Ranjan Srivastava
Professor
Department of Chemical & Biomolecular Engineering
Ph.D. University of Maryland, College Park (1999)
Current Research
- Systems Biology
- Computational Material Design
- Evolutionary Algorithms
- Applied Machine Learning
Professional Activities
Joint Faculty Member: Biomedical Engineering Department, UConn, 2002 – Present
Joint Faculty Member: Multidisciplinary Head & Neck Cancer Program, The Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut Health Center, 2008 – Present
Affiliated Faculty: Environmental Engineering Program, UConn, 2006 – Present
Member: American Chemical Society
Member: American Institute of Chemical Engineers
Member: Society of Biological Engineering
Chair: American Chemical Society Biochemical Technology Division, 2018
Joint Faculty Member: Multidisciplinary Head & Neck Cancer Program, The Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut Health Center, 2008 – Present
Affiliated Faculty: Environmental Engineering Program, UConn, 2006 – Present
Member: American Chemical Society
Member: American Institute of Chemical Engineers
Member: Society of Biological Engineering
Chair: American Chemical Society Biochemical Technology Division, 2018
Current Research Group
| Graduate Students | Undergraduate Students |
| Nicole Beauregard Christine Endicott Stephen Lincoln Maryam Pardakhti Rebecca Rubinstein Ian Rogers |
Ryan Padden |
Research Statement
Our research group is interested in all aspects of evolutionary dynamics and its applications. We focus on applying evolutionary dynamics to solve problems in science and engineering, primarily addressing problems systems biology and metabolic engineering. However, we also have a strong interest in understanding the principles underlying evolutionary dynamics. We have applied evolutionary principles to a wide range of problems through algorithm development and experimental studies. Examples of problems we have addressed in the biological arena include evolving new mathematical models of biological systems, curating existing models at the genome scale with evolutionary algorithms, and optimizing bioprocessing strategies. We have also applied these approaches to other disciplines, such as materials science and environmental engineering. To carry out our work, we employ experimental and theoretical tools from chemical engineering, molecular biology, applied mathematics, machine learning, and systems optimization.
Previous Positions
| 2013 – 2016 | Biomolecular Engineering Program Director, Department of Chemical, Materials, & Biomolecular Engineering, University of Connecticut |
| 2011 – 2013 | Chemical Engineering Program Director, Department of Chemical & Biomolecular Engineering, University of Connecticut |
| 2008 – 2016 | Associate Professor of Chemical, Material, Biomolecular Engineering, University of Connecticut |
| 2002 – 2008 | Facility Head, Fermentation & Bioprocessing Facility, University of Connecticut |
| 2002 – 2008 | Assistant Professor of Chemical Engineering, University of Connecticut |
Select Honors & Awards
| 2018 | Elected Member of the Connecticut Academy of Science & Engineering |
| 2017 | Inaugural Recipient of the University of Connecticut Family Support Award |
| 2014 | Visiting Professor of Biostatistics, Yale University |
| 2013 | Inaugural Recipient of the University of Connecticut School of Engineering Outstanding Faculty Mentoring Award |
| 2009 | Award for Teaching Excellence as Determined by the Students |
| 2007 | Office of Naval Research/American Society of Engineering Education Fellow |
| 2004 | University of Connecticut Junior Faculty Fellow |
| 2004 | Rogers Corporation Outstanding Teaching Award |
| 2000 | NIH Post-Doctoral Trainee in Cancer Biology |
Recent Publications
Pardakhti M, Jafari T, Tobin Z, Dutta B, Moharreri E, Shemshaki N, Suib S, Srivastava R. (2019) Trends in Solid Adsorbent Materials Development for CO2 Capture. ACS Applied Materials & Interfaces. https://doi.org/10.1021/acsami.9b08487
Moharreri E*, Pardakhti M*, Srivastava R**, Suib S.** (2019) Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach. ACS Combinatorial Science. https://doi.org/10.1021/acscombsci.9b00028
*Contributed equally
** Co-Corresponding Authors
Ribeiro L, Chelius C, Boppidi K, Naik N, Hossain S, Ramsey J, Kumar J, Ribeiro L, Ostermeir M, Tran B, Young A, de Assis L, Ulas M, Bayram O, Goldman G, Lincoln S, Srivastava R, Harris S, Marten M. (2019) Comprehensive analysis of Aspergillus nidulans PKA phosphorylome identifies a novel mode of CreA regulation. mBio. https://doi.org/10.1128/mBio.02825-18
Chelius C, Ribeiro L, Huso W, Kumar J, Lincoln S, Tran B, Goo Y, Srivastava R, Harris S, Marten M. (2019) Phosphoproteomic and transcriptomic analyses reveal multiple functions for Aspergillus nidulans MpkA independent of cell wall stress. Fungal Genetics and Biology. https://doi.org/10.1016/j.fgb.2019.01.003
Gao T, Wang Y, Zhang C, Pittman ZA, Oliveira A, Fu K, Zhao J, Srivastava R, Willis B. (2019) Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays. Sensors. https://doi.org/10.3390/s19112547
Rogers I, Srivastava R. (2018) Using ensemble modeling to determine causes of multifactorial disorders. Proceedings of the Genetic and Evolutionary Computation Conference Companion. https://doi.org/10.1145/3205651.3205686
Benjamino J, Lincoln S, Srivastava R, Graf J. (2018) Low-abundant bacteria drive compositional changes in the gut microbiota after dietary alteration. Microbiome. https://doi.org/10.1186/s40168-018-0469-5
Boppidi K, Ribeiro L, Iambamrung S, Nelson S, Wang Y, Momany M, Richardson E, Lincoln S, Srivastava R, Harris S, Marten M. (2018) Altered secretion patterns and cell wall organization caused by loss of PodB function in the filamentous fungus Aspergillus nidulans. Scientific Reports. https://doi.org/10.1038/s41598-018-29615-z
Pardakhti M, Moharreri E, Wanik D, Suib S, Srivastava R. (2017) Machine learning using combined structural and chemical descriptors for prediction of methane adsorption performance of metal organic frameworks (MOFs). ACS Combinatorial Science. https://doi.org/10.1021/acscombsci.7b00056
Gao T, Wang Y, Zhang C, Pittman ZA, Oliveira A, Fu K, Zhao J, Srivastava R, Willis B. (2019) Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays. Sensors. https://doi.org/10.3390/s19112547
Rogers I, Srivastava R. (2018) Using ensemble modeling to determine causes of multifactorial disorders. Proceedings of the Genetic and Evolutionary Computation Conference Companion. https://doi.org/10.1145/3205651.3205686
Benjamino J, Lincoln S, Srivastava R, Graf J. (2018) Low-abundant bacteria drive compositional changes in the gut microbiota after dietary alteration. Microbiome. https://doi.org/10.1186/s40168-018-0469-5
Boppidi K, Ribeiro L, Iambamrung S, Nelson S, Wang Y, Momany M, Richardson E, Lincoln S, Srivastava R, Harris S, Marten M. (2018) Altered secretion patterns and cell wall organization caused by loss of PodB function in the filamentous fungus Aspergillus nidulans. Scientific Reports. https://doi.org/10.1038/s41598-018-29615-z
Pardakhti M, Moharreri E, Wanik D, Suib S, Srivastava R. (2017) Machine learning using combined structural and chemical descriptors for prediction of methane adsorption performance of metal organic frameworks (MOFs). ACS Combinatorial Science. https://doi.org/10.1021/acscombsci.7b00056
| rs@uconn.edu | |
| Phone | (860) 486-4020 |
| Mailing Address | 191 Auditorium Road, Unit 3222, Storrs, CT 06269-3222 |
| Office Location | EII-204 |
| Link | https://www.rslabs.org |