Vahab Khoshdel, P.Eng.

Area

My research lies at the interface of machine learning, deep learning, computer vision, medical imaging and robotics. In the past, I have designed machine learning techniques for a variety of applications, including rehabilitation robotics, microwave and ultrasound imaging, stored grain monitoring, and precision agriculture.

Expertise

Generative AI, Machine Learning, Deep Learning, Computer Vision, Robotics, Medical Robots, Medical Imaging.

Vahab Khoshdel was born in Mashhad (Iran) in 1989. He received his bachelor's and master's degrees in computer engineering from Shahrud University in Iran; he obtained his first Ph.D. in robotics from Ferdowsi University of Mashhad, Iran. He has received his second Ph.D. in Biomedical Engineering from the University of Manitoba. Vahab has worked in the computer industry for several years, where he directed research teams involved in computer vision, machine learning, and AI. Vahab is currently an Assistant Professor in the department of Electrical and Computer Engineering at the University of Manitoba.

V. Khoshdel, A. Ashraf, M. Asefi, J. LoVetri, “A Multi-Branch Deep Convolutional Fusion Architecture for 3D Microwave Inverse Scattering: Stored Grain Application”, Neural Computing and Applications, (2021)

P. Mojabi, M. Hugson, V. Khoshdel, I. Jeffrey, J. LoVetri, “CNN for Compressibility to Permittivity Mapping for Combined Ultrasound-Microwave Breast Imaging”, IEEE Journal on Multiscale and Multiphysics Computational Techniques, (2021)

K. Edwards, V. Khoshdel, M. Asefi, J. LoVetri, C. Gilmore, I. Jeffrey, “A Machine Learning Workflow for Tumour Detection in Breasts Using 3D Microwave Imaging”, Electronics, (2021)

V. Khoshdel, A. Ashraf, M. Asefi, J. LoVetri, “Full 3D Microwave Breast Imaging Using a Deep-Learning Technique”, Journal of Imaging, (2020)

P. Mojabi, V. Khoshdel and J. LoVetri, "Tissue-Type Classification with Uncertainty Quantification of Microwave and Ultrasound Breast Imaging: A Deep Learning Approach," IEEE Access, (2020)

K. Edwards, K. Krakalovich, R. Kruk, V. Khoshdel, J. LoVetri, C. Gilmore, I. Jeffrey, “The implementation of neural networks for phaseless parametric inversion”, Symposium of the International Union of Radio Science, IEEE, (2020)

V. Khoshdel, A. Ashraf, J. LoVetri, “Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique”, Sensors, Volume 19, Issue 18, (2019)

V. Khoshdel, A. Ashraf, J. LoVetri, “Using a Deep-Learning Technique for Microwave-Ultrasound Breast Imaging”, PIERS, Rome, Italy, (2019)

V. Khoshdel, A. Akbarzadeh, "An optimized artificial neural network for human-force estimation: consequences for rehabilitation robotics", Industrial Robot: the international journal of robotics research and application, (2018)

V. Khoshdel, A. Akbarzadeh Tootoonchi, N. Nagavi, A. Sharifnzhad “sEMG-based impedance control for lowerlimb rehabilitation robot”, Intelligent Service Robotics, Volume 4, Issue 1, (2017)

Khanjani, V. Khoshdel, A. Akbarzadeh Tootoonchi, “Estimate Human-Force from sEMG signals for a Lower-Limb Rehabilitation Robot”, 25th Iranian Conference on Electrical Engineering (ICEE2017), (2017)

V. Khoshdel, A. Akbarzadeh Tootoonchi, “Application of statistical techniques and artificial neural network to estimate force from sEMG signals”, Journal of AI and data mining, Volume 4, Issue 2, (2016)

V. Khoshdel, A. Akbarzadeh, H. Moeenfard “Variable Impedance Control for Rehabilitation Robot using Interval Type-2 Fuzzy Logic”, International Journal of Robotics, Volume 4, Issue3, P 46-5, (2016)

V. Khoshdel, A. Akbarzadeh, H. Moeenfard “Robust Impedance Control of a Lower-Limb Rehabilitation Robot Using Fuzzy Parameters”, Journal of Solid and Fluid Mechanics, Volume 5, issue 4, P 83-95, (2015)

M.M. Fateh, V. Khoshdel “Voltage-based adaptive impedance force control for a lower-limb rehabilitation robot”, Advanced Robotics, Volume 29, Issue 15, Page 961-971, (2015)

M.M. Fateh, V.Khoshdel “Robust Impedance Control for a Rehabilitation Robot Using Voltage Strategy”, Modares Mechanical Engineering, Volume 15, Issue 8 , (2015)