Dong, Wendy Wanxue(董婉雪)

Biography

Professor Dong is an Assistant Professor in the Department of Decisions, Operations and Technology at the CUHK Business School. She hold a PhD in Information Systems from the McCombs School of Business, the University of Texas at Austin. Her research aims to develop machine learning and artificial intelligence algorithms to solve business problems. Her recent projects develop novel ML and AI methods to evaluate workers’ decision accuracy and societal bias in many key domains including health care, fraud detection, fact checking, finance, and online labor markets. She earned a dual B.S. degree in Computer Science and Statistics from Purdue University, IN.

Teaching Areas

Business Information Systems

Research Interests

Machine Learning
Predictive Modeling
Experts/Labelers’ Decision Quality Assessment
Human AI Collaboration
Fair and Responsible AI

  • Grants
    • Provost Research Grant awarded by The University of Texas at Austin, 2021-2022
  • Awards & Honours
    • Graduate School Summer, The University of Texas at Austin, 2022
    • College Continuing Fellowship, The University of Texas at Austin, 2021
    • McCombs Dean’s Fellowship, The University of Texas at Austin, 2017-2021
  • Academic/Professional Services
    • Reviewer, Management Information Systems Quarterly (MISQ), 2023
    • Reviewer, International Conference on Information Systems (ICIS), 2023

Chen, Zhi(陳植)

Biography

Prof. Zhi Chen is an Assistant Professor in the Department of Decisions, Operations and Technology, CUHK Business School, The Chinese University of Hong Kong. He obtained his PhD from NUS Business School, National University of Singapore and his BE from Tsinghua University, China.

His primary research involves developing models and designing algorithms for analytics under uncertainty with different levels of data availability as well as applications in business, economics, finance, and operations. He is also interested in how to compete or cooperate in joint activities such as resource allocation and risk management. His works appear in journals such as INFORMS Journal on Computing, Management Science, Operations Research, Production and Operations Management, Mathematical Finance, Transportation Science, and TRB.

Teaching Areas

Business Analytics
Data Mining & Machine Learning
Operations & Supply Chain Management
Risk Management

Research Interests

Analytics under Uncertainty
Data-Driven Analytics
Risk Management
Robust Optimisation

  • Grants
    • “A Distribution-Free Model of Time Series”, General Research Fund awarded by Hong Kong Research Grants Council with HK$414,059, 2024-2025 (Principal Investigator)
    • CUHK “Improvement on Competitiveness in Hiring New Faculties” Funding Scheme awarded by The Chinese University of Hong Kong with HK$1,500,000 (Principal Investigator)
    • “Robust Mechanism Design with Limited Information”, General Research Fund awarded by Hong Kong Research Grants Council with HK$925,120, 2023-2025 (Principal Investigator)
    • “Financial Systemic Risk Measures based on Monte Carlo Simulation: Theory and Methods”, NSFC/RGC Joint Research Scheme awarded by National Natural Science Foundation of China & Hong Kong Research Grants Council, 2022-2025 (Co-Investigator)
    • “A Python Algebraic Modeling Package for Robust Optimization”, Strategic Research Grant awarded by City University of Hong Kong with HK$100,000, 2021-2023 (Principal Investigator)
    • “The Hurwicz Criterion for Data-Driven Decision-Making under Uncertainty”, Early Career Scheme awarded by Hong Kong Research Grants Council, HK$628,950, 2020-2023 (Principal Investigator)
    • “Risk Sharing under Distributional Ambiguity: Stability, Inequality, and Monotonicity”, Start-Up Grant awarded by City University of Hong Kong, with HK$300,000, 2019-2022 (Principal Investigator)
  • Awards & Honours
    • College Research Excellence Award, College of Business, City University of Hong Kong, 2022
    • Finalist, George E. Nicholson Student Paper Competition, INFORMS, 2017
  • Academic/Professional Services
    • Reviewer for INFORMS Journal on ComputingManagement Science, Manufacturing & Service Operations Management, Operations Research, Production and Operations Management, Mathematics of Operations Research, Mathematical Programmin, Naval Research Logistics, Operations Research Letters, SIAM Journal on Optimization, TRB, TRE, Transportation Science, ICLR, ICML, and NeurIPS.

