Data Champions Search

Ali is Senior Data Scientist and public-health/transport modeller in the Public Health Modelling (PHM) group at the MRC-Epidemiology Unit, University of Cambridge. He is interested in active travel, specifically cycling research. 

Coming from a Computer Science background, with a focus on modelling in his PhD, for over a decade, he has been doing data-driven research and development. This includes Exploratory Data Analysis (EDA), Statistical Modelling (or Machine Learning), Interactive Visualization, all with a focus on collaborative, transparent and reproducible research. In addition, he leads in project management and managing, training, guiding, and teaching of junior staff in his Unit. His work can be seen on GitHub at https://github.com/usr110.

I am a part-time PhD student and part-time veterinarian. My research is about the genetics of obesity in dogs, which is also relevant to human genetics genetic and physiological similarities, and shared environmental factors. I am particularly interested in bringing better data management standards to the veterinary field, specially in clinical research.

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 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.