About Me

I am a final year PhD candidate focussed on developing methods and algorithms for high dimensional feature extraction and predictive analytics for medical imaging data. The current research applies these methods on brain MRI data for Parkinson’s disease patients.

I am being supervised by Dr. Mirza Faisal Beg,  and actively work with Dr. Martin McKeown on multiple projects.

My work during the M.Sc.  was supervised by Dr. Andrew Blaber.

The plethora of experience in Medical Image Analysis, Machine Learning, Biomedical and Statistical Signal Processing, Human Physiology and Electrical Engineering empower me to tackle a variety of problems with interdisciplinary solutions.

I am always on the look out to find solutions to problems with potentially wide social impact. Challenging interdisciplinary, multi-modal problems are of very high interest to me.


CURRENT RESEARCH

  • Topology Data Analysis in non-invasive medical imaging diagnostics.
  • Graph theoretic and network connectivity analysis of medical imaging data.
  • Prognostic models for early diagnosis of diseases using multi-modal MRI data.

SKILLS

  • Medical Imaging: Computational anatomy, image registration, image segmentation.
  • Biomedical Signals:Wearable devices, mobile health, Signal acquisition, Signal Processing.
  • Machine Learning: Supervised Learning (SVM, Regression methods),Unsupervised Learning (Clustering), Deep Neural Networks.
  • Graph theoretic analysis: Graph Matching, Brain graphs.
  • working in a 1000+ node cluster compute environment.
  • Scripting: MATLAB, Bash, Python.

EDUCATION

A detailed CV can be found here.

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