Li, Anran(李安然)

Biography

Prof. Anran Li is an associate professor at the Department of Decisions, Operations and Technology at The Chinese University of Hong Kong (CUHK) Business School. Prior to joining CUHK, she was a faculty member at the Department of Management, London School of Economics and Political Science (LSE). Prof. Li received her PhD in Operations Research from Columbia University in 2017.

Prof. Li is broadly interested in designing algorithms and analysing data in order to optimise supply chain decisions. More precisely, Prof. Li focuses on developing and estimating consumer choice models using econometric tools, optimising assortment and recommendation for both traditional retailing and online digital platform, and creating a fair marketplace for all shareholders. Prof. Li’s research has been published in leading journals such as Operations Research and Management Science. Prof. Li is passionate about bringing impacts to practice through the work. She is an active external researcher and scientist for a number of companies, including Hewlett Packard, SAS Institute, Sabre Airline Solutions and Jet.com.

Prof. Li has served as reviewer for premier journals such as Operations Research and Management Science, Manufacturing & Service Operations Management and Production and Operations Management. Prof. Li is the co-organiser of the 2023 INFORMS Revenue Management and Pricing (RM&P) Section Conference.

Teaching Areas

Supply chain management
Operations management
Revenue management and dynamic pricing

Research Interests

Operations Management
Supply Chain Management
Business Analytics
Revenue Management
E-commerce Applications
Choice Modeling and Assortment Optimization
Approximation Algorithms
Dynamic Programming and Online Algorithm

  • Grants
    • Hong Kong Research Grants Council, General Research Fund 14506423, PI, HK$462,238, Jan 2024- May 2026
    • “Revenue Maximization and Learning in Products Ranking”, RIIF Fund awarded by LSE Department of Management with £4,000, 2021-2022
    • “Product Line Design and Pricing under the Basic Attraction Model”, RIIF Fund awarded by LSE Department of Management with £10,000, 2020-2021

Karhade, Prasanna

Biography

Prof. Prasanna Karhade joined the CUHK Business School as an Associate Professor in the Department of Decisions, Operations and Technology in August 2022.

Prof. Karhade is interested in digital innovation, design thinking and entrepreneurship. His research has been published in MIS Quarterly, Information Systems Research, and Journal of Management Information Systems.

He has currently started an ambitious research programme on micro-financing in GREAT (growing, rural, eastern, aspirational, and transitional) economies. Prof. Karhade loves hiking, poetry & meditation. Prasanna means happiness and so there is no incorrect way to pronounce Prasanna — as long as you do it with a smile.

Teaching Areas

Digital Innovation
Entrepreneurship
FinTech

Research Interests

Digital Innovation & Entrepreneurship
Digital Platforms & Decolonization
Governance & Control of IT in Family Business

  • Publications and Working Papers

    Digital Innovation & Entrepreneurship

    • Karhade, P. and Dong, J.Q. (2021), “IT Investment & Commercialized Innovation Performance: Dynamic Adjustment Costs and Curvilinear Effects,” MIS Quarterly, 45(3), 1007-1024.
    • Karhade, P. and Dong, J.Q. (2021), “Innovation outcomes of the digitally enabled collaborative problemistic search capability,” MIS Quarterly, 45(2), 693-718.
    • Dong, J.Q., Karhade, P., Rai, A., and Xu, S.X. (2021), “How Firms Make Information Technology Investment Decisions: Toward a Behavioral Agency Theory,” Journal of Management Information Systems, 38(1), 29-58. [Authors listed alphabetically.]

    Digital Platforms & Decolonization

    • Kathuria, A., Karhade, P., and Konsynski, B.R. (2020), “In the realm of hungry ghosts: Multi-level theory for restaurant participation in food delivery platforms,” Journal of Management Information Systems ,37(2), 396-430. [Kathuria A. and Karhade P. are both co-first authors.]
    • Karhade, P. and Kathuria, A. (2020), “Missing Impact of Ratings on Platform Participation in India: A Call for Research in GREAT Domains,” Communications of the Association for Information Systems, 47(Article 19), 364-381. [Both authors are co-first authors.]

