About

I have broad research interests related to the applications of probabilistic modelling and deep learning in business, with special focuses on marketing and finance. I welcome inquiries from students wishing to pursue PhD with me. Expectations are that potential candidates have a passion and strong skills for quantitative research and are highly self-motivated. Please email me with your CV and transcripts.

Student research funding opportunities

Research

Datasets

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DVM Car: a large-scale automobile dataset for visual marketing
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Multimedia datasets: trade-offs optimisation in real-time bidding for display advertising
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Multi-slot real-time bidding multimedia datasets

Selected Working Papers/Papers in Progress

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Gated neural networks for implied volatility surfaces
Yu Zheng, Yongxin Yang, Bowei Chen
Working paper (available in arXiv), 2020
Does that car want to give me a ride? Bio-inspired product design
Jingmin Huang, Bowei Chen, Lan Luo
Paper in progress, 2020

Publications

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Index tracking with cardinality constraints: a stochastic neural networks approach
Yu Zheng, Bowei Chen, Timothy Hospedales, Yongxin Yang
Proceedings of the AAAI Conference on Artificial Intelligence, 2020
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A hybrid model for predicting human physical activity status from lifelogging data
Ji Ni, Bowei Chen, Nigel Allinson, Xujiong Ye
European Journal of Operational Research, Volume 281, Issue 3, pp. 532-542, 2020
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Combining guaranteed and spot markets in display advertising: selling guaranteed page views with stochastic demand
Bowei Chen, Jingmin Huang, Yufei Huang, Stefanos Kollias, Shigang Yue
European Journal of Operational Research, Volume 280, Issue 3, pp. 1144-1159, 2020
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Pricing average price advertising options when underlying spot market prices are discontinuous
Bowei Chen, Mohan Kankanhalli
IEEE Transactions on Knowledge and Data Engineering, Volume 31, Issue 9, pp. 1765-1778, 2019
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MM2RTB: bringing multimedia metrics to real-time bidding
Xiang Chen, Bowei Chen, Mohan Kankanhalli
Proceedings of the 10th International Workshop on Data Mining for Online Advertising (KDD Workshop), No.4, 2017
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Optimizing trade-offs among stakeholders in real-time bidding by incorporating multimedia metrics
Xiang Chen, Bowei Chen, Mohan Kankanhalli
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 205-214, 2017
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Risk-aware dynamic reserve prices of programmatic guarantee in display advertising
Bowei Chen
Proceedings of the 16th IEEE International Conference on Data Mining Workshops (ICDMW), pp. 511-518, 2016
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A lattice framework for pricing display advertisement options with the stochastic volatility underlying model
Bowei Chen, Jun Wang
Electronic Commerce Research and Applications, Volume 14, Issue 6, pp. 465-479, 2015
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Multi-keyword multi-click advertisement option contracts for sponsored search
Bowei Chen, Jun Wang, Ingemar Cox, Mohan Kankanhalli
ACM Transactions on Intelligent Systems and Technology, Volume 7, Issue 1, Article No. 5, 2015
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A dynamic pricing model for unifying programmatic guarantee and real-time bidding in display advertising
Bowei Chen, Shuai Yuan, Jun Wang
Proceedings of the 8th International Workshop on Data Mining for Online Advertising (KDD Workshop), pp. 1-9, 2014
Best Paper Award
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An empirical study of reserve price optimisation in real-time bidding
Shuai Yuan, Jun Wang, Bowei Chen, Peter Mason, Sam Seljan
Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 1897-1906, 2014
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To personalize or not: a risk management perspective
Weinan Zhang, Jun Wang, Bowei Chen, Xiaoxue Zhao
Proceedings of the 7th ACM Conference on Recommender Systems (RecSys), pp. 229-236, 2013
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Selling futures online advertising slots via option contracts
Jun Wang, Bowei Chen
Proceedings of the 21st International World Wide Web Conference (WWW), pp. 627-628, 2012

Teaching

I teach data science and analytics related courses for undergraduate and postgraduate students in computer science school (previously) and business school (now). I mainly use the materials from this list of resources as the main references in my teaching (as in my research). My students or potential students who need suggestions for directed studies could have a look.

Adam Smith Business School, University of Glasgow, UK

Data Science for Marketing Analytics
2018-2019 | 2019-2020 (MSc)
Digital Marketing Strategy
2019-2020 (MSc)

Copenhagen Business School, Denmark

Business Intelligence
2018-2019 | 2019-2020 (Summer School MSc)
Machine Learning for Predictive Analytics in Business
2019-2020 (Summer School MSc)

School of Management, University College London, UK

Mathematics III: Probability Theory
2019-2020 (Year 2)

Department of Economics and Business Economics
Aarhus University, Denmark

Data Science for Business Intelligence
2018-2019 (Summer School BSc)

School of Computer Science, University of Lincoln, UK

Algorithms for Data Mining
2017-2018 (Year 3 and MComp)
Data Science Tools and Techniques
2017-2018 (Year 3 and MComp)
Business Intelligence
2016-2017 | 2017-2018 (Year 3 and MComp)
Data Science
2016-2017 (Year 3 and MComp)
Business Processes
2015-2016 | 2016-2017 (Year 2)
Information Systems in Practice
2015-2016 (Year 1)
Social Media and Society
2015-2016 (Year 1)
© Bowei Chen 2018-2020