About
My research focuses on the development and application of
AI/machine learning, probabilistic modelling, and data
mining to address challenges in business. My work spans
marketing, finance, operations management, and
metascience. In marketing, I examine digital advertising
revenue management, AI-powered product visual design,
and tourism and service analytics. In finance, I explore
digital financial products and markets, including
cryptocurrency assets, risk modelling, and computational
investing. In operations management, I develop
AI-enabled analytical approaches for forecasting,
optimisation, and decision support. In metascience, I
investigate the role of AI in scientific discovery,
knowledge production, and research evaluation, with a
particular interest in integrating AI with traditional
research methodologies.
Information for Students
I am on sabbatical during the 2026-2027 academic year and am therefore not accepting new PhD students during this period, other than those already agreed. Prospective PhD students interested in business analytics, AI, or related areas are encouraged to contact colleagues at the Adam Smith Business School, who may have suitable opportunities available.
For students undertaking BSc, MSc, MBA, or MRes
dissertations, as well as final-year projects under my
supervision at the Adam Smith Business School, this
General Advice
to Dissertation Projects may be
helpful.
Publications
Books
Business Analytics with R: A Tidy
Approach
Bowei Chen and Tianyuan
Huang
Palgrave Macmillan, 1st
Edition,
2026, Forthcoming
Supplementary materials (datasets, example
scripts and exercise solutions) available at the
Github
Repo.
Business Analytics with Python:
Essential Skills for Business Students
Bowei Chen and Gerhard
Kling
Kogan Page, 1st Edition,
March, 2025
Supplementary materials (datasets, example
scripts and exercise solutions) available at the
Github
Repo.
Papers
Dimos: Diffusion model with unified
sequential state space for session-based
recommendation
Weiyue Li, Ming Gao, Bowei Chen,
Jingmin An, Hao Dong, Wei Jiang, Jiafu
Tang
Engineering Applications of
Artificial Intelligence, 169, 114131,
2026.
From prediction to prevention:
Using text mining and explainable machine
learning for urban bus accident analytics
Bowei Chen, Yufei Huang, Yu
Zheng, Xiaofeng Liu
Risk Analysis, 46, No. 1,
e70183, 2026
MultiNFT: A multimodal dataset for
non-fungible tokens market analysis
Shuying Liu, Bowei Chen, Cathy
Yi-Hsuan Chen, Yu Zheng, Jun Wang
Proceedings of 2025 IEEE
International Conference on Big Data,
pp. 6906-6913, 2025
Exploring serial patterns in
negative hotel reviews
Rodion Skovoroda, Wei Yang, Bowei
Chen, Trevor Buck
Annals of Tourism Research
Empirical Insights,
6(2), 100199, 2025
Social capital matters: Towards
comprehensive user preference for product
recommendation with deep learning
Weiyue Li, Ming Gao, Bowei Chen,
Jingmin An, Yeming Gong
Decision Support Systems,
198, 114527, 2025
Collaborative local-global context
modeling for session-based recommendation
Weiyue Li, Bowei Chen, Ming Gao,
Jingmin An, Hao Donga, Cheng Chen, Weiguo Fan,
Zhiguo Zhu
Information Processing and
Management, 62, 104196, 2025
Business continuity management in
the sharing economy: Insights from Airbnb online
reviews
Bowei Chen, Thomas Anker,
Xiaoning Liang
Tourism Management, 107,
105067, 2025
EcoVal: An efficient data valuation
framework for machine learning
Ayush K Tarun, Vikram S
Chundawat, Murari Mandal, Hong Ming Tan, Bowei
Chen, Mohan Kankanhalli
Proceedings of the 30th ACM
SIGKDD Conference on Knowledge Discovery and
Data Mining, pp. 2866-2875, 2024
Towards a unified understanding of
uncertainty quantification in traffic flow
forecasting
Weizhu Qian, Yan Zhao, Dalin
Zhang, Bowei Chen, Kai Zheng, Xiaofang
Zhou
IEEE Transactions on Knowledge
and Data Engineering, 36(5), pp.
2239-2256, 2024
SRNI-CAR: A comprehensive dataset
for analyzing the Chinese automotive
market
Ruixin Ding, Bowei Chen, James M
Wilson, Zhi Yan, Yufei Huang
Proceedings of 2023 IEEE
International Conference on Big Data,
pp. 3405-3412, 2023
GEO: A computational design
framework for automotive exterior facelift
Jingmin Huang, Bowei Chen, Zhi
Yan, Iadh Ounis, Jun Wang
ACM Transactions on Knowledge
Discovery from Data, 17(6), No. 82,
2023
DVM-CAR: A large-scale automotive
dataset for visual marketing research and
applications
Jingmin Huang, Bowei Chen, Lan
Luo, Shigang Yue, Iadh Ounis
Proceedings of 2022 IEEE
International Conference on Big Data,
pp. 4130-4137, 2022
A Bayesian graph embedding model
for link-based classification problems
Yichao Zhang, Huangxin Zhuang,
Tiantian Liu, Bowei Chen, Zhiwei Cao, Yun Fu,
Zhijie Fan, Guanrong Chen
IEEE Transactions on Network
Science and Engineering, 9(2), pp.
716-727,
2022
Incorporating prior financial
domain knowledge into neural networks for
implied
volatility surface prediction
Yu Zheng, Yongxin Yang, Bowei
Chen
Proceedings of the 27th ACM
SIGKDD Conference on Knowledge Discovery and
Data Mining, pp. 3968-3975, 2021
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,
pp. 1242-1249, 2020
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, 281(3), pp.
532-542, 2020
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, 280(3), pp. 1144-1159,
2020
Pricing average price advertising
options when underlying spot market prices are
discontinuous
Bowei Chen, Mohan
Kankanhalli
IEEE Transactions on Knowledge
and Data Engineering, 31(9), pp.
1765-1778, 2019
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, No.4, 2017
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,
pp. 205-214, 2017
Risk-aware dynamic reserve prices
of programmatic guarantee in display
advertising
Bowei Chen
Proceedings of the 16th IEEE
International Conference on Data Mining
Workshops, pp. 511-518, 2016
A lattice framework for pricing
display advertisement options with the
stochastic volatility underlying model
Bowei Chen, Jun Wang
Electronic Commerce Research and
Applications, 14(6), pp.
465-479, 2015
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, 7(1), No. 5,
2015
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, pp. 1-9,
2014
Best Paper Award
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, pp. 1897-1906, 2014
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,
pp. 229-236, 2013
Selling futures online advertising
slots via option contracts
Jun Wang, Bowei Chen
Proceedings of the 21st
International World Wide Web Conference,
pp. 627-628, 2012
Teaching
Current Teaching
MGT5372 Data Science for
Marketing Analytics (MSc)
Adam Smith Business School,
University of Glasgow, UK
MGT5494 Text Mining for Business
(MSc)
Adam Smith Business School,
University of Glasgow, UK
