Dr. WU Qi (吳琦 博士)
Ph.D (Columbia University), M.S (Peking University), B.Eng (Wuhan University)
Associate Professor (Tenured), Research Degree Coordinator, School of Data Science
PI, CityU-JD Digits Laboratory in Financial Technology and Engineering
Program Leader & PI of Program I - AI-Driven Financial Service, Laboratory for AI-Powered Financial Technologies Limited (HKAIFT)
Executive Committee, Hong Kong Institute of Data Science
- Quantitative Finance
- Financial Technology
- Business Analytics
- Applied Probability
- 2013 - 2018, The Chinese University of Hong Kong, Department of System Engineering and Engineering Management, Assistant Professor, Hong Kong. -- Research areas: Financial Engineering, Applied Probability, Operations Research.
- 2012 - 2013, The Depository Trust & Clearing Corp., Division of Financial Engineering, Senior Quantitative Analyst, New York. -- Team Lead of Interest Rate Analytics and Stress Testing Methodology.
-- Developing Quant Analytics for USD Cash and Derivative Securities.
- 2010 - 2012, UBS Investment Bank, Fixed Income Division, USD Non-Linear Rates and Structured Rates Desk, Associate Director, Stamford CT. -- Pricing and Risk Managing of Interest Rate Exotic Products.
-- Developing Asia (ex-Japan) USD Structure Notes Trading Business.
- 2008, Lehman Brothers, Fixed Income Division, Quantitative Credit Research Group, Quantitative Associate, London. -- Developing Production Pricing Models for Single-name Credit Derivatives.
-- Prototyping Portfolio-level Hedging of FX Exposure in the Credit Derivative Book.
- HKRGC - GRF, “Generative Models of Multivariate Dependence for Asset Retu, Amount: HKD $952,494, 2021 - 2023, Qi WU (sole-PI).
- AIR@InnoHK, ITC, Laboratory for AI-Powered Financial Technologies LTD(HKAIFT), Amount: HKD $272,000,000, 2020 - Now, Qi WU (PI of Program I - AI-Driven Financial Service).
- HKRGC - GRF, "Risk-Potential Framework for Dynamic Portfolio Selection", Amount: HKD $869,898, 2020 - 2022, Qi WU (PI), Xiao QIAO (Co-I).
- CityU New Research Initiatives/Infrastructure Grant, “Interpretable Machine Learning Methods for Financial Risk M, Amount: HKD $1,066,560, 2019 - 2021, Qi WU (sole-PI).
- JD Finance Strategic Collaboration & Contract Research, “Fundamental Research of Financial Technology and its Strate, Amount: HKD $10,182,590, 2019 - 2023, Qi WU (sole-PI).
- HKRGC - GRF, "Studies on Margin Procyclicality - the Impact of Volatility, Amount: HKD $582,000, 2018 - 2020, Qi WU (sole-PI).
- HKRGC - GRF, "Asymptotic Analysis of Portfolio Tail Risk and the Diversif, Amount: HKD $482,605, 2017 - 2019, Qi WU (sole-PI), Heng SUN (Co-I), Bank of New York Mellon.
- HKRGC - Early Career Scheme, "Low-dimensional Modeling of Collateralized Term Structure w, Amount: HKD $656,737, 2015 - 2018, Qi WU (sole-PI).
- CUHK Faculty of Engineering Direct Research & Startup Grant, “Interest Rate Derivative Modeling in the Post-Crisis Era”, Amount: HKD $300,000, 2013 - 2015, Qi WU (sole-PI).
- Jan 2019 - Now, Member of Expert Review Panel, Hong Kong R&D Centre for Logistics and Supply Chain Management Enabling Technologies (LSCM).Hong Kong.
Service in CityU
- Sep 2022 - Now, SDSc School Graduate Studies Committee, Chairman.
- Sep 2022 - Now, Univerisity Committee - Board of Graduate Studies (BGS), the ex officio member.
- Jul 2022 - Now, SDSc Research Degree Coordinator, ..
- 1 Jul 2019 - Now, SGS Academic Conduct Committee, Member.
- Sep 2018 - Now, Hong Kong Institute of Data Science, Member of Executive Committee.
- ( * refers to a supervised student co-author or postdoc co-author; † denotes the corresponding author.)
