Dr Bowei Chen

  • Senior Lecturer in Marketing Analytics and Data Science (Management)

telephone: 01413307032
email: Bowei.Chen@glasgow.ac.uk

241L, Gilbert Scott Building, G12 8QQ

ORCID iDhttps://orcid.org/0000-0002-4045-3253

Biography

Bowei Chen is a Senior Lecturer (Associate Professor) in Marketing Analytics and Data Science at the Adam Smith Business School of University of Glasgow. He received a PhD in Computer Science from University College London, and has broad research interests related to the applications of probabilistic modeling and machine learning in business, with special focuses on marketing and finance. Previously, he was a Lecturer (Assistant Professor) in the School of Computer Science at University of Lincoln and has also worked at/research visited Copenhagen Business School, Trinity College Dublin, University College London, Aarhus University, Université de Technologie de Belfort-Montbéliard, University of Bath, National University of Singapore, and Microsoft Research Cambridge. [Personal Website]

Research interests

Bowei is a member of the School's Marketing Research Cluster and also a member of the College's interdisciplinary research unit Social and Digital Change Group.

Areas of expertise:

  • Data Science
  • Machine Learning
  • Quantitative Marketing
  • Mathematical Finance
  • Information Systems

Publications

List by: Type | Date

Jump to: 2022 | 2021 | 2020 | 2019 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012
Number of items: 17.

2022

Huang, J., Chen, B. , Yan, Z., Ounis, I. and Wang, J. (2022) GEO: A computational design framework for automotive exterior facelift. ACM Transactions on Knowledge Discovery from Data, (Accepted for Publication)

Huang, J., Chen, B. , Luo, L., Yue, S. and Ounis, I. (2022) DVM-CAR: A Large-Scale Automotive Dataset for Visual Marketing Research and Applications. In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), Osaka, Japan, 17-20 Dec 2022, (Accepted for Publication)

Zhang, Y., Zhuang, H., Liu, T., Chen, B. , Cao, Z., Fu, Y., Fan, Z. and Chen, G. (2022) A Bayesian graph embedding model for link-based classification problems. IEEE Transactions on Network Science and Engineering, 9(2), pp. 716-727. (doi: 10.1109/TNSE.2021.3131223)

2021

Zheng, Y., Yang, Y. and Chen, B. (2021) Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction. In: 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21), Singapore, 14-18 Aug 2021, pp. 3968-3975. ISBN 9781450383325 (doi: 10.1145/3447548.3467115)

2020

Zheng, Y., Chen, B. , Hospedales, T. M. and Yang, Y. (2020) Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. In: 34th AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA, 07-12 Feb 2020, pp. 1242-1249. ISBN 9781577358350 (doi: 10.1609/aaai.v34i01.5478)

Ni, J., Chen, B. , Allinson, N. M. and Ye, X. (2020) A hybrid model for predicting human physical activity status from lifelogging data. European Journal of Operational Research, 281(3), pp. 532-542. (doi: 10.1016/j.ejor.2019.05.035)

Chen, B. , Huang, J., Huang, Y., Kollias, S. and Yue, S. (2020) Combining guaranteed and spot markets in display advertising: selling guaranteed page views with stochastic demand. European Journal of Operational Research, 280(3), pp. 1144-1159. (doi: 10.1016/j.ejor.2019.07.067)

2019

Chen, B. and Kankanhalli, M. (2019) Pricing average price advertising options when underlying spot market prices are discontinuous. IEEE Transactions on Knowledge and Data Engineering, 31(9), pp. 1765-1778. (doi: 10.1109/TKDE.2018.2867027)

2017

Chen, X., Chen, B. and Kankanhalli, M. (2017) MM2RTB: Bringing Multimedia Metrics to Real-Time Bidding. In: 10th International Workshop on Data Mining for Online Advertising (ADKDD), Halifax, NS, Canada, 14 Aug 2017, ISBN 9781450351942 (doi: 10.1145/3124749.3124757)

Chen, X., Chen, B. and Kankanhalli, M. (2017) Optimizing Trade-offs Among Stakeholders in Real-Time Bidding by Incorporating Multimedia Metrics. In: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Tokyo, Japan, 7-11 Aug 2017, pp. 205-214. ISBN 9781450350228 (doi: 10.1145/3077136.3080802)

2016

Chen, B. (2016) Risk-Aware Dynamic Reserve Prices of Programmatic Guarantee in Display Advertising. In: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), Barcelona, Spain, 12-15 Dec 2016, pp. 511-518. ISBN 9781509059102 (doi: 10.1109/ICDMW.2016.0079)

2015

Chen, B. , Wang, J., Cox, I. J. and Kankanhalli, M. S. (2015) Multi-keyword multi-click advertisement option contracts for sponsored search. ACM Transactions on Intelligent Systems and Technology, 7(1), 5. (doi: 10.1145/2743027)

Chen, B. and Wang, J. (2015) A lattice framework for pricing display advertisement options with the stochastic volatility underlying model. Electronic Commerce Research and Applications, 14(6), pp. 465-479. (doi: 10.1016/j.elerap.2015.07.002)

