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陳薇，中國科學院計算技術研究所研究員、博士生導師，現任智能算法安全全國重點實驗室副主任，曾任微軟亞洲研究院計算學習理論組負責人。長期從事機器學習基本理論與方法方向的研究，擔任中科院戰略性先導科技專項項目負責人，在深度學習機理、分布式優化、安全可信應用等方面取得科研成果，在本領域國際重要學術會議與期刊發表學術論文70余篇（如ICML、NeurIPS、ICLR等），入選2021年度福布斯中國科技女性榜、2023年度麻省理工科技評論智能計算創新人物、2024年度中國科學院大學小米青年學者。擔任本領域主要學術會議ICML、NeurIPS、AAAI的程序委員會高級領域主席、領域主席等。

2022年2月 — 今：中國科學院計算技術研究所，研究員

2011年7月 — 2022年2月： 微軟亞洲研究院，Associate Researcher，Researcher，Lead Researcher，Principal Research Manager?

2006年9月 — 2011年7月：中國科學院數學與系統科學研究院，博士

2002年9月 — 2006年7月：山東大學，數學與系統科學學院，學士

學術專著：

? 劉鐵巖，陳薇，王太峰，高飛，《分布式機器學習：算法、理論與實踐》，機械工業出版社，北京，2018(ISBN 978-7-111-60918-6)

期刊/會議文章：

[1] Wenjie Zhou, Bohan Wang, Wei Chen, Xueqi Cheng, BSFA: Leveraging the Subspace Dichotomy to Accelerate Neural Network Training. 2025 Conference on Empirical Methods in Natural Language Processing. (EMNLP), 2025.

[2] Junjie Nan, Jianing Li, Wei Chen, Mingkun Zhang, Xueqi Cheng, NAPPure: Adaversarial Purification for Robust Image Classification under Non-Additive Perturbations. IEEE/CVF International Conference on Computer Vision (ICCV), 2025.

[3] Yuchen Wen, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng, Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective. Findings of the Association for Computational Linguistics (ACL), 2025. (Project Webpage)

[4] Mingkun Zhang, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng, CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification.The 13rd International Conference on Learning Representations(ICLR), 2025.

[5] Mingkun Zhang, Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo, Xueqi Cheng, CausalDiff: Causality-Inspired Disentanglement via Difussion Model for Adversarial Defense. The 38th Annual Conference on Neural Information Processing systems(NeurIPS), 2024.

[6] Mingkun Zhang, Jianing Li, Wei Chen, Jiafeng Guo, Xueqi Cheng, Classifier Guidance Enhances Diffusion-based Purification by Preserviong Predictive Information. The 27th European Conference on Artifitial Intelligence(ECAI), 2024.

[7] Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen, Randomly-reshuffled Adam can provably converge under non-uniform smoothness. The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024.

[8] Wenjie Zhou, Bohan Wang, Wei Chen, Zhi-Ming Ma, Xueqi Cheng, Momentum Gradient Descent over single-neuron linear network: rich behaviors of limiting Sharpness. Bridging the Gap Between Practice and Theory in Deep Learning (BGPT) ICLR workshop, 2024.

[9] Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen, Xueqi Cheng, Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off. The 38th International Association for the Advancement of Artificial Intelligence Conference (AAAI), 2024.

[10] Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen. Closing the Gap between the Upper Bound and Lower Bound of Adam’s Iteration Complexity. Advances in Neural Information Processing Systems 37 (NeurIPS), 2023

[11] Lu Chen, Ruqing Zhang, Wei Huang, Wei Chen, Jiafeng Guo, Xueqi Cheng, Inducing Causal Structure for Abstractive Text Summarization. The 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023.