Dr. Akhbardeh is Professor and Director of the UTHealthSonix Ultrasound Center at McGovern Medical School, The University of Texas Health Science Center at Houston (UTHealth Houston) and he is also a Professor at the Graduate School of Biomedical Sciences (GSBS), Medical Physics and Quantitative Sciences programs at The University of Texas MD Anderson Cancer Center. He has over 25 years of experience in both academia and industry and has achieved international recognition in the development of novel medical devices, and innovative new methods for many different projects and applications. 

He has focused on various aspects of medical imaging and spectroscopy (Ultrasound, MRI, PET/CT, Optical), biosensing and wearables (ECG, EEG, EMG, BCG, Pulse Ox), algorithm development using machine learning and AI, computer vision, signal and image processing methods for many different industrial and medical applications. He has BSc and MSc degrees in electrical and biomedical engineering and a PhD in AI for biomedical applications. He also completed two different fellowships in biomedical engineering and radiology. He has worked as Tenure -Track Faculty at Johns Hopkins University School of Medicine and visiting faculty at Stanford School of Medicine, and with several other adjunct faculty appointments in ECE and BME in the past. 

He led and managed algorithm and data science teams in multiple companies with the focus on developing advanced machine learning, computer vision, signal and image processing algorithms as well as data mining, data dashboard and analytics platform for different industrial, medical and digital health applications. He has directed, as PI and Co-Investigator, on numerous research projects funded by federal grants and has extensively published over 120 proceedings, journal papers, and book chapters. He has also patented several systems and methods for industrial and medical applications, granted over 16 awarded and pending patents. He has also served as editor and reviewer for several peer-reviewed journals and conferences. He has extensive entrepreneurial experience with several SBIR grants and startups.

Education & Training

Areas of Interest:

Dr. Akhbardeh's primary research interests include the development of medical devices, spanning from conceptualization to product development. He specializes in creating innovative systems that leverage advanced signal and image processing techniques, artificial intelligence (AI) and machine learning algorithms, bioinformatics, and radiological methods. His work is dedicated to advancing diagnostic accuracy, prognostic capabilities, and the monitoring of treatment effectiveness across a wide spectrum of diseases. With a multifaceted background and extensive training in engineering (ECE/BME), medical imaging, computer science, and device development, Dr. Akhbardeh brings a diverse skill set to his research endeavors.

Selected Publications:

https://med.uth.edu/radiology/2022/11/03/alireza-akhbardeh-phd/