2014

Chen, B. , Yuan, S. and Wang, J. (2014) A Dynamic Pricing Model for Unifying Programmatic Guarantee and Real-Time Bidding in Display Advertising. In: Eighth International Workshop on Data Mining for Online Advertising (ADKDD), New York, NY, USA, 24-27 Aug 2014, ISBN 9781450329996 (doi: 10.1145/2648584.2648585)

Yuan, S., Wang, J., Chen, B. , Mason, P. and Seljan, S. (2014) An Empirical Study of Reserve Price Optimisation in Real-time Bidding. In: 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), New York, NY, USA, 24-27 Aug 2014, pp. 1897-1906. ISBN 9781450329569 (doi: 10.1145/2623330.2623357)

2013

Zhang, W., Wang, J., Chen, B. and Zhao, X. (2013) To Personalize or Not: a Risk Management Perspective. In: 7th ACM Conference on Recommender Systems (RecSys), Hong Kong, China, 12-16 Oct 2013, pp. 229-236. ISBN 9781450324090 (doi: 10.1145/2507157.2507167)

2012

Wang, J. and Chen, B. (2012) Selling Futures Online Advertising Slots via Option Contracts. In: 21st International Conference on World Wide Web (WWW), Lyon, France, 16-20 Apr 2012, pp. 627-628. ISBN 9781450312301 (doi: 10.1145/2187980.2188160)

This list was generated on Mon Jan 30 11:59:17 2023 GMT.
Number of items: 17.

Articles

Huang, J., Chen, B. , Yan, Z., Ounis, I. and Wang, J. (2022) GEO: A computational design framework for automotive exterior facelift. ACM Transactions on Knowledge Discovery from Data, (Accepted for Publication)

Zhang, Y., Zhuang, H., Liu, T., Chen, B. , Cao, Z., Fu, Y., Fan, Z. and Chen, G. (2022) A Bayesian graph embedding model for link-based classification problems. IEEE Transactions on Network Science and Engineering, 9(2), pp. 716-727. (doi: 10.1109/TNSE.2021.3131223)

Ni, J., Chen, B. , Allinson, N. M. and Ye, X. (2020) A hybrid model for predicting human physical activity status from lifelogging data. European Journal of Operational Research, 281(3), pp. 532-542. (doi: 10.1016/j.ejor.2019.05.035)

Chen, B. , Huang, J., Huang, Y., Kollias, S. and Yue, S. (2020) Combining guaranteed and spot markets in display advertising: selling guaranteed page views with stochastic demand. European Journal of Operational Research, 280(3), pp. 1144-1159. (doi: 10.1016/j.ejor.2019.07.067)

Chen, B. and Kankanhalli, M. (2019) Pricing average price advertising options when underlying spot market prices are discontinuous. IEEE Transactions on Knowledge and Data Engineering, 31(9), pp. 1765-1778. (doi: 10.1109/TKDE.2018.2867027)

Chen, B. , Wang, J., Cox, I. J. and Kankanhalli, M. S. (2015) Multi-keyword multi-click advertisement option contracts for sponsored search. ACM Transactions on Intelligent Systems and Technology, 7(1), 5. (doi: 10.1145/2743027)

Chen, B. and Wang, J. (2015) A lattice framework for pricing display advertisement options with the stochastic volatility underlying model. Electronic Commerce Research and Applications, 14(6), pp. 465-479. (doi: 10.1016/j.elerap.2015.07.002)

Conference Proceedings

Huang, J., Chen, B. , Luo, L., Yue, S. and Ounis, I. (2022) DVM-CAR: A Large-Scale Automotive Dataset for Visual Marketing Research and Applications. In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), Osaka, Japan, 17-20 Dec 2022, (Accepted for Publication)

Zheng, Y., Yang, Y. and Chen, B. (2021) Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction. In: 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21), Singapore, 14-18 Aug 2021, pp. 3968-3975. ISBN 9781450383325 (doi: 10.1145/3447548.3467115)

Zheng, Y., Chen, B. , Hospedales, T. M. and Yang, Y. (2020) Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. In: 34th AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA, 07-12 Feb 2020, pp. 1242-1249. ISBN 9781577358350 (doi: 10.1609/aaai.v34i01.5478)

Chen, X., Chen, B. and Kankanhalli, M. (2017) MM2RTB: Bringing Multimedia Metrics to Real-Time Bidding. In: 10th International Workshop on Data Mining for Online Advertising (ADKDD), Halifax, NS, Canada, 14 Aug 2017, ISBN 9781450351942 (doi: 10.1145/3124749.3124757)

Chen, X., Chen, B. and Kankanhalli, M. (2017) Optimizing Trade-offs Among Stakeholders in Real-Time Bidding by Incorporating Multimedia Metrics. In: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Tokyo, Japan, 7-11 Aug 2017, pp. 205-214. ISBN 9781450350228 (doi: 10.1145/3077136.3080802)

