Data Champions Search

Abdulwahab is a PhD student in Physical Activity Epidemiology, advised by Dr. Soren Brage at the MRC Epidemiology Unit, University of Cambridge. He is a recipient of the Kuwaiti High Science Achiever PhD Scholarship by the Kuwait Foundation for the Advancement of Sciences and the Kuwait Chamber of Commerce and Industry and was previously awarded a full Bachelor's and Master's Scholarship from the Kuwait Ministry of Higher Education. His interests lie in the analysis of accelerometer-measured physical activity data in different populations and related disease endpoints. He previously studied adolescent physical activity behavior in relation to mental well-being. His current research interest is in the analysis of physical activity behavior in the Arabian Gulf in relation to metabolic disease incidence.

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 bioinformatician who has been working in Cancer Research UK Cambridge Institute since 2017. I have a background in biology and have experience with HPC, version control, R and python, and confidential data. I work with big volumes of cancer patient data on a daily basis.

Additional areas of expertise:

High Performance Computing (HPC) - cluster.

I am a Research Associate at the University of Cambridge, UK. I am also a Postdoctoral Affiliate of Trinity College, Cambridge. I am currently working on several exciting research problems concerning codon usage, optimality and, in general, knowledge discovery from large-scale genomic data. I am focusing on developing novel ML approaches, such as Neuro-Symbolic Models and Deep Neural Networks, to learn from genomic sequences. For more details, please visit my homepage, which is usually updated often: https://tirtharajdash.github.io/