About this community

The mission of the School of Technology is to provide a focus and framework for its constituent departments to formulate and express views pertinent to technology, methods and processes, both within and without the University, recognising that technology has its own priorities and its own criteria for success: above all, technology departments recognise a duty to influence and be influenced by society at large and to work towards the creation of wealth and an improved quality of life. Institutions within the School are: the Department of Chemical Engineering and Biotechnology, the Computer Laboratory, the Department of Engineering, Judge Business School and the Cambridge Institute for Sustainability Leadership.

Find out more about the School of Technology at http://www.tech.cam.ac.uk/.

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Recent Submissions

  • Ownership, institutions and firm value: cross-provincial evidence from China 

    Wang, Boya (Elsevier, 2017-07-17)
    The distinctive political-economic setups of emerging economies engender special corporate governance issues that warrant added attention to the broader institutional environments. Using a unique provincial firm-level ...
  • Bioprinting of three-dimensional culture models and organ-on-a-chip systems 

    Huang, Yanyan; Zhang, D; Liu, Y (Materials Research Society, 2017-08-10)
    Multimaterial bioprinting technologies offer promising avenues to create mini-organ models with enhanced tissue heterogeneity and complexity. This article focuses on the application of three-dimensional bioprinting to ...
  • Unfolding and Shrinking Neural Machine Translation Ensembles 

    Stahlberg, Felix; Byrne, William Joseph (Association for Computational Linguistics, 2017-09-09)
    Ensembling is a well-known technique in neural machine translation (NMT) to improve system performance. Instead of a single neural net, multiple neural nets with the same topology are trained separately, and the decoder ...
  • SGNMT -- A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies 

    Stahlberg, Felix; Hasler, E; Saunders, Danielle; Byrne, William Joseph (Association for Computational Linguistics, 2017-09-09)
    This paper introduces SGNMT, our experimental platform for machine translation research. SGNMT provides a generic interface to neural and symbolic scoring modules (predictors) with left-to-right semantic such as translation ...

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