Amir Dehsarvi Principal Scientist · Imaging Biomarkers
CV

Curriculum vitae

Positions, education, research coordination and technical background. A PDF version is available to download.

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Current Positions

  • 2025 to date: Principal Scientist, Imaging Biomarkers, Boehringer Ingelheim. Building end-to-end pipelines for the processing and analysis of imaging data, and the quantitative biomarkers derived from them, to support diagnosis and drug development — neuroimaging at the core, extending across organ systems including the retina and abdominal MR.

Previous Research Positions

  • 2018-2025: Chief Technology Officer, ClearSky Medical Diagnostics Ltd..
  • 2022-2025: Postdoctoral Researcher, The Institute for Stroke and Dementia Research (ISD), The Ludwig-Maximilians-University Munich Medical Center (Germany) I developed and deployed ADPREP, an automated neuroimaging pipeline that standardizes data from multiple modalities (MRI, fMRI, PET, DTI). It is now set for integration into the GRIP platform, a Gates Ventures initiative. I also created a deep learning model to infer full Alzheimer’s disease A/T/N classification from single tau-PET scans, achieving high predictive accuracy for amyloid-PET (r=0.8) and MRI grey matter density (r=0.76). In addition to my research, I managed the High-Performance Computing (HPC) resources for the lab and provided data analysis support to my colleagues while also serving as an IT assistant for the LMU Hospital.
  • 2021-2022: Research Associate, Department of Electronic Engineering at the University of York (UK) Using a proven white-box machine learning approach developed previously, in this project, we used resting brain scans from a large existing dataset (the UK Biobank) to generate new algorithms that can identify participants with depression from healthy volunteers.
  • 2020-2024: EMS Technical and Data Coordinator for Exenatide-PD3 research study, a randomised, double blind, parallel group, placebo controlled, Phase III trial of Exenatide once weekly over 2 years as a potential disease modifying treatment for Parkinson’s disease.
  • 2020-2024: EMS Technical and Data Coordinator for two different research studies in Ruijin (China).
  • 2020-2024: EMS Technical and Data Coordinator for AZA-PD research study, a randomised, double blind, placebo controlled, Phase II trial on Azathioprine immunosuppression and disease modification in Parkinson’s disease.
  • 2020-2021: Research Fellow, Aberdeen Biomedical Imaging Centre within the Institute of Medical Sciences, at the School of Medicine, Medical Sciences and Nutrition at the University of Aberdeen (UK) Supervised by Dr. Gordon Waiter, in collaboration with Professor Neil Basu. In this research project, I worked with a multidisciplinary team of clinicians and scientists on unravelling the mechanisms of chronic fatigue, a salient issue across the chronic disease spectrum in the multicentre large project of The Lessening the Impact of Fatigue Trial (LIFT). Specifically, I focused on the analysis and understanding of a multimodal MRI/fMRI brain study, using machine learning techniques (including and not limited to Evolutionary Algorithms), in order to identify potential central neurobiological correlates of rheumatoid arthritis related fatigue and to then characterise the most plausible mediators of fatigue which may be feasibly targeted in the future.
  • 2017-2020: EMS Technical and Data Coordinator for PD-STAT research study, Simvastatin as a Neuroprotective Treatment for Parkinson’s disease, a trial of 235 participants from 23 participating NHS hospitals across the UK.
  • 2019: Post-Doctoral Researcher in Neuroimaging, The Neural Engineering Group within the Trinity Centre for Bioengineering and the Trinity College Institute of Neuroscience at the University of Dublin (Ireland) Supervised by Dr. Céline de Looze and Professor Richard Reilly. In this research project, we investigated the impact cognitive impairment may have on a person’s ability to communicate and how, in turn, such cognitive and speech difficulties may affect the quality of their day-to-day interactions. This research identified speech markers and their underlying neural correlates (brain structure and functional connectivity) for the detection of cognitive impairment in MCI and AD. It also established efficient communications strategies between a person with MCI or AD and their caregivers in order to enhance the quality of their day-to-day interactions.

