Dr. Noorbakhsh Amiri Golilarz
Assistant Professor
Contact
- 3006 Cyber Hall
- phone (205) 348-2164
- Faculty Website
Research Areas
Education
- Postdoctoral Research Fellow, Computer Science, Boston College (BC), Massachusetts, USA, 2023
- Ph. D., Electrical and Computer Engineering, Southern Illinois University Carbondale (SIUC), Illinois, USA, 2023
- D. Eng., Computer Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China, 2021
- M.S., Electrical and Electronic Engineering, Eastern Mediterranean University (EMU), Famagusta, Cyprus, 2017
- B.S., Electrical Engineering, University of Guilan, Rasht, Iran, 2012
Noorbakhsh Amiri Golilarz is an Assistant Professor in the Department of Computer Science at The University of Alabama. Prior to joining UA, he served as an Assistant Research Professor in the Department of Computer Science and Engineering at Mississippi State University. Before that, he was a Postdoctoral Research Fellow at Boston College in Massachusetts, USA. Amiri holds two Ph.D. degrees: one in Computer Science and Technology from the University of Electronic Science and Technology of China, and another in Electrical and Computer Engineering from Southern Illinois University Carbondale, USA. His research interests include artificial intelligence, deep learning, machine learning, computer vision, pattern recognition, robotics, cognitive neuroscience, and image processing (HSI and biomedical imaging). He is the author of numerous papers in the fields of AI, computer vision, and image processing. He has served as a Lead Guest Editor and Topic Editor for several SCI-indexed journals and has also held the role of Conference Program Chair. In 2024, he co-founded AI Letters, a double-blind peer-reviewed journal, where he currently serves as the Associate Editor-in-Chief.
Affiliated Areas
Computer Science
Selected Publications
- Neupane, S., Mitra, S., Mittal, S., Gaur, M., Golilarz, N.A., Rahimi, S. and Amirlatifi, A., 2024. Medinsight: A multi-source context augmentation framework for generating patient-centric medical responses using large language models. ACM Transactions on Computing for Healthcare.
- Kumar, R., Khan, A.A., Kumar, J., Golilarz, N.A., Zhang, S., Ting, Y., Zheng, C. and Wang, W., 2021. Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging. IEEE Sensors Journal, 21(14), pp.16301-16314.
- Ali, L., Wajahat, I., Golilarz, N.A., Keshtkar, F. and Bukhari, S.A.C., 2021. LDA–GA–SVM: improved hepatocellular carcinoma prediction through dimensionality reduction and genetically optimized support vector machine. Neural Computing and Applications, 33, pp.2783-2792.
- Golilarz, N.A., Addeh, A., Gao, H., Ali, L., Roshandeh, A.M., Munir, H.M. and Khan, R.U., 2019. A new automatic method for control chart patterns recognition based on ConvNet and harris hawks meta heuristic optimization algorithm. IEEE Access, 7, pp.149398-149405.
- Addeh, A., Khormali, A. and Golilarz, N.A., 2018. Control chart pattern recognition using RBF neural network with new training algorithm and practical features. ISA Transactions, 79, pp.202-216.