Dr Jajati Mandal
School of Science, Engineering & Environment
Current positions
University Fellow
Biography
I am an environmental soil chemist, studying the behavior and impacts of environmental contaminants like metal(loid)s, PFAS, and tyre-rubber chemicals in agricultural systems and the environment. Currently, I am serving as a University Fellow/Lecturer at the University of Salford. I was a visiting researcher at CSIRO Australia. I am well-versed in analytical and speciation techniques for metals and metalloids in various environmental samples such as water, soil, and plants. Additionally, I have expertise in developing predictive models using machine learning algorithms coded in R. Further I have developed R packages such as 'Inquilab,' and 'AdsorpR' to model adsorption kinetics and adsorption.
Areas of Research
- Research interest: Study of environmental contaminants such as metal(loid)s, PFAS, and tire rubber chemicals within agricultural systems and their broader ecological impact.
- Analytical skills: Analytical and speciation techniques for metals and metalloids in various environmental samples, including water, soil, and plants.
- Predictive modeling: Interested in developing models using ML algorithms such as logistic regression, random forest and gradient boost machine
- Integration: Research approach combines laboratory experiments and field studies to gain a holistic understanding of the interactions between contaminants and ecosystems.
Qualifications
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PhD
2020 - 2023 -
Agricultural Chemistry and Soil Science
2008 - 2010 -
Agriculture
2004 - 2008
Recognitions
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ICAR-Netaji Subhas International Fellowship
Publications
- Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice : introducing machine learning-based prediction models from field data
- Complexation, retention and release pattern of arsenic from humic/fulvic acid extracted from zinc and iron enriched vermicompost
- Determination of bioavailable arsenic threshold and validation of modeled permissible total arsenic in paddy soil using machine learning
- Replacing conventional surface irrigation with micro-irrigation in vegetables can alleviate arsenic toxicity and improve water productivity
- Meta-analysis enables prediction of the maximum permissible arsenic concentration in Asian paddy soil