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Dequn Teng (he/him) is a third-year Ph.D. candidate in Engineering at the University of Cambridge’s Institute for Manufacturing (IfM), Centre for Technology Management. His doctoral research examines human–algorithm interactions' effects on analytical creativity in algorithmic trading, funded by Cambridge Trust. His long-term research identity focuses on emerging algorithmic innovations' effects on strategic value creation, bridging insights from computer engineering, technology management, and organizational strategy. He also serves as a Research Assistant in the International Business and Strategy Group at the CJBS, where he contributes to research on regenerative innovations and strategies.

Prior to his Ph.D., Dequn completed an MPhil in Engineering (IfM, University of Cambridge) under Prof. Veronica Martinez, focusing on supply chain risk modeling with machine learning–enabled blockchain systems. He earned a first-class honors degree in Computer Science and Electrical Engineering from the University of Liverpool (2+2 routine) and further enriched his expertise as a visiting student at Stanford University.

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 CJBS. He is also the Vice President of the Cambridge Algorithmic Trading Society (CUATS), fostering interdisciplinary collaboration in algorithmic trading research and practice.

As an educator, Dequn supervise industrial engineering, strategic management, and marketing, and leads coding and analytics sessions—including Brainteaser and LeetCode sessions—within the CUATS, cultivating interactive learning experiences at the intersection of technology, strategy, and innovation.

Publications

I provide Bioinformatic support for a few research groups in the Cambridge Stem Cell Institute. For the most part I deal with the analysis of single cell sequencing data, storage management of such data and the deployment of data processing pipelines into HPC environments.

I am an Affiliated Lecturer in Architecture and the Moving Image and a researcher working with large audio-visual datasets. I specialise in developing digital methodologies and database approaches for film and media research. I am currently the main researcher of the ‘CineMuseSpace: A Cinematic Musée Imaginaire of Spatial Cultural Differences’ project (cinemusespace.com).

Additional areas of expertise:

Audio-visual data analysis, film databases, metadata ontologies.

Karla’s PhD is about the level of energy services used in different countries with a focus on development. The research involves analysing country-level databases, performing statistical analyses and making visualisations. 

Karla holds a Bachelors’ degree in Chemical Engineering from the National Autonomous University of Mexico (UNAM) and an MSc from University College London (UCL). 

Karla’s professional experiences before the PhD included working for the non-alcoholic beverage industry in Mexico in the areas of quality, environment protection and operations management.