输电通道隐患智能分析，企业委托，山东信通电子股份有限公司，80万，负责人
4.博弈智能对抗演练场基础理论与平台子课题, 科技创新 2030-“新一代人工智能（2030）”重大项目，283万，负责人
5.国产自主可控多模态大模型关键技术及示范应用任务二：大模型高效分布式训练与压缩技术，北京市基金项目，任务二经费100万，任务负责人。
6.电力异构融合类脑计算模型研发技术，国家电网科技项目，372万，课题负责人

[1]Zeyu Zhu, Fanrong Li, Gang Li, Zejian Liu, Zitao Mo, Qinghao Hu, Xiaoyao Liang, Jian Cheng. MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization. The International Symposium on High-Performance Computer Architecture (HPCA), 2024.
[2]Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng. A2Q:Aggregation-Aware Quantization for Graph Neural Networks. The International Conference on Learning Representations (ICLR), 2023.
[3] Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng. A2Q:Aggregation-Aware Quantization for Graph Neural Networks. The International Conference on Learning Representations (ICLR), 2023.
[4][Zhixiang Ye*, Qinghao Hu*, Tianli Zhao, Wangping Zhou, Jian Cheng. MCUNeRF: Packing NeRF into an MCU with 1MB Memory. ACM International Conference on Multimedia(ACM MM) ，2023
[5]Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong, Guanghui Wang. Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets. IEEE Winter Conference on Applications of Computer Vision (WACV)，2023
[6]Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng.PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerator.European Conference on Computer Vision (ECCV), 2022
[7]Qiang Chen, Qiman Wu, Jian Wang, Qinghao Hu*, Tao Hu, Errui Ding, Jian Cheng, Jingdong Wang. Mixformer: Mixing features across windows and dimension. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)，2022
[8]Xing Lan, Qinghao Hu, Jian Cheng.ATF: An Alternating Training Framework for Weakly Supervised Face Alignment. IEEE Transactions on Multimedia (TMM)，2022
[9]Tianli Zhao, Qinghao Hu, Xiangyu He, Weixiang Xu, Jiaxing Wang, Cong Leng, Jian Cheng.ECBC: Efficient convolution via blocked columnizing. IEEE Transactions on Neural Networks and Learning Systems (TNNLS),  2021
[10]Guan’An Wang, Qinghao Hu,Yang Yang,Jian Cheng, Zeng-Guang Hou. Adversarial Binary Mutual Learning for Semi-Supervised Deep Hashing.IEEE Transactions on Neural Networks and Learning Systems (TNNLS)，2021
[11]Qinghao Hu, Gang Li, Peisong Wang, Yifan Zhang, Jian Cheng. Training Binary Weight Networks via Semi-Binary Decomposition. European Conference on Computer Vision (ECCV), 2018
[12]Qinghao Hu, Peisong Wang, Jian Cheng. From Hashing to CNNs: Training Binary Weight Networks via Hashing. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018
[13]Peisong Wang, Qinghao Hu, Yifan Zhang, Chunjie Zhang, Yang Liu, Jian Cheng. Two-Step Quantization for Low-bit Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition(CVPR 2018)
[14]Qinghao Hu, Jiaxiang Wu, Jian Cheng, Lifang Wu, Hanqing Lu. Pseudo label based unsupervised deep discriminative hashing for image retrieval. ACM International Conference on Multimedia(ACM MM）,2017
Qinghao Hu, Jiaxiang Wu, Lu Bai, Yifan Zhang, Jian Cheng. Fast k-means for large scale clustering. The 26th ACM International Conference on Information and Knowledge Management(CIKM)， 2017

1. 2019年ICCV轻量化人脸识别挑战赛 第二名
2. 2019年Nvidia 奖学金
3. 2015年MSR-Bing 图像识别挑战赛第一名

(1) 程健; 胡庆浩 ; 深度神经网络加速与压缩方法及装置, 2020-12-25, 中国,
ZL201810088723.X (专利)
(2) 胡庆浩; 王培松; 李成华; 辛淼; 程健 ; 一种人工智能自动避障行走底盘, 2021-3-19, 中国,
ZL201911365547.0 (专利)
(3) 兰星; 胡庆浩 ; 一种基于唇语指令的终端解锁方法, 2021-11-19, 中国,
ZL201911045860.6 (专利)