Dr. Jignesh Amin

EDUCATION

Ph.D. in Structural Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Civil and Structural Engineering, Building and Construction

Scopus Publications

Assessing Water Quality Through Remote Sensing: A Regression-Based Approach with Sentinel-2 Data
Mridul S. Seth, Mrugen B. Dholakia, Sanjay D. Dhiman, Umesh. K. Khare, Jignesh A. Amin, et al.
Nature Environment and Pollution Technology, 2026
Monitoring water quality is essential for ensuring human health and environmental sustainability. Traditional methods that rely on laboratory analysis and point-based sampling often lack sufficient spatial and temporal coverage. This study assessed the water quality along the Sabarmati Riverfront in Ahmedabad, India, using Google Earth Engine (GEE) and Sentinel-2 satellite imagery. Key parameters, including pH, turbidity (Tur), Electrical Conductivity (EC), Total Suspended Solids (TSS), Total Solids (TS), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Total Phosphorus (TP), Fecal Coliform (FC), and ammonia (NH₃), were estimated using remote sensing. An empirical regression model was developed to relate in situ data to satellite-derived spectral indices. Results revealed significant seasonal and spatial variations, with some areas showing favorable levels of TSS, BOD, and FC. The model showed strong predictive accuracy for pH, TSS, and TP (R² = 0.80, R² = 0.76, R² = 0.75, respectively) and moderate performance for turbidity (R² = 0.62). Integrating remote sensing and GIS enables scalable, cost-effective, real-time water quality monitoring, providing critical insights for pollution control and water resource management. Future research should explore hyperspectral imaging and machine learning to enhance predictive accuracy and broaden the applicability of satellite-based monitoring models.
Corrigendum: Multivariate analysis of inland water quality index in parts of Vapi district, Gujarat, India (Water Supply, (2025), 25, 2, (193-211), 10.2166/ws.2024.264)
Mridul Seth, Mrugen Dholakia, Sanjay Dhiman, U. K. Khare, Jignesh Amin, et al.
Water Supply, 2026
Attention-Enhanced Progressive Transfer Learning for Scalable Seismic Vulnerability Assessment of RC Frame Buildings
Kaushik M. Gondaliya, Konstantinos Daniel Tsavdaridis, Aanal Raval, Jignesh A. Amin, Komal Borisagar
Buildings, 2025
Urban infrastructure in seismic zones demands efficient and scalable tools for damage prediction. This study introduces an attention-integrated progressive transfer learning (PTL) framework for the seismic vulnerability assessment (SVA) of reinforced concrete (RC) frame buildings. Traditional simulation-based vulnerability models are computationally expensive and dataset-specific, limiting their adaptability. To address this, we leverage a pretrained artificial neural network (ANN) model based on nonlinear static pushover analysis (NSPA) and Monte Carlo simulations for a 4-story RC frame, and extended its applicability to 2-, 8-, and 12-story configurations via PTL. An attention mechanism is incorporated to prioritize critical features, enhancing interpretability and classification accuracy. The model achieves 95.64% accuracy across five damage categories and an R2 of 0.98 for regression-based damage index predictions. Comparative evaluation against classical and deep learning models demonstrates superior generalization and computational efficiency. The proposed framework reduced retraining requirements across varying building heights, shows potential adaptability to other structural typologies, and maintains high predictive fidelity, making it a practical AI solution for structural risk evaluation in seismically active regions.
Seismic vulnerability and fragility assessment of elevated water tanks with diverse staging frame patterns
Dhaval Bhalani, Kaushik Gondaliya, Jignesh Amin
Innovative Infrastructure Solutions, 2025
Seismic Vulnerability Assessment of Building Stocks in the Western Zone of Surat-City, Gujarat, India, Using the Capacity Spectrum-Based Method
Kaushik Gondaliya, Jignesh Amin, Vishisht Bhaiya, Sandip Vasanwala, Atul Desai
Journal of Structural Design and Construction Practice, 2025
Multivariate analysis of inland water quality index in parts of Vapi district, Gujarat, India
Mridul Seth, Mrugen Dholakia, Sanjay Dhiman, U. K. Khare, Jignesh Amin, et al.
Water Supply, 2025
Water resource management substantially depends on water quality (WQ). Anthropogenic and geogenic pollutants in water system are challenging to identify, transport, and properly dispose of, thus demanding frequent monitoring. Study focuses on application of statistical approach to analyse pattern and to monitor WQ parameters of region. Paper presents computation of water quality index (WQI) based on various WQ parameters of the Daman Ganga River situated in Vapi, Gujarat, India. 17 WQ parameters considered were pH, electrical conductivity, temperature (Temp), total dissolved solids, NO2 + NO3, (P-Tot), Ca, Mg, Na, K, Cl, SO4, CO3, HCO3, total hardness, sodium absorption ratio (SAR), and calcium hardness (HAR_Ca). Quartile deviation was carried out as preprocessing technique to identify fair analysis of trend followed by other parameters. Application of PCA followed by varimax rotation factor analysis was attempted to identify contribution of significant parameters. Methods developed by Council of Canadian Ministry of Environment (CCME) and British Columbia (BC) were applied to compute WQI. WQI evaluated were 42.35 and 63.29 for CCME and BC, respectively, based on five significantly influencing parameters, namely, HAR_Ca, SAR, CO3, Temp, and P-Tot. Study signifies the hardness and salinity factors impacting WQ and efficiently reduces subjectivity and bias to determine the WQI model.
