CV

Contact Information

Name Vignesh Sella
Email vsella@utexas.edu

Education

  • 2022 - present

    Austin, TX

    PhD
    University of Texas at Austin
    Computational Science, Engineering, and Mathematics
    • Co-Advisors: Dr. Karen Willcox & Dr. Anirban Chaudhuri
  • 2021 - 2023

    Austin, TX

    M.S.
    University of Texas at Austin
    Computational Science, Engineering, and Mathematics
  • 2017 - 2021

    Urbana, IL

    B.S.
    University of Illinois at Urbana-Champaign
    Aerospace Engineering, Minor in Computer Science

Experience

  • 01/2025 - 10/2025

    Mountain View, CA

    AI/ML Resident
    Google
    • AI/ML R&D for an undisclosed project related to finance, decarbonization, and climate at X, the moonshot factory.
  • 05/2022 - 08/2022

    Salisbury, NC

    Data Scientist Intern
    Toyota
    • Built a time-series analysis tool and an end-to-end testing method in Python to replace human-in-the-loop process saving in excess of 10% in operating costs
    • Expedited data analysis timeline by 90% by building an ETL pipeline for wind tunnel data

Research Experience

  • 07/2021 - Present

    Austin, TX

    Graduate Research Assistant
    Oden Institute for Computational Engineering and Sciences
    • Developing interpretable multi-fidelity (MF) deep learning and linear regression methods for high-dimensional, data-scarce problems on HPCs, resulting in 2 journal publications to date
    • Contributed to DARPA-funded open-source causal inference and dynamical systems modeling toolkit by developing testing frameworks, validating methods using ODE-based COVID-19 epidemiological models
    • Applied MF neural networks to airfoil optimization and MF linear regression to hypersonic vehicle pressure field prediction, achieving >95% accuracy at the same cost as single-fidelity methods
  • 08/2020 - 05/2021

    Urbana, IL

    Research Intern
    National Center for Supercomputing Applications (NCSA)
    • Investigated the explainability of deep convolutional neural networks (CNNs) in TensorFlow through saliency maps and first principles yielding a contribution in a publication
    • Constructed CNNs to predict Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics results from flow field and geometrical information
  • 08/2019 - 05/2020

    Urbana, IL

    Undergraduate Research Assistant
    UIUC Electric Propulsion Laboratory
    • Created analytical model based off incompressible Navier-Stokes equation and control volume analysis of thrust stand to understand theoretical guarantees
    • Improved electric micro-propulsion thrust stand accuracy by over 90% through hardware improvements
  • 05/2019 - 03/2020

    Urbana, IL

    Undergraduate Research Assistant
    UIUC Aerospace Controls & Optimization Group
    • Translated model predictive control code in MATLAB to C++ through the IPOPT library

Publications

  • 2025
    Projection-based multifidelity linear regression for data-scarce applications
    Machine Learning for Computational Science and Engineering

    Machine Learning for Computational Science and Engineering 1, no. 2 (2025): 47.

  • 2025
    Multifidelity linear regression for scientific machine learning from scarce data
    Foundations of Data Science

    Foundations of Data Science 7, no. 1 (2025): 271-297.

  • 2025
    Improving neural network efficiency with multifidelity and dimensionality reduction techniques
    AIAA SciTech 2025 Forum

    AIAA SciTech 2025 Forum, p. 2807.

  • 2023
    Projection-based multifidelity linear regression for data-poor applications
    AIAA SciTech 2023 Forum

    AIAA SciTech 2023 Forum, p. 0916.

  • 2021
    Turbomachinery blade surrogate modeling using deep learning
    International Conference on High Performance Computing

    Springer International Publishing, pp. 92-104.

  • 2020
    Development of a nytrox-paraffin hybrid rocket engine
    AIAA Propulsion and Energy 2020 Forum

    AIAA Propulsion and Energy 2020 Forum, p. 3729.

Conference Presentations

  • 2024
    Surrogate modeling for data-scarce applications using projection-based multifidelity linear regression
    Vignesh Sella, Julie Pham, Anirban Chaudhuri, Karen Willcox
    Model Reduction and Surrogate Modeling 2024 (MORe24)
  • 2024
    Multifidelity linear regression via a combined loss function for data-constrained applications
    Vignesh Sella, Julie Pham, Anirban Chaudhuri, Karen Willcox
    WCCM 2024

Invited Talks

  • 2025
    Take your hobbies seriously!
    Vignesh Sella
    Google X Belonging Talks
  • 2025
    Geospatial Foundation Models for Learned Feature Embeddings in Ecological Systems
    Vignesh Sella, Greg Bronevetsky
    Google X Technical Talk

Awards

  • 2025
    Google Belonging Award
    Google
  • 2020
    Dean's List
    University of Illinois at Urbana-Champaign

    2019-2021

  • 2020
    William R. Schowalter Scholarship
    University of Illinois at Urbana-Champaign
  • 2019
    Research Support Grant
    University of Illinois at Urbana-Champaign
  • 2019
    French Merit Award
    University of Illinois at Urbana-Champaign
  • 2019
    Student Sustainability Grant
    University of Illinois at Urbana-Champaign

Skills

Programming Languages / Frameworks: Python, C++, CUDA, MATLAB, R, REST API, Node.js, Flask
Technologies: SQL (MySQL), MLflow, AWS Aurora, Lambda, Glue, SQS, SNS, Kinesis, S3, HDFS, GCP BigQuery, Apache Beam, Hive, Redis, Git
Build / CI/CD: Docker, Kubernetes, Jenkins, GitHub Actions
Data Science / ML: PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, Pandas

Languages

English : Native
Marathi : Intermediate
French : Beginner
Spanish : Beginner

Interests

Machine Learning: Multi-fidelity methods, deep learning, scientific machine learning
Computational Science: High-performance computing, surrogate modeling, numerical methods
Applied Mathematics: Linear regression, dimensionality reduction, dynamical systems