Nondestructive Quality Monitoring of lab-grown organs
How do you know the organ/tissue you are growing in the lab is maturing properly and the cells are transforming towards organ-specific cells?
You can't slice the organ, then you don't have an organ for transplanting in a patient!
That's where my Ph.D. research comes in. Using Dielectric impedance spectroscopy and machine learning techniques, I am developing a method to monitor the quality of tissue-engineered medical products in real-time!
Destructive Quality Evaluation
Offline | Time consuming | Non scalable
Non-destructive Quality Evaluation
Real-time | Non-invasive | Scalable
Application of Supervised Machine Learning to Dielectric Spectroscopy for Non-destructive Quality Evaluation of Engineered Tissues. International Conference on Biofabrication, Australia, 2021
Soft-sensing with Smooth Matrix Completion of Dielectric Spectroscopy Profiles for Non-destructive Quality Monitoring During Biofabrication. IISE Virtual Conference & Expo 2021
Non-destructive quality monitoring of 3D printed tissue scaffolds via dielectric impedance spectroscopy and supervised machine learning. 49th SME North American Manufacturing Research Conference, NAMRC 49, Ohio, USA
Machine Learning for Dielectric Spectroscopy-based Quality Assessment of Engineered Tissues. IISE Virtual Conference & Expo 2021
Journal Publications & Conference Proceedings
Shohan, S., Hasan, M., Starly, B., & Shirwaiker, R. (2022), Investigating Autoregressive and Machine Learning-based Time Series Modeling with Dielectric Spectroscopy for Predicting Quality of Biofabricated Constructs. Manufacturing Letters, 33, 902–908. https://doi.org/10.1016/j.mfglet.2022.07.110
Shohanuzzaman Shohan, Yingyan Zeng, Xiaoyu Chen, Ran Jin, Rohan Shirwaiker. Investigating dielectric spectroscopy and soft sensing for nondestructive quality assessment of engineered tissues. Biosensors and Bioelectronics Volume 216, 15 November 2022, 114286
Shohanuzzaman Shohan, Mahmud Hasan, BinilStarly, Rohan Shirwaiker. Investigating Autoregressive and Machine Learning-based Time Series Modeling with Dielectric Spectroscopy for Predicting Quality of Biofabricated Constructs. 2022 Proc 50th N American Mfg. Res Conf.
Shohanuzzaman Shohan, Jordan Harm, Mahmud Hasan, BinilStarly, Rohan Shirwaiker. Non-destructive quality monitoring of 3D printed tissue scaffolds via dielectric impedance spectroscopy and supervised machine learning. 2021 Proc 49th N American Mfg. Res Conf.
S Shohan, SM Ali, G Kabir, SK K Ahmed, SA Suhi, T Haque. Green supply chain management in the chemical industry: structural framework of drivers. International Journal of Sustainable Development & World Ecology, 2019, Pages 752-768