Seismic Performance-Based Evaluation of R-factor for Indian Code-Compliant RC Frames with URM Infill Walls
Rushali Madhwani, Kaushik Gondaliya, Harshingar Patel, Jignesh Amin
Springer Proceedings in Materials, 2025
Design Optimization of Indian Code-Compliant RC Frames
Kaushik Gondaliya, Sandip Vasanwala, Atul Desai, Jignesh Amin
Lecture Notes in Civil Engineering, 2025
A Novel Machine Learning Framework for Seismic Vulnerability Assessment of Urban Infrastructure
Kaushik Gondaliya, Sneha Kumari, Jignesh Amin, Abdullah Ansari, RC Bush
International Conference for Artificial Intelligence Applications Innovation and Ethics Ai2e 2025, 2025
The assessment of seismic vulnerability in urban infrastructure presents a significant challenge in rapidly growing cities, as conventional evaluation methods frequently do not yield reliable and accurate insights for emergency response and planning. Machine learning algorithms demonstrate potential in structural analysis; however, a notable gap exists in methodologies capable of integrating diverse data sources for thorough vulnerability assessment. This paper presents a novel framework integrating Geographic Information Systems (GIS) data, structural analysis, and machine learning techniques to overcome existing limitations. The proposed methodology utilizes ArcGIS Pro for spatial data management, SAP2000 for conducting Nonlinear Static Pushover Analysis (NSPA) to assess structural response to seismic forces, and employs advanced machine learning algorithms to train the ANN model applicable to various urban structures, including residential buildings, bridges, and water tanks. The framework employs artificial neural networks for damage prediction and utilizes Monte Carlo simulation for uncertainty quantification, thereby providing a probabilistic method for vulnerability assessment. The proposed system processes structural and seismic data via an automated pipeline, facilitating rapid risk assessment and decision-making support. This approach addresses existing gaps in probabilistic seismic vulnerability assessment and provides a theoretical foundation for developing resilient urban infrastructure systems. The framework can be applied in urban planning, emergency response, and infrastructure prioritization, providing essential support for decision-makers in disaster management.
Machine learning-based approach for assessing the seismic vulnerability of reinforced concrete frame buildings
Kaushik M. Gondaliya, Sandip A. Vasanwala, Atul K. Desai, Jignesh A. Amin, Vishisht Bhaiya
Journal of Building Engineering, 2024
Investigation of Wind Interference on Vertically Twisted Skyscrapers
Chirag Mehta, Kaushik Gondaliya, Jignesh Amin
Lecture Notes in Civil Engineering, 2024
Comparison of Methodologies for Seismic Fragility Analysis of Designed RC Frame Building as Per Indian Provisions
Kaushik Gondaliya, Jignesh Amin, Sandip Vasanwala, Atul Desai
Lecture Notes in Civil Engineering, 2024
Methods Comparison of Seismic Fragility for Indian Code-Compliant RC Frame
Kaushik Gondaliya, Ronak Motiani, Jignesh Amin, Sandip Vasanwala, Atul Desai
Lecture Notes in Civil Engineering, 2024
Wind-Induced Interference Effects due to Partial Shielding of Building
Jignesh Amin
Journal of the Institution of Engineers India Series A, 2023
Generating seismic fragility curves of RC frame building using NSPA and IDA
Kaushik Gondaliya, Jignesh Amin, Vishisht Bhaiya, Sandip Vasanwala, Atul Desai
Asian Journal of Civil Engineering, 2023
Influence of Epistemic Uncertainty on the Seismic Vulnerability of Indian Code-Compliant RC Frame Building
Kaushik Gondaliya, Vishisht Bhaiya, Sandip Vasanwala, Atul Desai, Jignesh Amin
Lecture Notes in Civil Engineering, 2023
Seismic Vulnerability Assessment of Indian Code Compliant RC Frame Buildings
Kaushik M. Gondaliya, Jignesh Amin, Vishisht bhaiya, Sandip Vasanwala, Atul K. Desai
Journal of Vibration Engineering and Technologies, 2023
Assessment of seismic collapse probability of RC shaft supported tank
Jignesh Amin, Kaushik Gondaliya, Chirag Mulchandani
Structures, 2021
Seismic evaluation of rc frame designed with effective and gross section using fbd and ddbd approach
Indian Concrete Journal, 2021
Drift and Response Reduction Factor of RC Frames Designed with DDBD and FBD Approach
Kunjan Gamit, Jignesh A. Amin
Journal of the Institution of Engineers India Series A, 2021
Assessment of Seismic Response Reduction Factor for RC Shaft Supported Tank
Chirag Mulchandani, Jignesh Amin
Journal of the Institution of Engineers India Series A, 2021
Seismic assessment of RC frame building designed using gross and cracked section as per Indian standards
Samir K. Prajapati, Jignesh A. Amin
Asian Journal of Civil Engineering, 2019
Comparative assessment of RC wall-frame buildings designed with DDBD and FBD method
Journal of Structural Engineering India, 2018
Performance-based assessment of response reduction factor of RC-elevated water tank considering soil flexibility: a case study
Kashyap N. Patel, Jignesh A. Amin
International Journal of Advanced Structural Engineering, 2018
Characteristics of wind forces and responses of rectangular tall buildings
J. A. Amin, A. K. Ahuja
International Journal of Advanced Structural Engineering, 2014

