C. (Charles) Wan MSc

Charles Wan
Rotterdam School of Management (RSM)
Erasmus University Rotterdam
ERIM PhD Candidate
Field: Logistics & Information Systems
Affiliated since 2019

Charles is broadly interested in how humans make decisions against a certain causal structure or representation of the world.  Recently, the adoption of statistical learning algorithms has introduced a novel causal context for studying the human learning-cum-decision-making process.  Charles' research explores how statistical learning algorithms interact with human agency, human causal reasoning, organizational information-processing, and organizational decision-making. 

Previously Charles worked as a commodities trader in Europe, the US, and Asia. 

For more information please visit https://wan-charles.github.io/

PhD Track Ph.D. Research in Business Analytics in Information Systems

We are living in a highly connected world that is filled with digital technologies, social media, mobile devices, Internet-of-Things, smart cities, and connected cars. Growth of the information technologies has created new opportunities across different industries as companies innovate to meet changes in consumer demand, and has given rise to new challenges. In our Ph.D. program in Information Systems, you will be trained to conduct innovative research to address increasingly complex challenges facing digital society. Our faculty is working on a variety of projects in this area ranging from digital platforms, mobile advertising, recommendation and personalization, social networks, online piracy and privacy, and the role of AI.

We are seeking highly motivated students with demonstrated academic ability, those who possess a commitment to interdisciplinary research on significant information technology and management issues, and those who desire to pursue an academic research career in this field. You will be part of the Business Information Management (BIM) section within the Department of Technology & Operations Management at the Rotterdam School of Management, Erasmus University.

Applicants must have strong quantitative training, with preference given to candidates who have earned an MSc, MPhil or Research Master in economics, computer science, econometrics, statistics, or a related field. Successful candidates have proficiency with R, SQL, Python, or other programming languages.

As a Ph.D. student, you will gain the training and experience necessary to conduct independent research through course work in information systems, economics, econometrics, machine learning, and large-scale data analytics. You will work closely with the advisors to define, develop, and execute your own research. The Ph.D. dissertation will be defined by the student with inputs from the advisors, and thus requires creativity, self-direction, and a passion for scientific inquiry.

Artificial intelligence, business analytics, information strategy, digital innovation, digital platforms, economics of information systems
Time frame
2019 -


  • Academic (4)
    • Wan, C., Belo, R., Zejnilović, L., & Lavado, S. (2023). The Duet of Representations and How Explanations Exacerbate It. In L. Longo (Ed.), Explainable Artificial Intelligence - 1st World Conference, xAI 2023, Proceedings: First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part II (1 ed., pp. 181-197). Springer Cham. https://doi.org/10.1007/978-3-031-44067-0_10

    • Wan, C. (2023). Timescales, Levels of Organization, and Multi-objective Agents. In ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference https://doi.org/10.1162/isal_a_00562

    • Wan, C., Zejnilović, L., & Lavado, S. (2023). How Differential Robustness Creates Disparate Impact: A European Case Study. In CEUR Workshop Proceedings (Vol. 3442) https://ceur-ws.org/Vol-3442/paper-22.pdf

    • Wan, C., Crisostomo Pereira Belo, R., & Zejnilović, L. (2022). Explainability's Gain is Optimality's Loss? — How Explanations Bias Decision-making. In AIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (pp. 778-787). Association for Computing Machinery. https://doi.org/10.1145/3514094.3534156


Visiting address

Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam