Abhishek S. Dhoble, Ph.D.
Affiliations: | 2004-2008 | Chemical Engineering | LIT Nagpur |
2008-2009 | Biological Engineering | University of Florida, Gainesville, Gainesville, FL, United States | |
2012-2016 | Biological Engineering | University of Illinois, Urbana-Champaign, Urbana-Champaign, IL | |
2016-2019 | PostDoc | NSF/USDA EAGER at UIUC | |
2019-2021 | Assistant Professor Chemical Engineering | BITS Pilani | |
2021- | Assistant Professor Biochemical Engineering | Indian Institute of Technology (BHU) |
Area:
Microbiome; Anaerobic Digestion; Flow Cytometry; Machine Learning; Microbial Population Dynamics; Microbiome CharacterizationWebsite:
https://iitbhu.ac.in/dept/bce/people/asdhoblebceGoogle:
"Abhishek Dhoble BCE IIT BHU"Bio:
Children
Sign in to add traineeBabuji Dandigunta | grad student | 2018-2020 | Birla Institute of Technology and Science, Pilani (BITS Pilani) |
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Publications
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Priyadarsini M, Kushwaha J, Pandey KP, et al. (2023) Application of flow cytometry for rapid, high-throughput, multiparametric analysis of environmental microbiomes. Journal of Microbiological Methods. 214: 106841 |
Dhoble AS, Ryan KT, Lahiri P, et al. (2019) Cytometric fingerprinting and machine learning (CFML): A novel label-free, objective method for routine mastitis screening Computers and Electronics in Agriculture. 161: 505-513 |
Dhoble AS, Lahiri P, Bhalerao KD. (2018) Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes. Journal of Biological Engineering. 12: 19 |
Dhoble AS, Lahiri P, Bhalerao KD. (2018) Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes Journal of Biological Engineering. 12: 19 |
Dhoble AS, Lahiri P, Bhalerao KD. (2018) Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes Journal of Biological Engineering. 12: 19 |
Dhoble AS, Bekal S, Dolatowski W, et al. (2016) A novel high-throughput multi-parameter flow cytometry based method for monitoring and rapid characterization of microbiome dynamics in anaerobic systems. Bioresource Technology. 220: 566-571 |