    Governance & Control

    • Karhade, P., Shaw, M.J., and Subramanyam, R. (2015), “Patterns in Information Systems Portfolio Prioritization: Evidence from Decision Tree Induction”, MIS Quarterly, 39(2), 413-433.
    • Susarla, A., Subramanyam, R., and Karhade, P. (2011), “Contractual Provisions to Mitigate Holdup: Evidence from Information Technology Outsourcing,” Information Systems Research, 21(1), 37-55.
    • Kathuria, A., Karhade, P., Ning, X., and Konsynski, B. “Blood and Water: IT Investment and Control in Family-Owned Businesses,” Journal of Management Information Systems, Accepted.
  • Grants
    • “Search for Innovation: Integrating the Behavioural Theory of the Firm with Agency-Theoretic Explanations”, awarded by, Research Grants Council (RGC)of Hong Kong with HK$717,470, 2018-2021
    • “IT Assets and Firm Innovation Output: An Empirical Examination”, awarded by Research Grants Council (RGC) of Hong Kong with HK$ 215,670, 2012-2014
  • Award & Honours
    • Excellence in Teaching Award Nomination, University of Hawaii, 2020
    • Dean’s Recognition of Excellent Teaching Performance, Hong Kong University of Science and Technology, 2013-14
    • Dean’s Recognition of Excellent Teaching Performance, Hong Kong University of Science and Technology, 2014-15
    • List of Teachers Ranked as Excellent by Their Students, University of Illinois at Urbana Champaign, 2006
    • List of Teachers Ranked as Excellent by Their Students, University of Illinois at Urbana Champaign, 2007

Liu, Ruixuan(劉睿軒)

Teaching Areas

Econometrics

Research Interests

Econometrics
Data Science

  • Grants
    • “Improvement on Competitiveness in Hiring New Faculties” Funding Scheme awarded by The Chinese University of Hong Kong with HK$1,072,208, 2022-2024.

Wang, Weiquan(王偉泉)

Biography

Prof. Weiquan Wang is a Professor in the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School. He received his Ph.D. in Management Information Systems from the University of British Columbia, and double-bachelor’s degrees in i) Engineering Physics and ii) Enterprise Management as well as a Master’s degree in Management Science and Engineering from Tsinghua University. Before joining CUHK Business School, he was at the College of Business at the City University of Hong Kong. He served as an associate editor of MIS Quarterly during Jan 2012 and Dec 2015. He is serving on the editorial boards of the Journal of the Association for Information Systems (JAIS) and a few other leading scholarly outlets.

Teaching Areas

IT-enabled organisational transformation
Information Systems Management
Business research method

Research Interests

Online Platforms: Designs, User Engagement and Behavior;
Human-AI/Algorithm Interaction
Online Recommendation Agents and Decision-Making
Financial Technologies

