Dr Longzhu Shen

Contact information

Biography

I obtained my Ph.D. from Carnegie Mellon university with research focus on quantum chemistry. After graduation, I moved to Yale University as a research associate. I coupled quantum chemistry principles and machine learning algorithms to produce the first two-way design diagram to realise a complete mapping between toxicological and chemical spaces. I also developed spatial models to predict the distributions of nutrients in river streams based on machine learning algorithms. These models stand with the best performance in the field. Currently I am working at University of Cambridge to build mathematical model to predict the evolution of influenza viruses and infer preemptive vaccine design.

Research interests

My research interests reside in tackling challenging interdisciplinary problems via modelling approaches. With continuous growth of data availability and computational power, I am extremely enthusiastic at developing machine intelligence to assist human comprehension of the world complex phenomena. Built upon this advanced knowledge, we are ought to be in a better position to mange resources and create new values. In one word, I am interested in using modelling to enhance our perception, capacity and prosperity.

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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