A iuvenis team, professio technology in omni doctrinae genere et GPU gluteus maximus, AI fecerit summo usque ad partum, et algorithms solutions ad corporates, Labs, et Communitates scholarum.
- Miao Yin, Master, University of Electronic Science and Technology of China, 2016~2018. PhD student in Electrical and Computer Engineering of Rutgers University, 2019.09~present
Hongyang Yang, Research Scientist at AI4Finance, 03/01/2020~ 01/31/2021.
- Zhaoran Wang, Assistant professor, Northwestern University.
- Qibin Zhao, Unit Leader, Tensor Learning Unit, Riken Lab, Janpan.
- Christina Dan Wang, Assistant Professor of Finance, NYU Shanghai; Global Network Assistant Professor, NYU.
- Tao Zhang, Assistant Professor, Shanghai University.
- Cai Fu, Professor of Computer School, Huazhong University and Science and Technology.
Current Student Team Members
- Zihan Ding, Master, Artificial Intelligence, Imperial College London, 2018.9~2019.7; PhD in Princeton University.
- Yigong Hu, Master, Electrical Engineering, Columbia University, 2019.09~2020.04. PhD at UIUC, 2020.09.
- Jiawei Ma, Master, Electrical Engineering, Columbia University, 2019.1~2019.08. Now, PhD at Columbia University.
Yimeng Zhang, Master, Electrical Engineering, Columbia University, 2019.07~2020.12. Now, PhD at Michigan State University.
- Iris Yang, Bachelor, Computer Science, Columbia University, 2019.6~
[EdgeBlock] Liuqing Yang, X.-Y. Liu, W. Gong, Secure smart home systems: A blockchain perspective. IEEE INFOCOM Workshop on International Symposium on Edge Computing Security and Blockchain (EdgeBlock), 2020.
[URTC] Liuqing Yang, X.-Y. Liu. Tensor nuclear-norm minimization for snapshot compressive imaging cameras. MIT Undergraduate Research Technology Conference, 2019. [PDF]
[SmartBlock] Liuqing Yang, X.-Y. Liu, X. Li, Y. Li. Price prediction of cryptocurrency: empirical analysis. SmartBlock 2019.
[NeurIPS Workshop] X. Li, Y. Li, H. Yang, Liuqing Yang, X.-Y. Liu. DP-LSTM: A differential privacy framework for stock prediction based on financial news. Robust AI in FS 2019 NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, 2019.
Xiaocheng Han, Bachelor, Computer Science, Shanghai Jiao Tong University, summer intern, 2019.07~2019.12. Now at Carnegie Mellon University.
- Paul Zhuoran Xiong, Master, Electrical Engineering, Columbia University, 2018.09~2019.02. Ph.D student, McGill University, 2019.09~
Runjia Luna Zhang, Bachelor, Electrical Engineering, Columbia University, 2018.9~2019.08. Riken Lab, 2019.09~
- Chen Shang, Bachelor, Mathematic, University of Michigan–Ann Arbor, 2017.6~2018.8.
- Xinyi Li, Master, Department of Statistics, Columbia University, 2018.9~2019.06. Feizai Co. Ltd., 2019.07~
[NeurIPS Workshop] X. Li, Y. Li, H. Yang, L. Yang, X.-Y. Liu. DP-LSTM: A differential privacy framework for stock prediction based on financial news. Robust AI in FS 2019 : NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, 2019.
[ICML Workshop] X. Li, Y. Li, Y. Zhan, X.-Y. Liu. Optimistic Bull or Pessimistic Bear: adaptive deep reinforcement learning for stock portfolio allocation. ICML Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning, 2019.
[KDD Workshop] X. Li, Y. Li, X.-Y. Liu, D. Wang, Risk management via anomaly circumvent: mnemonic deep learning for midterm stock prediction. KDD Workshop on Anomaly Detection in Finance, 2019.
Ming Zhu, Post Doc, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences.
Yinchuan Li, Visiting Scholar, PhD at Beijing Institute of Technology.
Rui She, Visiting Scholar, PhD at Tsinghua University, 2019.01~2019.07.
- Tianyu Geng, Visiting Scholar, PhD at Nankai University, 2018.09~2019.09.
Wenhang Bao, Master, Department of Statistics, Columbia University, 2016.09~2017.12. Now, Senior Consultant/Data Scientist at Capgemini.
[NeurIPS Workshop] W. Bao, X.-Y. Liu. Spatial influence-aware reinforcement learning for intelligent transportation system. NeurIPS Workshop on Machine Learning for Autonomous Driving, 2019.
[ICML Workshop] W. Bao, X.-Y. Liu, Multi-agent reinforcement learning for liquidation strategy analysis. ICML Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning, 2019.
- Yunzhe Fang, Master, Industrial Engineering and Operations Research, Columbia University, 2016.09~2018.06. Research Analyst, Active Equity at BlackRock, now.
[BigData] Yunzhe Fang, X.-Y. Liu, Hongyang Yang. Practical machine learning approach to capture the scholar data driven alpha in AI industry. IEEE Big Data 2019, 5th Special Session on Intelligent Data Mining.
Qingwei Wu, Master, Electrical Engineering, Columbia University, 2017.09~2018.05. Microsoft at Suzhou, China.
[NeurIPS Workshop] W. Lu, X.-Y. Liu, Qingwei Wu, Y. Sun, A. Walid. Transform-based multilinear dynamical system for tensor time series analysis. NeurIPS Workshop on Modeling and Decision-Making in the Spatiotemporal Domain, 2018.
H. Yang, X.-Y. Liu, Qingwei Wu. A practical machine learning approach for dynamic stock recommendation. IEEE TrustCom, 2018.
Chenxiao Zhu, Master, Hong Kong University of Science and Technology, 2017.09~2018.05.
Chenxiao Zhu, L. Xu, X.-Y. Liu, F. Qian. Tensor-generative adversarial network with two-dimensional sparse coding: application to real-time indoor localization. IEEE International Conference on Communications (ICC), 2018.