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Dr. Madjid Soltani

Faculty

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Qualification:

Ph.D. in Chemical Engineering – Nanotechnology, University of Waterloo

M.Sc. in Mechanical Engineering, Sharif University of Technology

Teaching & Scholarly Interests:

Management of Technology, Applications of Emerging Technologies, Artificial Intelligence, Medical Technologies, Renewable and Sustainable Energies, Multi Scale System Modelling

Biography:

Madjid Soltani completed his PhD in the University of Waterloo, Waterloo Institute for Nanotechnology and his postdoctoral studies in the University of Johns Hopkins, School of Medicine. Dr. Soltani has published widely with high impact journals across engineering, science and technology disciplines. Dr Soltani has been awarded the University of Waterloo’s 2013 Outstanding Achievement in Graduate Studies Honours. He is currently a Senior Research Fellow with Waterloo Institute for Sustainable Energy.

Publications:

  • Artificial Intelligence and Machine Learning Applications in Vaccine Development, A Sarmadi, M Hassanzadeganroudsari, M Soltani, Bioinformatics Tools for Pharmaceutical Drug Product Development, 233-253
  • Deep Learning for Modelling an Offshore Hybrid Wind–Wave Energy System, M Dehghan Manshadi, M Mousavi, M Soltani, A Mosavi, L Kovacs, Energies 15 (24), 9484
  • Recent Advances of Utilizing Artificial Intelligence in Lab on a Chip for Diagnosis and Treatment, S Zare Harofte, M Soltani, S Siavashy, K Raahemifar, Small 18 (42), 2203169
  • Modelling the efficacy of different anti-angiogenic drugs on treatment of solid tumours using 3D computational modelling and machine learning, M Mousavi, MD Manshadi, M Soltani, FM Kashkooli, A Rahmim, A Mosavi, Computers in biology and medicine 146, 105511
  • Synthetic 18f-FDG PET image generation using a combination of biomathematical modelling and machine learning, MA Abazari, M Soltani, F Moradi Kashkooli, K Raahemifar, Cancers 14 (11), 2786
  • A novel numerical and artificial intelligence-based approach to study anti-angiogenic drugs: Endostatin, MA Ghazani, M Soltani, P Jalali, R Hassannejad, Applied Mathematical Modelling 105, 258-283
  • Deep neural networks for neuro-oncology: Towards patient individualized design of chemo-radiation therapy for Glioblastoma patients, A Ebrahimi Zade, S Shahabi Haghighi, M Soltani
  • Deep neural networks for neuro-oncology: Towards patient individualized design of chemo-radiation therapy for Glioblastoma patients, AE Zade, SS Haghighi, M Soltani
  • Journal of Biomedical Informatics 127, 104006
  • Energy simulation of residential house integrated with novel IoT windows and occupant behaviour, H Fekri, M Soltani, M Hosseinpour, W Alharbi, K Raahemifar, Sustainable Cities and Society 78, 103594
  • Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology, A Rahmim, J Brosch-Lenz, A Fele-Paranj, F Yousefirizi, M Soltani, C Uribe, Frontiers in Oncology 12
  • Optimization and energy assessment of geothermal heat exchangers for different circulating fluids, M Soltani, P Farzanehkhameneh, FM Kashkooli, A Al-Haq, J Nathwani, Energy Conversion and Management 228, 113733
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