Dr Nishant Ravikumar

Dr Nishant Ravikumar

Profile

Nishant Ravikumar is a Lecturer in AI, at the School of Computing, University of Leeds. He completed his PhD in 2017 at the University of Sheffield. Following this, he spent two years as a postdoctoral researcher at the Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Germany, before joining the University of Leeds in 2019. His past research projects have focused on developing machine learning algorithms for medical image analysis. These have included: development of shape registration and shape analysis tools for computer-aided-diagnosis (CAD); analysis of the variation in structural integrity and diffusion-related properties within the brain and its links to dementia; multi-scale and multi-modal image analysis for breast cancer detection & diagnosis; and quantification of cardiac functional indices for population-wide analyses and CAD. His current research interests are in developing algorithms that aid in the effective integration of multi-modal imaging and non-imaging data, for improved biomarker discovery, diagnosis, disease monitoring and patient prognosis.

Responsibilities

  • Lecturer in Computer Science
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://eps.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>

Qualifications

  • PhD
  • MEng. Biomedical Engineering

Research groups and institutes

  • Computational Medicine
  • Artificial Intelligence
  • Computing in Biology, Medicine and Health

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>
Projects
    <li><a href="//phd.leeds.ac.uk/project/2042-medical-vision-language-models-for-visual-question-answering">Medical Vision-Language Models for Visual Question Answering</a></li>