  • Publications & Working Papers
    • Honglin Deng, Weiquan Wang, and Kai H. Lim (2024), “Addressing Online Users’ Suspicion of Sponsored Search Results: Effects of Informational Cues,” Information Systems Research, forthcoming.
    • Jingzhi Zhang, Weiquan Wang, Lara Khansa, and Sung S. Kim (2024), “Actual Private Information Disclosure in Online Social Networking Sites: A Reflective–Impulsive Model,” Journal of the Association for Information Systems, forthcoming.
    • Lingyun Qiu, Weiquan Wang, and Jun Pan (2023), “The Persuasive Power of Emoticons in Electronic Word-of-Mouth Communication in Social Networking,” MIS Quarterly, (47:2), pp. 511-534.
    • Honglin Deng, Weiquan Wang, and Kai H. Lim (2022), “Repairing Integrity-based Trust Violations in Ascription Disputes for Potential e-Commerce Customers,” MIS Quarterly, (46:4) pp. 1983-2014.
    • F. Cao, Weiquan Wang, Chee-Wee Tan, and Eric Lim (2022), “Do Social Dominance-Based Faultlines Help or Hurt Team Performance in Crowdsourcing Tournaments?” Journal of Management Information Systems, 39(1), 247-275.
    • Honglin Deng, Weiquan Wang, Siyuan Li, and K. Lim (2022), “Reducing User Avoidance of Sponsored Search Results: The Effects of Social Influence Cues,” MIS Quarterly, 46(1), 35-70.
    • Ran Li, Yaobin Lu, Jifeng Ma, Weiquan Wang (2021), “Examining Gifting Behavior on Social Live Streaming Services: An Identity-based Motivation Model,” Information & Management, 58(6), No. 103406.
    • T. Liu, Weiquan Wang, J. Xu, D. Ding, H. Deng (2021), “Interactive effects of advising strength and brand familiarity on users’ trust and distrust in online recommendation agents,” Information Technology & People, 34(7), 1920-1947.
    • Weiquan Wang, and M. Wang (2019), “Effects of Sponsorship Disclosure on Perceived Integrity of Biased Recommendation Agents: Psychological Contract Violation and Knowledge-based Trust Perspectives,” Information Systems Research, 30(2), 507–522.
    • Weiquan Wang, J. Xu, and M. Wang (November 2018), “Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust versus Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations,” Management Science, 64(11), 5198-5219.
    • L. Zhou, Weiquan Wang, J.D. Xu, T. Liu, and J. Gu (July 2018), “Perceived Information Transparency in B2C e-commerce: An Empirical Investigation,” Information and Management, 55(7), 912-927.
    • Weiquan Wang and Izak Benbasat (September 2016), “An Empirical Assessment of Alternative Designs for Enhancing Different Types of Trusting Beliefs in Online Recommendation Agents,” Journal of Management Information Systems, 33(3), 744-775.
    • Z. Jiang, Weiquan Wang, B.C.Y. Tan, and J. Yu (2016), “The Determinants and Impacts of Aesthetics in Users’ First Interaction with Websites,” Journal of Management Information Systems, 33(1), 229-259.
    • Weiquan Wang, L. Qiu, D. Kim, and I. Benbasat (2016), “Effects of Rational and Social Appeals of Online Recommendation Agents on Cognition- and Affect-based Trust,” Decision Support Systems, 86 (2016), 48-60.
    • Weiquan Wang, Y. Zhao, L. Qiu, and Y. Zhu (2014), “Effects of Emoticons on the Acceptance of Negative Feedback in Computer-Mediated Communication,” Journal of the Association for Information Systems, 15(8), 454-483.
    • Weiquan Wang and Izak Benbasat (September 2013), “A Contingency Approach to Investigating the Effects of User-System Interaction Modes of Online Decision Aids,” Information Systems Research, 24(3), 861-876.
    • Y. Zhu, Y. Li, Weiquan Wang, and J. Chen (June 2010), “What Leads to the Post-Implementation Success of ERP? An Empirical Study of the Chinese Retail Industry”, International Journal of Information Management, 30(3), 265-276.
    • Y. Zhao, Weiquan Wang, Y. Zhu (June 2010), “Antecedents of the Closeness of Human-Avatar Relationships in a Virtual World”, Journal of Database Management, 21 (2), 41-68.
    • Weiquan Wang and Izak Benbasat, (2009) “Interactive Decision Aids for Consumer Decision Making in e-Commerce: The Influence of Perceived Strategy Restrictiveness,” MIS Quarterly 33(2), 293-320.
    • Weiquan Wang and Izak Benbasat, (2008) “Attributions of Trust in Decision Support Technologies: A Study of Recommendation Agents for E-Commerce,” Journal of Management Information Systems, 24(4), 249-273.
    • Weiquan Wang and Izak Benbasat, (2007) “Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs,” Journal of Management Information Systems, 23(4), 217-246.
    • Weiquan Wang and Izak Benbasat, (2005) “Trust in and Adoption of Online Recommendation Agents,” Journal of the Association for Information Systems, 6(3), 72-101.
    • Zhenhui Jiang, Weiquan Wang, and Izak Benbasat, (2005) “Multimedia-based Interactive Advising Technology for Online Consumer Decision Support,” Communications of the ACM, 48(9), 92-98.
    • Sherrie X. Komiak, Weiquan Wang and Izak Benbasat, (2004/2005) “Trust Building in Virtual Salespersons versus in Human Salespersons: Similarities and Differences,” e-Service Journal, 3(3), 49-63.
  • Grants
    • “’Open Source’ on Online Crowdsourcing Contest Platforms: Constraining or Stimulating Ideas?,” General Research Fund (GRF) awarded by Hong Kong Research Grant Council (RGC), 2024-2025 (Principal Investigator)
    • “App Innovation Strategies and Innovation Performance: A Perspective of Developer Brand Equity,” General Research Fund (GRF) awarded by Hong Kong Research Grant Council (RGC), 2021-2024 (Principal Investigator)
    • “搜索引擎中竞价排名广告披露方式与用户反应的实证研究,” awarded by National Natural Science Foundation of China (NSFC), 2021-2024 (Principal Investigator)
    • “This Is Not The Brand I Am Searching For! Can Social Influence Cues Always Reduce Sponsored Search Results Avoidance?,” GRF awarded by RGC, 2018-2021 (Principal Investigator).
    • “To Click or Not To Click? An Experimental Investigation into Users’ Avoidance of Sponsored Search Results,” GRF awarded by RGC, 2016-2021 (Principal Investigator)
    • “网络用户隐私担忧与主动性泄露隐私信息之间的悖论:理论探索和基于社交网络的实证研究,” awarded by NSFC, 2015-2018 (Principal Investigator)
    • “Do You Really Care about Your Information Privacy? An Empirical Investigation of Privacy Attitude-Behavior Paradox in Online Social Networking Sites,” GRF awarded by RGC, 2012-2014 (Principal Investigator)
    • “The Effects of Advising Strength on Users’ Trust and Distrust in Online Recommendation Agents: The Moderation Role of Source Credibility and Recommendation Familiarity,” GRF awarded by RGC, 2011-2012 (Principal Investigator)
    • “To Trust or Distrust Online Recommendation Agents? An Experimental Investigation into the Effect Mechanisms of Recommendation Neutrality and Transparency Strategies,” GRF awarded by RGC, 2010-2012 (Principal Investigator)
    • “Effects of Anthropomorphic Interfaces vs. Explanation Facilities on Trust in Online Recommendation Agents: An Elaboration Likelihood Model Perspective,” GRF awarded by RGC, 2008-2010 (Principal Investigator)
    • “Trust in Technological Artifacts: Dimensions and Roles in a Trust Network,” GRF awarded by RGC, 2007-2009 (Principal Investigator)

