李渝 - 哈尔滨工业大学（深圳） - 计算机科学与技术学院

个人简介

李渝，助理教授。于2022年博士毕业于香港中文大学计算机科学与工程系，2017年研究生毕业于比利时鲁汶大学，2016年取得鲁汶大学及电子科技大学（A+学科，电子信息工程）双学士学位，获得鲁汶大学及电子科技大学优秀毕业生称号。主要从事国际热点科学问题机器学习安全与测试的研究并取得一系列原创性成果。截至目前，已发表相关学术论文10余篇，发表在安全领域旗舰会议CCS，NDSS，机器学习旗舰会议NeurIPS，软件工程旗舰会议ISSTA，和测试领域旗舰会议ETS等。同时获得了安全、机器学习、以及软件工程领域的认可。被提名为2022年度香港中文大学青年学者博士论文奖候选人，获得了2022年亚洲测试会议（Asian Test Symposium）最佳博士论文奖以及IEEE测试技术委员会（TTTC）E. J. McCluskey博士论文奖亚洲区决赛第一名。该奖项是为了纪念在测试技术领域作出杰出贡献的E. J. McCluskey而设立，是该领域评价博士论文影响力的最高国际奖项之一。

研究领域

人工智能，网络安全,自动测试技术

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

ISSTA’22 HybridRepair: Towards Annotation-Efficient Repair for Deep Learning Models Yu Li, Muxi Chen, and Xu, Qiang ISSTA 2022 VTS’21 On Workload-Aware DRAM Failure Prediction in Large-Scale Data Centers Wang, Xingyi, Li, Yu, Chen, Yiquan, Wang, Shiwen, Du, Yin, He, Cheng, Zhang, YuZhong, Chen, Pinan, Li, Xin, Song, Wenjun, and others, In 2021 IEEE 39th VLSI Test Symposium (VTS) 2021 DAC’21 AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference Li, Min, Li, Yu, Tian, Ye, Jiang, Li, and Xu, Qiang The Design Automation Conference (DAC) 2021 IJCAI’21 Information Bottleneck Approach to Spatial Attention Learning Lai, Qiuxia, Li, Yu, Zeng, Ailing, Liu, Minhao, Sun, Hanqiu, and Xu, Qiang International Joint Conference on Artificial Intelligence (IJCAI) 2021 NeurIPS’21 TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks Li, Yu, LI, Min, Lai, Qiuxia, Liu, Yannan, and Xu, Qiang In Advances in Neural Information Processing Systems 2021 CCS’20 DeepDyve: Dynamic Verification for Deep Neural Networks Li, Yu*, Li, Min*, Luo, Bo, Tian, Ye, and Xu, Qiang In Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security (CCS) 2020 GLSVLSI’20 On Configurable Defense against Adversarial Example Attacks Luo, Bo, Li, Min, Li, Yu, and Xu, Qiang In Proceedings of the 2020 on Great Lakes Symposium on VLSI (GLSVLSI) 2020 ACSAC’19 D2NN: A Fine-Grained Dual Modular Redundancy Framework for Deep Neural Networks Li, Yu, Liu, Yannan, Li, Min, Tian, Ye, Luo, Bo, and Xu, Qiang In Proceedings of the 35th Annual Computer Security Applications Conference (ACSAC) 2019 DATE’19 On Functional Test Generation for Deep Neural Network IPs Luo, Bo, Li, Yu, Wei, Lingxiao, and Xu, Qiang In 2019 Design, Automation Test in Europe Conference Exhibition (DATE) 2019 ACSAC’18 I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators Wei, Lingxiao, Luo, Bo, Li, Yu, Liu, Yannan, and Xu, Qiang In Proceedings of the 34th Annual Computer Security Applications Conference (ACSAC) 2018 ETS’18 IEEE Std P1838’s flexible parallel port and its specification with Google’s protocol buffers Li, Yu, Shao, Ming, Jiao, Hailong, Cron, Adam, Bhatia, Sandeep, and Marinissen, Erik Jan In 2018 IEEE 23rd European Test Symposium (ETS) 2018