Chen, B. (2016) Risk-Aware Dynamic Reserve Prices of Programmatic Guarantee in Display Advertising. In: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), Barcelona, Spain, 12-15 Dec 2016, pp. 511-518. ISBN 9781509059102 (doi: 10.1109/ICDMW.2016.0079)

Chen, B. , Yuan, S. and Wang, J. (2014) A Dynamic Pricing Model for Unifying Programmatic Guarantee and Real-Time Bidding in Display Advertising. In: Eighth International Workshop on Data Mining for Online Advertising (ADKDD), New York, NY, USA, 24-27 Aug 2014, ISBN 9781450329996 (doi: 10.1145/2648584.2648585)

Yuan, S., Wang, J., Chen, B. , Mason, P. and Seljan, S. (2014) An Empirical Study of Reserve Price Optimisation in Real-time Bidding. In: 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), New York, NY, USA, 24-27 Aug 2014, pp. 1897-1906. ISBN 9781450329569 (doi: 10.1145/2623330.2623357)

Zhang, W., Wang, J., Chen, B. and Zhao, X. (2013) To Personalize or Not: a Risk Management Perspective. In: 7th ACM Conference on Recommender Systems (RecSys), Hong Kong, China, 12-16 Oct 2013, pp. 229-236. ISBN 9781450324090 (doi: 10.1145/2507157.2507167)

Wang, J. and Chen, B. (2012) Selling Futures Online Advertising Slots via Option Contracts. In: 21st International Conference on World Wide Web (WWW), Lyon, France, 16-20 Apr 2012, pp. 627-628. ISBN 9781450312301 (doi: 10.1145/2187980.2188160)

This list was generated on Mon Jan 30 11:59:17 2023 GMT.

Grants

Medium and large grants (> 10,000 GBP):

  • Co-I, "Self-supervised Learning of Transformers for Image Recognition", 150,000 CNY, Shenzhen University WeBank Institute of FinTech, China, 2022.
  • Co-I, “Investigating the Impact of AI Empowered Mobile Marketing Strategies on Customer Acquisition, Retention, Defection, and Win-back Links”, 480,000 CNY, National Natural Science Foundation Grant, China, 2020-2023.
  • Co-I, "Big Data and Eco-Innovative Resource Use in the NSR – Greenhouse Industry Greening the Growth in Horticultural Production", 3,400,768 EUR (and 576,808 EUR for Lincoln’s WP), North Sea Region Program, Europe, 2017-2022
  • PI (Academic Supervisor), "Developing a Data Mining Platform to Revolutionise Synthetic Sport Surface Maintenance Practice and Principles", 187,000 GBP, Knowledge Transfer Partnerships (KTP) Program (Innovative UK and Replay Ltd), UK, 2017-2019

Small grants (<=10,000 GBP):

PI/Awarded Researcher of Nvidia Accelerated Data Science Grant, Nvidia GPU Grant, Google Cloud Academic Research Grant, Microsoft Learn for Educators Program, ESRC IAA Business Booster Fund, Region Bourgogne Franche Comté Mobility Grant, UofG Research Reinvigoration Funding, etc.

Supervision

Bowei is interested in supervising new doctoral or visiting researchers, particularly in machine learning or AI applications in business. Expectations are that potential candidates have a passion and strong skills for quantitative research and are highly self-motivated. If you have an interesting idea and would like to make informal inquiry, please send over a research proposal along with a copy of your CV and transcripts. 

  • Ding, Ruixin
    Data Analytics and Decision Support for Auto Marketing Strategies in the Chinese Market
  • HE, Mengwei
    Customer engagement and online review: Different voices between Airbnb and hotel customers
  • Liang, Jiawen
    Robo-advisors and reinforcement learning
  • Liu, Shuying
    Deep Learning for Business Analtyics of Non-Fungible Tokens

Teaching

  • Data Science for Marketing Analytics (MSc)
  • Digital Marketing Strategy (MSc)

Additional information

Academic services:

Editorial board

  • Electronic Commerce Research and Applications
  • Frontiers in Big Data
  • Frontiers in Artificial Intelligence

Reviewer/technical program committee

  • European Journal of Operational Research
  • European Journal of Finance
  • International Journal of Finance & Economics
  • ACM Transactions on Economics and Computation
  • ACM Transactions on Information Systems
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Knowledge and Data Engineering 
  • Communications of the ACM
  • Neurocomputing
  • Journal of the American Society for Information Science and Technology
  • Information and Management
  • NeurIPS, ICML, AAAI, AISTATS, SIGIR, WWW, WSDM, CIKM

Membership:

  • Fellow of Higher Education Academy

Selected awards:

  • BITE Industry Award Exchange Scheme, University College London, UK, 2014
  • Best Paper Award, The 8th International Workshop on Data Mining for Online Advertising (AdKDD, KDD Workshop), New York City, USA, 2014
  • UCL Advances PhD Enterprise Scholarship, University College London, UK, 2014
  • Second Prize Award, Hedge Fund Trading Competition, IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr), London, UK, 2014
  • Dean’s Prize, University College London, UK, 2012
  • Postgraduate Research Studentship, University College London, UK, 2011