Gourav Jhanwar is an Optimization Modelling Engineer with eight years of experience applying operations research, Bayesian inference, and deep learning to real-world decision problems across healthcare, agriculture, and manufacturing. Currently at Memorial Sloan Kettering Cancer Center, he builds optimization and modeling solutions that bridge advanced probabilistic methods (Gaussian processes, MCMC, polynomial chaos) with production-grade tooling in Python, AWS, and Spark. As a Purdue graduate researcher he created a first-of-its-kind visual analytics tool combining in-situ and remote sensing, biophysical models, and Bayesian decision frameworks to help growers manage water and energy—an unusual blend of field-scale sensing and rigorous uncertainty quantification. His background in mechanical engineering and hands-on manufacturing roles gives him practical expertise in SPC, Six Sigma, and predictive maintenance, enabling him to translate complex models into operational improvements. Comfortable across languages and frameworks from Python and PyTorch to Django and Spark, he focuses on turning probabilistic research into usable decision-support systems.
8 years of coding experience
1 year of employment as a software developer
High School Diploma, Maths and Physics, High School Diploma, Maths and Physics at Govindrao Junior High School, Ichalkaranji
Master's degree, Industrial Engineering and Operation research, 3.9, Master's degree, Industrial Engineering and Operation research, 3.9 at Purdue University
Bachelor of Technology - BTech, Mechanical Engineering, 8.46, Bachelor of Technology - BTech, Mechanical Engineering, 8.46 at SPCE,bhavans college,andheri(w)
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