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    Nikita Sengar

    PhD Candidate at Cornell - Bayesian ML, Deep Learning, Data Science & Chemical Engineering

    Nikita Sengar is a diligent PhD candidate at Cornell University and Johns Hopkins University, specializing in Machine Learning, Applied Statistics, and Computational Chemical Engineering.

    With expertise in Bayesian Optimization, Neural Networks, Random Forests, PCA, SVM, and statistical methods like hypothesis testing and A/B testing, Nikita's skills encompass Python, Bash, SQL, and more.

    During Nikita's academic journey, they have excelled, achieving a Master of Science and now pursuing a Doctor of Philosophy in Chemical Engineering, showcasing a strong academic foundation.

    Through roles like Research Assistant at Cornell University and Materials Modeling Intern at Corning Incorporated, Nikita has honed their skills in data science and chemical engineering, preparing to make impactful contributions in these fields.

    Actively seeking industry opportunities from November 2020, Nikita aims to utilize their expertise in Data Science, Machine Learning, and Chemical Engineering to craft innovative data products with practical applications.

    Having a rich history of academic and industry experiences, including internships at prominent companies like Uber, GLOBALFOUNDRIES, and ABB, Nikita is well-versed in applying theoretical knowledge to real-world scenarios.

    Nikita Sengar
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    Location

    Ithaca, New York