Raju Chowdhury

About

Raju is a researcher focusing on Bayesian optimization, surrogate modeling, and global optimization techniques for expensive black-box functions. His work aims to develop efficient, scalable methods for real-world applications in science and engineering.

Employment

• Indian Statistical Institute Research Associate
  2025 - Present
• Indian Institute of Technology Madras Post Doctoral Researcher
  2025 - 2025
• Indian Institute of Technology Madras Senior Research Fellow
  2024 - 2025

Education

• Indian Institute of Technology Madras Doctor of Philosophy
  2019 - 2024
• Indian Institute of Technology Madras MTech (Upgraded to PhD)
  2018 - 2019
• Indian Institute of Technology Kharagpur Master of Science
  2016 - 2018

Projects & Funding

Projects & funding information is unavailable.

Publications (5)

• Constrained Bayesian Optimization with Feasibility-Infeasibility Weighted Improvement Criterion
  Journal of Computational and Graphical Statistics 2026 DOI: 10.1080/10618600.2025.2611111
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• Addressing mixed constraints: an improved framework for black-box optimization
  Journal of Global Optimization 2025 DOI: 10.1007/s10898-025-01486-5
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• Constrained Bayesian Optimization with Lower Confidence Bound
  Technometrics 2024 DOI: 10.1080/00401706.2024.2336535
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• Hybrid Method for Constrained Bayesian Optimization
  2023 DOI: 10.21203/rs.3.rs-2421809/v1
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• Estimation of the parameters of vector autoregressive moving average (VARMA) time series model with symmetric stable noise
  International Journal of Advances in Engineering Sciences and Applied Mathematics 2021 DOI: 10.1007/s12572-021-00307-8
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