Education

Cartesian Genetic Programming Classification of Resting-State fMRI: Towards a Brain Imaging Biomarker for Parkinson’s Disease. Topics examined included the analysis of resting state fMRI data using Dynamic Causal Modeling and timeseries analysis. The extracted features from the analyses were then subjected to the classifiers that were developed based on Cartesian Genetic Programming, Artificial Neural Networks, and Support Vector Machines.

  • 2017: Translate: Me – Innovation Bootcamp, Translate: Medical Technologies (UK).
  • 2015: Higher Education Academy Associate Fellow Status, following completion of York Learning and Teaching Award, University of York (UK): equivalent to one third of a Postgraduate Certificate in Higher Education.
  • 2013: MSc Digital Signal Processing, University of York (UK).
  • 2010: BSc Applied Science Electronics, University of Science and Arts of Yazd (Iran).

Work experience

  • 2021: Machine Learning and Image Processing Engineer, smartR.ai, located in the Silicon Valley, smartR.ai is experienced in delivering solutions in the embedded marketspace. The company has worked on Machine Vision, Robotics, Fintech, Medical, and Consumer products for customers worldwide.
  • 2014-2018: Technical Officer, ClearSky Medical Diagnostics Ltd., a spinout company which specialises in medical devices for the diagnosis and monitoring of Parkinson’s disease, Alzheimer’s disease and a range of other neurodegenerative conditions.
  • 2016-2017: Professional Engineer, My Therapy Tools Ltd., a start-up company involved in the Horizon 2020 EU programme with the project “Acquired brain injury telerehabilitation system with high impact in patient’s wellbeing at limited cost” under SME instrument phase 1 funding scheme.
  • 2010-2012: Control Engineer, working in ‘Padideh Control Engineering’ Office. Programming and installing PLC devices.

Research Interests

Machine Learning, Deep Learning, Classification, Cartesian Genetic Programming, Evolutionary Algorithms, Neuroimaging data analysis, Mediation Analysis, and Neurodegenerative Diseases Diagnosis (Biomarkers) and Monitoring.

Technical Skills

Machine Learning, Deep Learning, Git, Neuroimaging data analysis, High Performance Computing, MATLAB, C, R, Python, Shell, PHP, SQL, AI-based medical devices.

Publications

Talks

Teaching

Service and leadership

  • 2025: Reviewer for the journal of Neural Computing and Applications
  • 2024: Reviewer for the journal of Health Science Reports
  • 2024: Reviewer for the journal of Neural Computing and Applications
  • 2024: Conference committee member of EvoApplications*, 27th European Conference on the Applications of Evolutionary and bio-inspired Computation, part of evo*2024, held in Wales (United Kingdom).
  • 2023: Conference committee member of EvoApplications*, 26th European Conference on the Applications of Evolutionary and bio-inspired Computation, part of evo*2023, held in Brno (Czech Republic).
  • 2022: Conference committee member of ICONIP 2022*, 29th International Conference on Neural Information Processing, in New Delhi (India).
  • 2022: Conference committee member of EvoApplications*, 25th European Conference on the Applications of Evolutionary and bio-inspired Computation, part of evo*2022, held in Madrid (Spain).
  • 2021: Reviewer for the journal of Frontiers in Human Neuroscience.
  • 2021: SINAPSE-IA Deputy Lead
  • 2021: Reviewer for the journal of Genetic Programming and Evolvable Machines.
  • 2021: Conference committee member of EvoApplications*, 24th European Conference on the Applications of Evolutionary and bio-inspired Computation, part of evo*2021, held virtually.
  • 2020: Conference committee member of EvoApplications*, 23rd European Conference on the Applications of Evolutionary and bio-inspired Computation, part of evo*2020, held virtually.
  • 2020: Conference committee member of The 10th International Conference on Soft Computing for Problem Solving (SocProS 2020), held in Indore (India).
  • 2017-2019: Association for Computing Machinery member.
  • 2014-2018: IEEE student member.
  • 2016: Conference committee member of The International Conference for Students on Applied Engineering (ICSAE 2016) held in Newcastle upon Tyne (UK).
  • 2016: Conference Chair of The 31st Annual Psychology Postgraduate Affairs Group Conference held in York (UK).
  • 2016: Conference committee member of York Doctoral Symposium
  • 2014-2016: Postgraduate Representative at The Department of Electronic Engineering, University of York (UK).