Zhang, Philip Renyu(張任宇)

ZHANG Renyu

Biography

Professor Philip Renyu Zhang joined The Chinese University of Hong Kong (CUHK) Business School as a visiting scholar in the Department of Decisions, Operations and Technology in September 2021 and has been an Associate Professor since September 2022. Prior to joining CUHK Business School, he was an Assistant Professor of Operations Management at New York University (NYU) Shanghai and an NYU Global Network Assistant Professor since August 2016. Professor Zhang holds a PhD degree in Business Administration (Operations Management) at Olin Business School, Washington University in St. Louis, and a Bachelor’s degree in Mathematics from Peking University.

Professor Zhang’s research interests are applying AI and data science to address fundamental business operations issues under the emerging trends in technology, marketplaces, and society. He is particularly enthusiastic about developing data science methodologies (machine learning, causal inference, and data-driven optimisation) to evaluate and optimise the operations strategies in the contexts of online platforms and marketplaces, sharing economy, and social networks, especially their recommendation, advertising, pricing, and matching policies. His research works have appeared in Management Science, Operations Research, and Manufacturing & Service Operations Management, and have been recognised by various research awards of the INFORMS and POMS communities. His research projects have been funded by NSFC, SMEC, STCSM, HK RGC, and Tencent.

Professor Zhang is also a strong adherent to the philosophy that business research should push the “efficient frontier” of intellectual depth and practical impact, thus striving to implement his research in business practice whenever applicable.

Teaching Areas

Business Analytics
Data Science
Machine Learning
Artificial Intelligence
Operations Management

Research Interests

Methodologies:
Machine Learning and Deep Learning
Causal Inference and Econometrics
Reinforcement Learning
Data-Driven Optimisation

Applications:
Online Platforms and Marketplaces
Social Networks
Artificial Intelligence Ethics
Revenue Management and Pricing
Inventory and Supply Chain Management

