Dr. Arvind Dewangan

@globalinstitutes.edu.in

Professor- Civil Engineering Dept.(Dean - Research & Development)
Global Group of Institutes Amritsar (Punjab)

Dr. Arvind Dewangan


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https://researchid.co/arvind_dewangan

RESEARCH, TEACHING, or OTHER INTERESTS

Civil and Structural Engineering, Geology, Multidisciplinary, Social Sciences

FUTURE PROJECTS

GeoChem


Applications Invited
8

Scopus Publications

176

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Physics-guided deep ensemble and inverse design for sustainable concrete
    Arvind Dewangan, Neha Sharma, Akanksha Kulshreshtha, Reeta Gulia, Sumit Saini, Sagar Paruthi, Rupesh Kumar Tipu
    Multiscale and Multidisciplinary Modeling Experiments and Design, 2026
    Cement production contributes a significant share of global CO $$_2$$ 2 emissions, yet most laboratories can only access small concrete mix datasets, which limits the direct use of data-driven design tools. This study develops a physics-guided deep ensemble and inverse design framework to support the design of lower-carbon concrete mixtures under data scarcity. The framework first augments a 103-record concrete slump dataset with a physics-regularized conditional tabular GAN (PR-CTGAN) that enforces mass balance, water–binder bounds, and admixture dosage limits during synthetic data generation. It then trains a heterogeneous deep ensemble that combines tree-based regressors with a deep evidential regression (DER) network and a physics-regularized neural network (PRNN) that encodes an empirical slump–water–binder relation as a soft penalty in the loss. This ensemble predicts slump, flow, and 28-day compressive strength while providing uncertainty estimates for each target. Multi-objective Bayesian optimisation tunes the evidential backbone to balance accuracy and probabilistic calibration, and explainable AI tools (SHAP and Sobol sensitivity analysis) highlight how water, binder chemistry, and aggregate ratios drive fresh and hardened behaviour in a way that aligns with concrete practice. Finally, an NSGA-III-based inverse design stage searches the mix space for candidate formulations that meet workability and strength targets while lowering estimated binder-related CO $$_2$$ 2 emissions compared with an all-cement reference mix. The framework integrates physics-guided data augmentation, uncertainty-aware evidential prediction, and eco-constrained inverse optimisation into a single pipeline for sustainable concrete mix design.
  • Bayesian-optimized explainable machine learning framework for predicting reinforced concrete beam ultimate load-carrying capacity
    Arvind Dewangan, Nikita Jain, Neha Sharma, Sagar Paruthi, Rupesh Kumar Tipu
    Asian Journal of Civil Engineering, 2026
  • Interpretable SHAP-Weighted Stacked Ensemble for Joint Prediction of Ultrasonic Pulse Velocity and Rebound Number in SCM-Modified Concrete
    Arvind Dewangan, Nikita Jain, Neelaz Singh, Neha Sharma, Sagar Paruthi, Rupesh Kumar Tipu
    Iranian Journal of Science and Technology Transactions of Civil Engineering, 2026
  • Weighted-ensemble machine learning for simultaneous non-destructive prediction of rebound number and ultrasonic pulse velocity in concrete
    Neha Sharma, Arvind Dewangan, Neelaz Singh, Devjani Bhattacharya, Sagar Paruthi, Rupesh Kumar Tipu
    Asian Journal of Civil Engineering, 2025
  • GA–PSO–optimised dual-path attention network for predicting strength of nano/micro-modified alkali-activated concrete
    Neha Sharma, Arvind Dewangan, Vidhika Tiwari, Neelaz Singh, Rupesh Kumar Tipu, Sagar Paruthi
    Asian Journal of Civil Engineering, 2025
  • AI-Powered Optimization of Antenna Arrays: Enhancing Communication Performance Through Strategic Business Management
    Arvind Dewangan, Navaneetha Krishnan Rajagopal, Adnan Adel Bitar, T. Roseline Velankanni, J. Ravi Kumar, Senthilkumar Sakthivel
    Proceedings of the 2025 International Conference on Technology Enabled Economic Changes Intech 2025, 2025
