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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

Elizabeth has an MPhil in HPS from Cambridge and has worked for the Newton Project Canada. She has worked for the Darwin Correspondence Project for more than fifteen years, and assisted in the conversion of the Project's core files to TEI XML, and is now developing and implementing strategies to ensure the quality, robustness, interoperability, and long-term viability of our electronic data. She is a co-founder of Epsilon, a nineteenth century science letters platform and has been a guest lecturer at the Digital Humanities at Oxford Summer School.

After completing my undergraduate degree in psychology, I spent several years working within the NHS and the charity sector, before moving into clinical research (Department of Oncology) in 2011. During this tenure I worked as a research assistant and latterly senior data manager, working across a variety of research and clinical systems (including OpenClinica, Achiever Medical and EDGE), gaining valuable experience in data approaches to research and governance. During this time I also completed a MSc in Psychological Research Methods. My knowledge and understanding of NHS systems was furthered during a secondment to the eHospital team, which facilitated the transition of Cambridge University NHS Foundation Trust to a fully electronic medical health record system (EPIC), the first of its kind in the UK.
   
   I joined the Department of Clinical Neurosciences in 2020, bringing a wealth of experience in the collection and management of clinical data from my time in Oncology. I currently work with the clinical and laboratory teams and external stakeholders to design, create and deliver streamlined methods for the prospective collection of high quality clinical and sample data.

I am a postdoctoral research associate in the Chemical Engineering and Biotechnology Department focusing on automation of laboratory biological research using a combination of AI, informatics, lab robotics, and software engineering. I have previously worked on metabolomic systems biology with mass spectrometry analysis. Currently, my interests are especially focused on the intersection of knowledge representation, generative AI, and symbolic methods for automating scientific discovery.