Xiang Ao, Associate Professor

Dr. Xiang Ao is an Associate Professor in the Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences(ICT, CAS). Before joining ICT, he received Ph.D. degree in Computer Science from the Institute of Computing Technology, CAS in 2015 and B.S. degree in Computer Science from Zhejiang University in 2010.

His research interests include algorithms and models for AI finance tasks, e.g. behavior modeling and NLP for financial applications. He has authored more than 90 referred publications at prestigious international conferences and journals like The Innovation, IEEE TKDE, KDD, WWW, SIGIR, ACL, ICLR, AAAI, IJCAI, etc., and has served as SPC or PC members over top tier international conferences such as KDD, WWW, IJCAI, AAAI, ACL, NeurIPS, ICML, etc. He is supported by the National Key Research and Development Program of China, National Natural Science Foundation of China, CCF-Tencent Rhino-Bird Young Faculty Open Research Fund, Tencent Advertising Rhino-Bird Research Fund, Ant Financial Science Funds, Alibaba Innovative Research Project, Youth Innovation Promotion Association CAS and Beijing Nova Program, etc.

I'm always looking for talented and self-motivated interns with a strong interest/background in machine learning, data mining,  and/or mathematics. 

New: Positions for recruiting Ph.D. and Master students in Fall 2025 will be open, and there might be 1 Ph.D. and 2 master capacities. Meanwhile, welcome the undergraduates who are interested in the position in the School of Future Technology of UCAS to contact me. Send your CV to me :-).

Recent News
  1. [2024.5]: One paper "EFSA: Towards Event-Level Financial Sentiment Analysis" is accepted by ACL2024. Congrats to Tianyu and Yiming!
  2. [2024.2]: Two papers "DRAMA: Dynamic Multi-Granularity Graph Estimate Retrieval over Tabular and Textual Question Answering" and "Distillation with Explanations from Large Language Models" are accepted by LREC-COLING2024. Congrats to Ruize and Hanyu!
  3. [2024.1]: One paper "Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspectiv" is accepted by ICLR2024. Congrats to Kuan!
  4. [2023.12]: One paper "F2GNN: An Adaptive Filter with Feature Segmentation for Graph-based Fraud Detection" is accepted by ICASSP2024. Congrats to Guanghui!
  5. [2023.12]: One paper "Online Conversion Rate Prediction via Multi-Interval Screening and Synthesizing under Delayed Feedback" is accepted by AAAI2024. Congrats to Qiming!



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