    This research study provides a novel strategy to improve communication performance inside the AI-powered optimizing efficiency of antenna arrays, merging strategic business management principles. As wireless technological innovations in communication improve, improving antenna arrays become critical for offering higher performance metrics, which may encompass coverage, capacity, and efficiency. Through rigorous simulations and empirical research, the study examines the effect of AI algorithms on antenna array topologies, revealing notable gains in signal strength and quality. The results demonstrate that AI-driven optimization strategies, including reinforcement of AI and algorithm evolution, lead to a 30 % enhancement in signal-to-noise ratio (SNR) and a 25 % increase in overall system capacity compared with regular optimization methods. Furthermore, the installation of these AI solutions resulted in a drop of operational expenditures by 20 %, with a forecast five-year cost savings of approximately $1.2 million for enterprises adopting these technologies. The business impact on leadership underscores the demand for organizations to adjust their business practices in pace with technological developments. By incorporating AI, organizations may not only boost their efficacy as they interact but also strengthen their competitive advantage and their competitiveness. Case examples of successful implementations show the real-world application of the proposed methodologies, highlighting how enterprises may enhance their consumption of resources and achieve long-term prosperity. In conclusion, the incorporation of AI in receiver array algorithm optimization is not merely a technological success but also a strategic business option that encourages creative thinking, efficacy, and profitability.
  • Machine Learning for Credit Scoring: A Comparative Analysis of Traditional and AI-Based Models
    Arvind Dewangan, Mohan Reddy Sareddy, Ida Md Yasin, Qaium Hossain, A.K.M.B. Hossain, Satish Kumar Das
    Proceedings of the 2025 International Conference on Technology Enabled Economic Changes Intech 2025, 2025
    In this research, this paper aims to make a comprehensive comparison between the conventional and the artificial intelligence credit scoring models to understand their performances on various indications and threshold levels. We then cheque the performance of the Logistic Regression, Random forest, Gradient boosting, SVM, artificial neural networks, LSTM, and Transformer architecture in terms of Precision, Recall, and F1-Scores with the help of different datasets and different threshold levels. From the results, it is clear that application of LSTM and Transformer networks improved and can improve credit assessment compared to traditional models. That is why, LSTM and Transformer models perform better in terms of flexibility in different thresholding leading to high F1-Scores and overall performance. Average performance research shown by the stacked area plots gives the idea of the superiority of the performance of the AI-based models in terms of the F1-Score which is particularly useful in dealing with large number of datasets and time span. The Precision, Recall, and F1-Scores evaluation also show that the Transformer model has the highest precision which is used to reduce false alarms. On the same note, the LSTM model has a much higher recall value, which is a clear revelation of the model's ability to diagnose a relatively higher proportion of the actual positive or true positive samples. The Motivation & Rationale comes under this section and it clearly explains that F1-Score proves that models based on Artificial Intelligence have better <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{P}-\mathrm{V}$</tex> balance than the traditional models. The study emphasises the high potential positive impact of using AI-based models in merging with credit score assessments, stating the higher performance and summed up positive effects of applying such models. The whole process of utilising such algorithms should be further extended to real datasets and consider exploring additional performance metrics for improvement and evaluation.
  • Environment pollution: A need of mass movement
    International Journal of Applied Environmental Sciences, 2010

