Dr Mohammad Karimi Moridani

I completed a Bachelor's degree in Electrical Engineering-Electronics with distinction in 2006. Additionally, I obtained an MSc in Biomedical Engineering-Bioelectric in 2008. I went on to receive my PhD in Biomedical Engineering-Bioelectric in 2015. My PhD research focused on developing a novel method for predicting the mortality of cardiovascular and cerebrovascular patients admitted to the ICU. Prior to joining UNSW Australia, I served as an assistant professor in the Biomedical Engineering Department at TMSIAU, Iran.

I am interested in Biomedical Signal and Image Processing, Artificial Neural Networks (ANNs), Machine Learning, Deep Learning, Nonlinear Time-Series Analysis, and Cognitive Science. I have experience in ECG, EMG, PPG, and EEG Signal Processing in Detecting and Predicting diseases and disorders such as Epilepsy, Apnea, Parkinson, and Cardiac Diseases. Moreover, in recent years, I completed several projects on Image processing such as Pattern Recognition, Breast Cancer, Face Beauty Detection, and etc.
I have strong background to use MATLAB and Python programming languages. I am proficient in many Python environments such as Google Colab, Spider, Pytorch, IDLE, and so on. Furthermore, I could easily write MATLAB code and design various models in SIMULINK. Additionally, I am capable of designing different Deep Learning models in MATLAB and Python. 

I am passionate about harnessing the power of data analysis and machine learning in R, which allows me to explore novel approaches to problem-solving and model development. My broad experience in different programming languages and their respective environments provides me with the versatility to adapt to various research and development projects effectively.

Currently, I am employed at UNSW Australia, where I am actively engaged in research and data analysis. My ultimate goal is to leverage this acquired knowledge to enhance disease detection methods and develop advanced models for various domains, particularly in the biomedical and biological fields. I am passionate about making meaningful contributions to the scientific community and utilizing data-driven approaches to address critical challenges in healthcare and related disciplines.