  • Grants
    • “Algorithmic Self-Preferencing on E-Commerce Platforms: Evidence from JD.COM” by Hong Kong Research Grants Council, General Research Fund 14504123, with HKD 444,066, 2024-2025 (Principal Investigator).
    • Collaboration with University Fund, by Tencent, RMB 332,310, 2022 (Principal Investigator)
    • “Causal Inference with Multiple A/B Tests on Large-Scale Online Platforms” by Hong Kong Research Grants Council, General Research Fund 14502722, with HKD 629,325, 2022-2025 (Principal Investigator)
    • CUHK ‘Improvement on Competitiveness in Hiring New Faculties’ Funding Scheme, with HKD 1,500,000, 2022 (Principal Investigator)
    • “Carpool Services of Online Ride-Sharing Platforms”, by the National Natural Science Foundation of China, Young Scientist Program 71802133, with RMB 180,000, 2019-2021 (Principal Investigator)
    • Shanghai Eastern Scholar, by Shanghai Municipal Education Commission, Young Scientist Program QD2018053, RMB 600,000, 2019-2021 (Principal Investigator)
    • “The Impact of Social Networks on Operations Strategies”, by the Shanghai Science and Technology Committee, Pujiang Talent Program 17PJC074, RMB 100,000, 2017-2019 (Principal Investigator)
  • Awards & Honours
    • Meritorious Service Award, Manufacturing & Service Operations Management, 2018, 2019, 2022
    • Finalist Award, POMS College of Supply Chain Management Best Student Paper Competition, 2015
    • Honorable Mention, INFORMS Service Science Best Cluster Paper Award, 2017
    • Finalist Award, INFORMS Data Mining Section Best Paper Competition, 2019
    • Finalist Award, INFORMS Revenue Management and Pricing Student Paper Competition, 2020
  • Academic/Professional Services
    • Senior Editor, Production and Operations Management, since September 2022
    • Associate Editor, Naval Research Logistics, since August 2022
    • CUHK Business School IBBA Business Analytics Concentration Advisor, since September 2022
    • Member, Curriculum Committee of the Department of Decisions, Operations and Technology, 2021-2022

Wang, Jingbo (Jimbo)(汪靜波)

WANG Jingbo

Biography

Prof. Jingbo Wang is an Assistant Professor in the Department of Marketing at The Chinese University of Hong Kong (CUHK) Business School. He holds a BA in Economics from Lingnan College, Sun Yat-sen University in Guangzhou, a MA in Economics and Finance from Centro de Estudios Monetarios y Financieros (CEMFI) in Madrid, and a PhD in Economics from University of Southern California, Los Angeles. His research interests include marketing analytics, quantitative marketing, machine learning, and social network analysis.

Teaching Areas

Business Analytics
Machine Learning

Research Interests

Marketing Analytics
Quantitative Marketing
Machine Learning
Social Network Analysis

Li, Tim Tianyi(李天意)

Biography

Prof. Tianyi (Tim) Li joined the Department of Decisions, Operations and Technology at The Chinese University of Hong Kong (CUHK) Business School in 2021 as an Assistant Professor, after completing PhD studies at the System Dynamics Group in MIT Sloan. He holds a bachelor’s degree from Peking University and a master’s degree from Princeton University. He received the Dana Meadows Award (2021) from the International System Dynamics Society. His research tries to contribute modelling and algorithmic efforts to management, industrial and policy studies from a data-driven, network-oriented, and dynamic-control perspective. He currently works on modeling platform dynamics, and network sciences & machine-learning applications in business practice.

Teaching Areas

Business Information Systems
Networks and Security

Research Interests

Network Sciences
System Dynamics
Industrial Engineering
Management Algorithms
Mathematical Modelling

  • Awards & Honours
    • Dana Meadows Award, International System Dynamics Society, 2021
    • Fellowship, MIT Sloan School of Management, 2017-2021
    • Fellowship, Princeton University, 2015-2017

Chen, Kevin Hongfan(陳泓帆)

Biography

Hongfan (Kevin) Chen is an Assistant Professor of the Department of Decisions, Operations and Technology at The Chinese University of Hong Kong (CUHK) Business School. He received his PhD and MBA degrees in Operations Management from the University of Chicago Booth School of Business. Prior to Chicago Booth, he studied Industrial Engineering and Applied Mathematics at Georgie Institute of Technology. Before joining CUHK, he also had some professional experience in companies including Airbnb, Amazon, Cox Enterprises, Interface, Hewlett Packard and ABB. Professor Chen’s research primarily focuses on revenue management, platform marketplaces, and optimisation under uncertainty.

Research Interests

Revenue Management
Platform Economy
Optimisation under Uncertainty