RECENT SCHOLAR PUBLICATIONS

  • Physics-guided deep ensemble and inverse design for sustainable concrete
    A Dewangan, N Sharma, A Kulshreshtha, R Gulia, S Saini, S Paruthi, ...
    Multiscale and Multidisciplinary Modeling, Experiments and Design 9 (1), 78 , 2026
    2026
  • Bayesian-optimized explainable machine learning framework for predicting reinforced concrete beam ultimate load-carrying capacity
    A Dewangan, N Jain, N Sharma, S Paruthi, RK Tipu
    Asian Journal of Civil Engineering, 1-27 , 2026
    2026
  • Interpretable SHAP-Weighted Stacked Ensemble for Joint Prediction of Ultrasonic Pulse Velocity and Rebound Number in SCM-Modified Concrete
    A Dewangan, N Jain, N Singh, N Sharma, S Paruthi, RK Tipu
    Iranian Journal of Science and Technology, Transactions of Civil Engineering … , 2026
    2026
    Citations: 1
  • Weighted-ensemble machine learning for simultaneous non-destructive prediction of rebound number and ultrasonic pulse velocity in concrete
    N Sharma, A Dewangan, N Singh, D Bhattacharya, S Paruthi, RK Tipu
    Asian Journal of Civil Engineering 26 (11), 4775-4796 , 2025
    2025
    Citations: 12
  • GA–PSO–optimised dual-path attention network for predicting strength of nano/micro-modified alkali-activated concrete
    N Sharma, A Dewangan, V Tiwari, N Singh, RK Tipu, S Paruthi
    Asian Journal of Civil Engineering 26 (10), 4287-4302 , 2025
    2025
    Citations: 13
  • Leveraging silica fume as a sustainable supplementary cementitious material for enhanced durability and decarbonization in concrete
    S Paruthi, A Dewangan, N Sharma, N Singh, R Gulia, V Garg, AH Khan
    Advances in Civil Engineering 2025 (1), 5513764 , 2025
    2025
    Citations: 17
  • ZENFI: A UNIFIED PLATFORM FOR PRODUCTIVITY AND RELAXATION
    A DEWANGAN, A JHA, PS SHRIVASTAV
    INTERNATIONAL JOURNAL OF ENGINEERING 9 (06), 92-97 , 2024
    2024
  • Dark Corners of the Cyber World
    A Dewangan
    Available at SSRN 4461445 , 2023
    2023
  • Artificial intelligence: A Privilege or A Disadvantage
    A Dewangan
    Available at SSRN 4442456 , 2023
    2023
  • The Women Empowerment through Banking Services
    A Dewangan
    Available at SSRN 4424401 , 2023
    2023
  • IMPACT OF BIOTITE AND MUSCOVITE IN MICACEOUS BRICKS
    A Dewangan, N Sharma, S Paruthi
    CORROSION AND PROTECTION 51 (1) , 2023
    2023
  • Industry Institute Interaction: A Global Perspective
    A Dewangan
    Available at SSRN 4176642 , 2022
    2022
  • Human Values and its impact on society
    A Dewangan
    Available at SSRN 3868738 , 2021
    2021
    Citations: 3
  • “PROSPECTING AND EXPLORATION APPROACH TO FIND OUT THE UNDERGROUND MINING EXTENSION”
    A Dewangan
    JOURNAL OF XI'AN UNIVERSITY OF ARCHITECTURE & TECHNOLOGY 13 (VI), 61-66 , 2021
    2021
  • MICACEOUS BRICKS : A Formulative and Strategic Study
    RKM Dr. Arvind Dewangan
    NOV YI MIR Research JOURNAL 6 (3), 60-66 , 2021
    2021
  • THE STUDY OF DESIGN OF INDUSTRIAL FACTORY STEEL SHED AND FOUNDATION AND COMPARE WITH REINFORCED CONCRETE PORTAL FRAME STRUCTURE WITH SPECIAL REFERENCE TO DESIGN OF COLUMN & FOOTING
    DDPG Dr. Arvind Dewangan
    EPRA International Journal of Research & Development -IJRD 4 (2), 22-27 , 2019
    2019
  • An Overview of Bearing Capacity of Shallow Foundation
    A Arya, NK Ameta, A Dewangan
    Compliance Engineering Journal 11 (7), 393-398 , 2019
    2019
    Citations: 2
  • Performance Evolution and Audit of Structure by NDT Methods
    EN Goyal, EB Arora, DS Sharma, DA Dewangan
    International Journal of Engineering Research And Management (IJERM) ISSN … , 2018
    2018
    Citations: 4
  • Significance of marble and Portland cement
    A Dewangan, PD Gupta
    Int J Eng Tech Manag Res 5, 255-265 , 2018
    2018
    Citations: 2
  • Assessment of competitive bidding strategy scenarios in the construction industry of India
    S Dey, B Arora, A Dewangan, M Das
    International Journal for Research in Applied Science and Engineering … , 2018
    2018
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • Evaluation of strength characteristics of concrete using crushed stone dust as fine aggregate
    L Nagpal, A Dewangan, S Dhiman, S Kumar
    International Journal of Innovative Technology and Exploring Engineering 2 … , 2013
    2013.0
    Citations: 45
