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<center><img  src="./images/me.jpg" style="width:324px" class="center"></center>


    <h1>Hello</h1>
    <p>I am a Principal Researcher at Microsoft Research Cambridge. My research focuses on the development of probabilistic machine learning methods for uncertainty quantification and
        data-efficient sequential decision making. I work on the challenges arising when uncertainty of different types (the loss of precision
        induced by numerical calculations, data errors, model miss-calibration, etc.) need to be be propagated, controlled and reduced in
        complex pipelines. I am also interested on how causal inference can be used to leverage decision making methods and to improve the understanding of complex
        systems and processes. As fields of application of my research I am interested in computational biology, health and environmental
        sciences.</p>
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    <h1>You may be interested on:</h1>
    <li> The <a href="https://bayesopt.github.io/special-issue.html">Special Issue in Bayesian optimization</a> that together with
        With Roberto Calandra, Frank Hutter, Bobak Bobak Shahriari and Roman Garnett we are editing for the <i>Journal of Machine Learning Research</i>.</li>
    <li> <a href="https://amzn.github.io/emukit/">Emukit</a>, a Python platform for emulation and decision making under uncertainty. Try the <a href="https://amzn.github.io/emukit-playground/#!/">Emukit-playground</a>! </li>
    <li> <a href="https://sheffieldml.github.io/GPyOpt/">GPyOpt</a>, a Python framework for Bayesian optimization.</li>
    <li> The series on <a href="http://gpss.cc"> Gaussian process summer schools</a> that I have helped to organize in Sheffield.</li>
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