Rutvij Kulkarni

Rutvij Kulkarni

Summer Intern

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  • Timeline

  • About me

    Scientific software developer @ Materials nexus | Imperial College London | BITS Pilani Hyderabad Campus

  • Education

    • BITS Pilani, Hyderabad Campus

      2017 - 2021
      Bachelor of Engineering - BE Mechanical Engineering
    • Imperial College London

      2022 - 2023
      Master of Science - MS Computational and Applied Mathematics

      Modules Undertaken- Modern Programming methods- Computational Mathematics- Data science and Machine learning- Deep Learning - Modelling and Numerical methods- Inversion and Optimisation- Advanced programming with C++- Patterns in Parallel programming

  • Experience

    • TATA AutoComp Systems Ltd

      May 2019 - Jul 2019
      Summer Intern

      Worked in the quality control department. Performed detailed analysis on the occurrence of cracks in automobile parts manufactured using Sheet Molding Composite (SMC)

    • Arizona State University

      Jun 2020 - Sept 2020
      Summer Research Intern

      Performed a review on commercial viability of all solid state lithium anode batteries. The review was presented to a panel of academics at Arizona State University.The aim of this project was to review key advances in literature in the following sub-topics1) The relationship between ionic conductivity, chemical and thermal stability of various types of solid electrolytes (garnet, sulfide, argyrodite) with their crystal structure2) The problems the electrolytes face in battery systems (dendrite short circuits, capacity loss, increase in interfacial resistance on extended cycling)3) Identify key themes for future research through critical analysis of literature with the objective of providing a possible solution to the above mentioned problems. Show less

    • Indian Institute of Science (IISc)

      Jan 2021 - Jul 2022
      Project Associate

      As a project associate, my responsibilities included leading the development of of a machine learning (ML) model for performing molecular simulations in the LiPON solid electrolyte system, and coordinating with my supervisor for enforcing domain specific requirements on the ML model. We identified and generated key data points using Ab-Initio Molecular dynamics simulations, and used these to train and analyse different ML models and architecture performance.

    • Matnex

      Oct 2023 - now
      • Scientific software developer

        Jun 2024 - now
      • Graduate Scientific Software Developer

        Oct 2023 - Jun 2024
  • Licenses & Certifications

    • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

      Coursera
      May 2020
      View certificate certificate
    • Neural Networks and Deep Learning

      Coursera
      May 2020
      View certificate certificate
    • Structuring Machine Learning Projects

      Coursera
      May 2020
      View certificate certificate