- "Deep into The Domain Shift: Transfer Learning through Dependence Regularization". S. M. Ma*, Z. R. Yuan*, Q. Wu†, Y. Y. Huang*, X. X. Hu*, C. H. Leung*, D. D. Wang and Z. X. Huang. IEEE Transactions on Neural Networks and Learning Systems. (Minor Revision). [pdf]
- “Towards Balanced Representation Learning for Credit Policy Evaluation”. Y. Y. Huang*, C. H. Leung*, S. M. Ma*, Z. R. Yuan*, Qi Wu†, S. Y. Wang*, D. D. Wang and Z. X. Huang. AISTATS 2023. (Forthcoming) [link]
- “A Unified Perspective on Regularization and Perturbation in Differentiable Subset Selection”. X. Q. Sun*, C. H. Leung*, Y. J. Li*, and Qi Wu†. AISTATS 2023. (Forthcoming) [link]
- “A Unified Domain Adaptation Framework with Distinctive Divergence Analysis”. Z. R. Yuan*, X. X. Hu*, Qi Wu†, S. M. Ma*, C. H. Leung*, Xin Shen and Y. Y. Huang*. (Forthcoming). Transactions on Machine Learning Research. [link]
- “Counter-cyclical Margins for Option Portfolios”. Y. Y. Chen, D. Li and Qi Wu†. Journal of Economic Dynamics and Control. (Forthcoming) [pdf]
- "Neural Learning of Online Consumer Credit Risk". D. WANG, Q. WU† and W. ZHANG. Management Science. (R&R). [pdf, link]
- “Robust Causal Learning for the Estimation of Average Treatment Effects”. Y. Y. Huang*, C. H. Leung*, X. Yan*, Q. Wu†, S. M. Ma*, Z. R. Yuan*, D. D. Wang and Z. X. Huang. IJCNN 2022. (Oral) [pdf, link]
- “Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information”. Y. Y. Huang*, C. H. Leung*, S. M. Ma*, Q. Wu†, D. D. Wang and Z. X. Huang. PRICAI 2022. [pdf, link]
- “The Causal Learning of Retail Delinquency”. Y. Y. Huang*, C. H. Leung*, X. Yan*, Q. Wu†, N.B. Peng, D.D. Wang and Z.X. Huang. AAAI 2021. [pdf, link]
- “Memory-Gated Recurrent Networks”. Y. Q. Zhuang*, Q. Wu†, N. B. Peng, M. Dai and J. Zhang* and H. Wang. AAAI 2021. [pdf, link]
- “Risk and Return Prediction for Pricing Portfolios of Non-performing Consumer Credit”. S. Y. Wang*, X. Yan*, B. Q. Zheng, H. Wang, W. L. Xu, N. B. Peng and Qi Wu†. ICAIF 2021. [pdf, link]
- “Understanding Distributional Ambiguity via Non-Robust Chance Constraint”. S. M. Ma*, C. H. Leung*, Q. Wu†, W. Liu, and N. B. Peng. ICAIF 2020. [pdf, link]
- "Capturing Deep Tail Risk via Sequential Learning of Quantile Dynamics" X. Yan* and Q. Wu†. Journal of Economic Dynamics and Control. 109 (2019) [pdf, link]
- “Cross-sectional Learning of Extremal Dependence among Financial Assets”. X. Yan*, Q. Wu† and W. Zhang. NeurIPS 2019. [pdf, link]
- "Persistence and Procyclicality in Margin Requirements" (2018) P. Glasserman and Q. WU. Management Science. Vol.64, No.12. 5705 - 5724. [pdf, link]
- “Parsimonious Quantile Regression of Asymmetrically Heavy-tailed Financial Return Series” X. Yan*, W. Z. Zhang, L. Ma, W. Liu and Q. Wu†. NeurIPS 2018. [pdf, link]
- “Procyclicality in Sensitivity-Based Margin Requirements”. (2018) P. Glasserman and Q. WU. Chapter 15 in "Margin in Derivatives Trading". Risk Books. 293 - 309. [pdf, link]
- "Series Expansion of the SABR Joint Density" (2012) Q. WU. Mathematical Finance. Vol.22, No.2. 310 - 345. [pdf, link]
- "Forward and Future Implied Volatility" (2011). P. Glasserman and Q. WU. International Journal of Theoretical and Applied Finance. Vol.14, No.03. 407 - 432. [pdf, link]
- "Symplectic Parareal". G. Bal and Q. WU. Domain Decomposition Methods in Science and Engineering XVII (2008) [pdf, link]
- "Robust Causal Machine Learning of Treatment Effects". Y. Y. Huang*, C. H. Leung*, Q. Wu and X. Yan†. (Submitted)
- “Memory Learning of Multivariate Asynchronous Time Series”. Y. J. Li*, C. H. Leung*, C. Q. Wang*, Y. Y. Huang* and Q. Wu†, D. D. Wang and Z. X. Huang. (Submitted).
- “Risk Neural Distribution Extraction and Option Pricing with Generative Machine Learning”. Z. H. Xian*, N. Yang, X. Yan* and Qi Wu. (Submitted).
- "Efficient Subsidies via Supply Re-usability" (2019) S. M. MA and Q. WU. (Working paper). [pdf]
- "Asymptotics of Portfolio Tail Risk Metrics for Elliptically Distributed Asset Returns" (2016) A. Lesniewski, H. SUN, and Q. WU. (Working paper). [pdf, link]
- "A Dual-curve Short Rate Model with Multi-factor Stochastic Volatility: I. Asymptotic Analysis" (2015) A. Lesniewski, H. SUN, and Q. WU. (Working paper). [pdf, link]
Last update date :
09 Feb 2023