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Jonathan Yumeng Li

Li, Jonathan Yumeng
Associate Professor
B.Sc. (National Sun Yat-Sen University), M.A.Sc. (McMaster), Ph.D. (Toronto)
Location
DMS 7105
Telephone
613-562-5800 x 4668
Email
This email address is being protected from spambots. You need JavaScript enabled to view it.
Website
jonli.net/

Biography

Jonathan Li holds a Ph.D. from the Mechanical and Industrial Engineering Department at the University of Toronto. He received his B.Sc degree in Physics from National Sun Yat-Sen University in 2003, and his M.A.Sc. degree in Computational Engineering and Science from McMaster University in 2008.

Research interests

Professor Li's research interests focus on business analytics, operations research, and financial engineering. At the centre of his work are risk management problems that involve quantifying and modelling risk. Robust solutions to these problems contribute to more reliable decisions, ones less prone to uncertainty from market behaviour, stock prices, supply and demand characteristics, and other hard-to-predict phenomena. To this end, professor Li seeks to better understand and control uncertainty, using tools such as optimization algorithms and statistical learning. He has a particular interest in the area of financial engineering and his current projects tackle portfolio management, derivative pricing, and risk hedging. He is also involved in supply chain management projects.

Publications during the last 7 years

Papers in Refereed Journals

  • Li, J.Y. 2021. Inverse optimization of convex risk functions. Management Science.
  • Marzban, S., Delage, E. and Li, J.Y. 2020. Equal risk pricing and hedging of financial derivatives with convex risk measures. Quantitative Finance.
  • Li, J.Y. 2018. Closed-form solutions for worst-case law invariant risk measures with application to robust portfolio optimization. Operations Research, 66(6): 1457-1759.
  • Delage, E. and Li, J.Y. 2018. Minimizing risk exposure when the choice of a risk measure is ambiguous. Management Science, 64(1): 327-344.
  • Kwon, R.H. and Li, J.Y. 2016. A stochastic semidefinite programming approach for bounds on option pricing under regime switching. Annals of Operations Research, 237(1-2): 41-75.

Funded Research during the last 7 years

Funded Research during the last 7 years
From-To Source Title * ** Role Amount
2020-2022 NSERC Extension of Modeling and Optimization of Risk Measures R C PI $ 47,520
2020-2021 Mitacs (Brane Capital) A Deep Risk-Sensitive Reinforcement Learning Framework for Portfolio Management R O Co-PI $ 15,000
2019-2020 Mitacs (EVOVEST) Portfolio Management by Reinforcement Learning R O Co-PI $ 30,000
2015 IBM CBAP Developing robust measures for quantitative risk management R I PI $ 5,000
2014-2019 NSERC Modeling and Optimization of Risk Measures R C PI $ 110,000
2014-2015 Telfer School of Management Research Fund (SMRF) Optimizing surgical scheduling using robust optimization R I Co-PI $ 6,000
2014-2015 Telfer School of Management Research Fund (SMRF) Modeling and Optimization of Risk Measures R I PI $ 6,000
2014-2015 RDP Modeling and Optimization of Risk Measures R I PI $ 6,000

LEGEND:

*Purpose
C: Contract (R and D) | E: Equipment Grant | R: Research Grant | S: Support Award | P: Pedagogical Grant | O: Other, U: Unknown

**Type
C: Granting Councils | G: Government | F: Foundations | I: UO Internal Funding | O: Other | U: Unknown

Role
PI = Principal Investigator | Co-I = Co-Investigator | Co-PI = Co-Principal Investigator

Areas of Strategic Impact
Health Systems Innovation and Management

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