Research Assistant
BEng (University of Liverpool), MPhil, PhD candidate (University of Cambridge)
My research identity focuses on emerging algorithmic innovations’ effects on strategic value creation, bridging insights from computer engineering, technology management and organisational strategy. As an empirical researcher, I develop full-cycle research from qualitative theory building (ethnography and field work) to quantitative theory testing (econometrics and experiments). My role as the research assistant of Professor Christopher Marquis focuses on regenerative innovation and strategies.

Professional experience
Beyond academia, Dequn has gained industry experience through roles at Deutsche Bank and Unilever, as well as through venture creation activities at the Entrepreneurship Centre at Cambridge Judge Business School. He co-founded LLMQuant and serves as Academic Collaboration Lead with initialised machine learning sessions at the Peking University Quant Trading Association. He is also the Vice President of the Cambridge Algorithmic Trading Society (CUATS), fostering interdisciplinary collaboration in algorithmic trading research and practice.
Previous appointments
Dequn is a PhD candidate in Engineering at the University of Cambridge’s Institute for Manufacturing (IfM), where he is supervised by Professor Tim Minshall at the Centre for Technology Management. His doctoral research examines human-algorithm interactions’ effects on analytical creativity in algorithmic trading, funded by the Cambridge Trust.
Publications
Selected publications
- Singh, G., Teng, D., Turki, H., Bouchard, L.F., Chen, Y., Chugh, M. et al (2024) “Changing outdated expectations.” Science, 383(6678): 24-26 (DOI: 10.1126/science.adn4211)
- Teng, D. (2024) “A loneliness cure.” Science, 384(6692): 242-242 (DOI: 10.1126/science.adp6654)
- Teng, D., Ye, C., Martinez, V. and Melfe, P. (2024) “Gen-AI’s effects on new value proposition in business model innovation: evidence from IT industry.” Academy of Management Proceedings, 2024(1): 17297 (DOI: 10.5465/AMPROC.2024.17297abstract)
- Teng, D. and Martinez, V. (2023) “Federated diversity and inclusion-focused NLP-based supply chain risk prediction system design.” Academy of Management Proceedings, 2023(1): 11312 (DOI: 10.5465/AMPROC.2023.11312abstract)
- Teng, D., Yang, T., Yue, Y., Chen, Q., Huang, X. and Dai, C. (2021) “Improve transparency and credibility of students’ educational records using school operated blockchain system.” In: International Conference on Information and Computer Technologies (ICICT) (4th), 11-14 March 2021. Virtual. Piscataway, NJ: IEEE, pp. 266-269
Awards and honours
- Best Performing Team, IfM Shoestring Hackathon, 2022
- Grand Prize Winner, KPMG Digital Future of Work Hackathon, 2022
- Elisabeth Stribling Award, Girton College, University of Cambridge, 2022