个人简介
我从2023年7月起任杭电计算机学院的特聘副教授，隶属于杭电的媒体智能实验室。我博士毕业于浙江大学计算机系人工智能方向，本科毕业于浙江大学数学系。我对人工智能的很多研究方向都感兴趣，涉猎广泛；目前主要对人工智能中的深度学习、迁移学习、大模型智能体、强化学习、具身智能进行深入研究；在国际顶级AI会议上发表相关论文20余篇。研究目标是研究和设计算法让AI能够像人类一样的认知和思考，或者具有与人类相当的认知和思考能力。
教育经历
2018年9月– 2023年6月，浙江大学，计算机科学与技术专业，人工智能方向，博士研究生，指导老师: 蔡登，何晓飞 2014年9月– 2018年6月，浙江大学，数学与应用数学专业（竺可桢荣誉培养计划），理科学士
工作经历
2023年7月至今，杭州电子科技大学，计算机学院，特聘副教授
研究领域
深度学习、迁移学习、多模态学习（视觉-语言学习）、大语言模型、大模型智能体、具身智能（包括强化学习和世界模型）
教学与课程
2025年夏学期 论文写作指导 2025年春夏学期 计算机视觉 2025年春夏学期 学科前沿 2025年春夏学期 大学计算机基础
2024年秋学期 论文写作指导（圣光机）
论文
最新、最全论文集请见我的google scholar： https://scholar.google.com/citations?user=xxPcRRQAAAAJ&hl=zh-CN （*为通讯作者或共同一作） Minghao Chen, Yihang Li, Yanting Yang, Shiyu Yu, Binbin Lin, Xiaofei He. AutoManual: Generating Instruction Manuals by LLM Agents via Interactive Environmental Learning. NeurIPS 2024. Minghao Chen, Fangyun Wei, Chong Li, Deng Cai: Frame-wise Action Representations for Long Videos via Sequence Contrastive Learning. CVPR 2022. Minghao Chen, Shuai Zhao, Haifeng Liu, Deng Cai: Adversarial-Learned Loss for Domain Adaptation. AAAI 2020. Minghao Chen, Hongyang Xue, Deng Cai: Domain Adaptation for Semantic Segmentation with Maximum Squares Loss. ICCV 2019. Yanting Yang, Minghao Chen*, Qibo Qiu, Jiahao Wu, Wenxiao Wang, Binbin Lin, Ziyu Guan, Xiaofei He: Adapt2Reward: Adapting Video-Language Models to Generalizable Robotic Rewards via Failure Prompts. ECCV 2024. Yuqi Lin, Minghao Chen*, Kaipeng Zhang, Hengjia Li, Mingming Li, Zheng Yang, Dongqin Lv, Binbin Lin, Haifeng Liu, Deng Cai: TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without Training. AAAI 2024.
Yuqi lin, Minghao Chen*, Wenxiao Wang, Boxi Wu, Ke Li, Binbin Lin, Haifeng Liu, Xiaofei He: CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation. CVPR 2023. Zhanwei Zhang, Minghao Chen, Shuai Xiao, Liang Peng, Hengjia Li, Binbin Lin, Ping Li, Wenxiao Wang, Boxi Wu, Deng Cai: Pseudo Label Refinery for Unsupervised Domain Adaptation on Cross-dataset 3D Object Detection. CVPR 2024. Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li: CRFL: Certifiably Robust Federated Learning against Backdoor Attacks. ICML 2021. Hao Feng, Minghao Chen, Jinming Hu, Dong Shen, Haifeng Liu, Deng Cai: Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person Re-identification. IEEE TIP 2021. Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu: Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework. ICML 2021. Zhanwei Zhang, Zishuo Hua, Minghao Chen, Wei Lu, Binbin Lin, Deng Cai, Wenxiao Wang: G2LTraj: A Global-to-Local Generation Approach for Trajectory Prediction. IJCAI 2024. Honghui Yang, Wenxiao Wang, Minghao Chen, Binbin Lin, Tong He, Hua Chen, Xiaofei He, Wanli Ouyang: PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer. CVPR 2023. Haozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen: KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation. ICML 2021. Hao-Zhe Feng, Kezhi Kong, Minghao Chen, Tianye Zhang, Minfeng Zhu, Wei Chen: SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations. AAAI 2021. Hao Fang, Daoxin Zhang, Yi Zhang, Minghao Chen, Jiawei Li, Yao Hu, Deng Cai, Xiaofei He: Salient Object Ranking With Position-Preserved Attention. CVPR 2021.
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