Publications

1.Jignesh Amin, Kaushik Gondaliya, Chirag Mulchandani (2021) Assessment of seismic collapse probability of RC shaft supported tank, Structures, Elsevier, 33 (2), pp-2639-2658, DOI: 10.1016/j., ISSN: 2352-0124.
2. Harshad Gajera and Jignesh Amin (2021) Seismic evaluation of RC frame designed with effective and gross section using FBD and DDBD approach, Indian Concrete Journal, Vol. 95 (9) , ISSN: 00194565
3. Kaushik M. Gondaliya, Jignesh Amin, Vishisht bhaiya, Sandip Vasanwala, Atul K. Desai (2023) Seismic vulnerability evaluation of code compliant RC frame buildings using fragility analysis, Journal of Vibration Engineering and Technologies (under review), ISSN- 2523-3939,
4. Kaushik Gondaliya, Jignesh Amin et al. (2023) Generating Seismic Fragility Curves of RC Frame Building using NSPA and IDA, Asian Journal of Civil Engineering,
5. Jignesh Amin (2023) Wind-Induced Interference Effects Due to Partial Shielding of Building, Journal of The Institution of Engineers (India): Series A, DOI: 10.1007/s40030-023-00756-3
6. Kaushik Gondaliya, Jignesh Amin et al. (2023) Machine Learning-based Approach for Assessing the Seismic Vulnerability of RC Frame Buildings , Prac Periodical on Structural Design and Construction,ASCE (Accepted for publication)

GRANT DETAILS

• Received Grant (INR 105000) under Minor Research Project scheme from GUJCOST, Department of Science and Technology, Government of Gujarat.
• Received Grant (INR 915000) under MODROB scheme from AICTE, New Delhi for the modernization of Strength of Material Lab. ( co-coordinator)

CONSULTANCY

Proof checking vettting of structural design and drawing of Civil Engineering Structures