  • Developing an Efficient Schedule in Primavera P6: Significance of Activity ID & Descriptions
    S Chopra, A Dewangan
    International journal of innovative research in science, engineering and … , 2014
    2014.0
    Citations: 22
  • Leveraging silica fume as a sustainable supplementary cementitious material for enhanced durability and decarbonization in concrete
    S Paruthi, A Dewangan, N Sharma, N Singh, R Gulia, V Garg, AH Khan
    Advances in Civil Engineering 2025 (1), 5513764 , 2025
    2025.0
    Citations: 17
  • GA–PSO–optimised dual-path attention network for predicting strength of nano/micro-modified alkali-activated concrete
    N Sharma, A Dewangan, V Tiwari, N Singh, RK Tipu, S Paruthi
    Asian Journal of Civil Engineering 26 (10), 4287-4302 , 2025
    2025.0
    Citations: 13
  • Weighted-ensemble machine learning for simultaneous non-destructive prediction of rebound number and ultrasonic pulse velocity in concrete
    N Sharma, A Dewangan, N Singh, D Bhattacharya, S Paruthi, RK Tipu
    Asian Journal of Civil Engineering 26 (11), 4775-4796 , 2025
    2025.0
    Citations: 12
  • The significance of geotextile in unpaved roads with special reference to stress analysis
    A Dewangan, DP Gupta, RK Bakshi, RK Manchiryal
    International Journal of Current Engineering and Technology 3 (1), 168-178 , 2013
    2013.0
    Citations: 10
  • Permeability behavior of Self compacting concrete
    S Dhiman, A Dewangan, EL Nagpal, S Kumar
    International Journal of Innovative Technology and Exploring Engineering … , 2013
    2013.0
    Citations: 9
  • The significance of partial replacement of cement with waste marble powder
    M Pawar, A Dewangan
    International Journal Online of Sports Technology & Human Engineering 3 (1), 1-6 , 2014
    2014.0
    Citations: 6
  • Implementation and analysis of strength characteristics of concrete using crusted stone dust as fine aggregate
    RK Manchiryal, A Dewangan, DP Gupta
    International Journal of Research in Engineering and Applied Sciences 4 (10 … , 2014
    2014.0
    Citations: 6
  • The role of advertisement in the society
    N Rai, A Dewangan
    International Journal of Research in IT and Management 5 (4), 26-31 , 2015
    2015.0
    Citations: 5
  • Performance Evolution and Audit of Structure by NDT Methods
    EN Goyal, EB Arora, DS Sharma, DA Dewangan
    International Journal of Engineering Research And Management (IJERM) ISSN … , 2018
    2018.0
    Citations: 4
  • Human Values and its impact on society
    A Dewangan
    Available at SSRN 3868738 , 2021
    2021.0
    Citations: 3
  • Determination of compressive strength difference between conventional concrete and recycled aggregate concrete
    R Sikka, A Dewangan
    International Journal of Current Research and Academic Review 2 (9), 175-180 , 2014
    2014.0
    Citations: 3
  • Hedging of currency option in trading market
    N Aggarwal, N Aggarwal, A Dewangan, G Aggarwal
    International Journal of Economic and Management Strategy 3 (1), 1-6 , 2013
    2013.0
    Citations: 3
  • Various prospects of nano technology
    T Singhal, D Rana, A Dewangan, N Agarwal
    International Journal of Nanotechnology & Applications 4 , 2010
    2010.0
    Citations: 3
  • Analysis of pavement for national highway
    A Dewangan, DP Gupta, RK Bakshi
    International Journal of Computer Technology and Economics Engineering … , 0
    Citations: 3
  • An Overview of Bearing Capacity of Shallow Foundation
    A Arya, NK Ameta, A Dewangan
    Compliance Engineering Journal 11 (7), 393-398 , 2019
    2019.0
    Citations: 2
  • Significance of marble and Portland cement
    A Dewangan, PD Gupta
    Int J Eng Tech Manag Res 5, 255-265 , 2018
    2018.0
    Citations: 2
  • Stress Distribution Analysis of the Kaolinite Layer at the Kaolinite–Geotextile
    A Dewangan, DP Gupta, RK Bakshi, RK Manchiryal
    International Journal of Innovative Technology and Exploring Engineering … , 2013
    2013.0
    Citations: 2
  • Interpretable SHAP-Weighted Stacked Ensemble for Joint Prediction of Ultrasonic Pulse Velocity and Rebound Number in SCM-Modified Concrete
    A Dewangan, N Jain, N Singh, N Sharma, S Paruthi, RK Tipu
    Iranian Journal of Science and Technology, Transactions of Civil Engineering … , 2026
    2026.0
    Citations: 1

INDUSTRY EXPERIENCE

5 Years