Meena Raju
Mississippi State University, Hindustan Aeronautics Limited (India), VIT University School of Mechanical Engineering, VIT University-School of Mechanical and Building Sciences, University of Madras
About
I have spent about 3+ years since 2019 in quantitative data research involving data analytics, statistical, and number crunching methods for addressing climate variability, change and natural resources management. My expertise in mathematics and statistics has helped to devise methodologies in quantitative research. I have expertise in working with various statistical and data management systems and tools such as R, Python, statistical significance, time series, descriptive, forecasting analysis, hypothesis testing, and data-driven optimization problems. I have hands on experience for over 3years on spatial analysis and mapping using GIS(version control). Technical understanding on stochastic and water quality modeling including HEC-RAS, QUAL-2K,LAKE 2K, WASP and EFDC, calibration and validation metrics, sensitivity and uncertainty analysis.
My decade over experience in industry on environment management(pollution abatement on air, water and solid waste management), sustainability development and and two years experience in academics has molded to be an effective observer, problem identifier and solver on various instances.
I am comfortable working on datasets independently as well as in team environment. I have strong communication skills with clear presentation and am passionate to creative writing.
Employment
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Mississippi State University Graduate Research Assistant2019 - 2022
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Hindustan Aeronautics Limited (India) Engineer-Manager2007 - 2018
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VIT University-School of Mechanical and Building Sciences Lecturer2005 - 2007
Education
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Mississippi State University PhD2019 - 2022
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VIT University School of Mechanical Engineering Masters2003 - 2005
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University of Madras Bachelor of Engineering1999 - 2003
Projects & Funding
Projects & funding information is unavailable.
Publications (4)
- Quantifying model output uncertainty from sparse input data: a case study in the Mississippi sound and mobile bay Save
- Sensitivity analysis of a hydrodynamic and harmful algal model in a riverine system Save
- Seasonal Salinity Trends in Central and Southern Biscayne Bay, Florida Save
- Development of Water Quality Time Series Inputs for Hydrodynamic Modeling Based on Sparse Data Save