CV
Contact Information
| Name | Vignesh Sella |
| vsella@utexas.edu |
Education
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2022 - present Austin, TX
PhD
University of Texas at Austin
Computational Science, Engineering, and Mathematics
- Co-Advisors: Dr. Karen Willcox & Dr. Anirban Chaudhuri
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2021 - 2023 Austin, TX
M.S.
University of Texas at Austin
Computational Science, Engineering, and Mathematics
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2017 - 2021 Urbana, IL
B.S.
University of Illinois at Urbana-Champaign
Aerospace Engineering, Minor in Computer Science
Experience
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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.
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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
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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
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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
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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
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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
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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.
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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.
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2025 Improving neural network efficiency with multifidelity and dimensionality reduction techniques
AIAA SciTech 2025 Forum
AIAA SciTech 2025 Forum, p. 2807.
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2023 Projection-based multifidelity linear regression for data-poor applications
AIAA SciTech 2023 Forum
AIAA SciTech 2023 Forum, p. 0916.
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2021 Turbomachinery blade surrogate modeling using deep learning
International Conference on High Performance Computing
Springer International Publishing, pp. 92-104.
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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
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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)
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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
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2025 Take your hobbies seriously!
Vignesh Sella
Google X Belonging Talks
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2025 Geospatial Foundation Models for Learned Feature Embeddings in Ecological Systems
Vignesh Sella, Greg Bronevetsky
Google X Technical Talk
Awards
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2025 Google Belonging Award
Google
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2020 Dean's List
University of Illinois at Urbana-Champaign
2019-2021
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2020 William R. Schowalter Scholarship
University of Illinois at Urbana-Champaign
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2019 Research Support Grant
University of Illinois at Urbana-Champaign
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2019 French Merit Award
University of Illinois at Urbana-Champaign
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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