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University of Oxford

Mattan Pelah

Working in:

  • Computational and dynamical brain models
  • Bioelectronics and sensor systems
  • Biomechanics
  • Non-invasive brain stimulation
  • Invasive brain or spinal stimulation
  • Virtual reality
  • Data science and biomarkers

I work in the Pain and Averse Learning lab under Prof. Ben Seymour on computational models for the neurological mechanisms of tonic pain, and modulating these mechanisms via neurostimulation (primarily non-invasive, eg. TUS and TMS) for clinical use.

University of Nottingham, Division of Clinical Neuroscience, Sir Peter Mansfield Imaging Centre

Dr Duncan Hodkinson

Working in:

  • Non-invasive brain stimulation
  • Peripheral stimulation
  • Data science and biomarkers

I study the neural mechanisms that underly nociception, central sensitization, pain processing and modulation. I am also interested in understanding the signs and symptoms that accompany many clinical pain states. My approach consists of combining neuroimaging (MRI) with a range of neuromodulation techniques including non-invasive brain stimulation and peripheral stimulation. This work aims to translate research between experimental human studies and clinical science, with a view to identifying new therapeutics, medical devices, and diagnostics.

University of Oxford

Kengo Shibata

Working in:

  • Digital Health
  • Non-invasive brain stimulation
  • Invasive brain or spinal stimulation
  • Neurofeedback
  • Data science and biomarkers

Neurodegeneration and digital biomarkers

University of Glasgow

Pradeep Dheerendra

Working in:

  • Computational and dynamical brain models
  • Non-invasive brain stimulation
  • Neurofeedback
  • Data science and biomarkers

Non-invasive brain stimulation to alleviate distress in misophonia and provide relief to sufferers using TMS. Chronic Neuropathic Pain in Spinal Cord Injury

University of Liverpool

Pruthvi Mehta

Working in:

  • Computational and dynamical brain models
  • Invasive brain or spinal stimulation
  • Neurofeedback
  • Data science and biomarkers

My main interest is in neurophysics and computational neurology. I have a background (PhD) in particle physics, but am looking to pivot to neuroscience. I have used computational neurology tools such as BRIAN (used to simulate spiking neural networks), and have used Python and Tensorflow as part of my machine learning projects and PhD research. I would love to contribute in any way to chronic pain research, and it is a topic close to my heart as I suffered from chronic pain throughout my PhD and continue to do so.

University of Liveprool

Sudipta Chowdhury

Working in:

  • Computational and dynamical brain models
  • Bioelectronics and sensor systems
  • Prosthetics and robotics
  • Biomechanics
  • Pumps and infusion devices
  • Digital Health
  • Non-invasive brain stimulation
  • Invasive brain or spinal stimulation
  • Peripheral stimulation
  • Neurofeedback
  • Invasive recording systems
  • Virtual reality
  • Data science and biomarkers
  • Optogenetic systems
  • Other

Current student – I am still exploring my interests in health and med tech

University of Sheffield, Neuroscience Institute

Fiona Boissonade

Working in:

  • Animal models
  • Neurofeedback
  • Data science and biomarkers

Chronic pain, Neuropathic pain, musculoskeletal pain.
Nerve injury, nerve repair, bioengineered conduits for nerve regeneration.
EEG in human pain states.
EMG as a therapeutic tool.
Transcriptomic approaches in human pain tissues – identification of potential analgesic targets and biomakers.

AIIMS Kalyani

Titli Saha

Working in:

  • Animal models
  • Data science and biomarkers
  • Optogenetic systems
  • Other

Integrating pathways in opioid addiction and chronic pain. Molecular and Imaging biomarkers for Chronic Pain using animal models, fMRI and fNIRS study.

University of Southampton

John McBeth

Working in:

  • Bioelectronics and sensor systems
  • Digital Health
  • Data science and biomarkers

Chronic pain, Multimorbidity, Epidemiology, Health Data Science, Digital health