M NIDHI

About

Dr. Nidhi M. is an accomplished academician and researcher with over 10 years of experience in the department of Civil Engineering, currently working as an Assistant Professor at the National Institute of Technology Puducherry. Her Ph.D Thesis entitled “Strength and Behaviour of HFRHPC Beam-Column-Slab Joints under Reverse Cyclic Loading” won ICI - Ultra Tech award 2017 for the outstanding thesis in the field of concrete. She is also a mentor for Indo German Science and Technology Centre PhD Industrial Exposure (IGSTC - PIEF fellowship 2025 for the project titled "Experimental Assessment of High Temperature Behaviour of Hybrid Fibre Reinforced Geopolymer Concrete and Prediction of Compressive Strength using Explainable Machine Learning Approaches". She has successfully completed Coalition for Disaster Resilient Infrastrucre (CDRI) fellowship 2022-23 for the project titled "Machine Learning Based Unified Seismic Vulnerability Prediction Model for Heritage Minarets of India". Her area of reseach interest includes structural health monitoring, vulnerability prediction modelling, forensic engineering, sustainable composites, application of machine learning techniques in the prediction of concrete properties.

Employment

• National Institute of Technology Puducherry Assistant Professor
  2021 - Present
• National Institute of Technology Puducherry Faculty
  2020 - 2021
• Jyothi Engineering College Associate Professor
  2018 - 2020
• Federal Institute of Science and Technology Assistant Professor
  2016 - 2018
• National Institute of Technology Calicut Research scholar
  2012 - 2016
• Universal Engineering College Assistant Professor
  2011 - 2012

Education

• National Institute of Technology PhD
  2012 - 2017
• College of Engineering Trivandrum MTech
  2009 - 2011
• Nair Service Society College of Engineering BTech
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (19)

• A Novel Hybrid Model for Predicting Strength Characteristics in Fiber-Reinforced Geopolymer Concrete Based on Extreme Gradient Boosting and Particle Swarm Optimization
  Lecture Notes in Civil Engineering 2026 DOI: 10.1007/978-981-96-7971-3_2
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• A Review of the Influence of Fibres on the Fracture Properties of Sustainable Geopolymer Concrete
  Lecture Notes in Civil Engineering 2026 DOI: 10.1007/978-981-96-7971-3_9
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• Assessing Seismic Risks in Heritage Slender Masonry Minaret: A Case Study of Chand Minar
  2026 DOI: 10.1007/978-3-032-15387-6_25
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• Mechanical and microstructural response of slag-sugarcane bagasse ash geopolymer fibrous concrete after elevated temperature exposure
  Journal of Building Engineering 2026 DOI: 10.1016/j.jobe.2026.116890
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• An interpretable machine learning approach with graphical user interface for strength prediction of sustainable slag-based geopolymer concrete
  Structures 2025 DOI: 10.1016/j.istruc.2025.110281
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• Compressive strength prediction and feature analysis for GGBS-Based geopolymer concrete using optimized XGBoost and SHAP: A comparative study of optimization algorithms and experimental validation
  Journal of Building Engineering 2025 DOI: 10.1016/j.jobe.2025.112879
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• Development and optimization of geopolymer concrete with compressive strength prediction using particle swarm-optimized extreme gradient boosting
  Applied Soft Computing 2025 DOI: 10.1016/j.asoc.2025.113149
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• Seismic vulnerability assessment of slender masonry structures: A machine learning approach with vibration-based assessment and nonlinear dynamic analysis
  Structures 2025 DOI: 10.1016/j.istruc.2025.109272
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• A comparative analysis of tree-based machine learning algorithms for predicting the mechanical properties of fibre-reinforced GGBS geopolymer concrete
  Multiscale and Multidisciplinary Modeling Experiments and Design 2024 DOI: 10.1007/s41939-023-00355-6
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• The Use of Artificial Neural Network Model to Predict the Compressive Strength of Sustainable Geopolymer Concrete: A Systematic Review
  Lecture Notes in Civil Engineering 2024 DOI: 10.1007/978-981-97-4844-0_50
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