Assist. Prof. Dr. Yan Zeng | AI in Engineering | Best Researcher Award

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Assist. Prof. Dr. Yan Zeng | AI in Engineering | Best Researcher Award

Assist. Prof. Dr. Yan Zeng | Hangzhou Dianzi University | China

Assist. Prof. Dr. Yan Zeng, an accomplished associate professor at the School of Computer Science, Hangzhou Dianzi University, has made significant contributions in the fields of distributed and parallel computing, distributed machine learning, and big data analytics. After earning her PhD from the Institute of Software, Chinese Academy of Sciences in 2016, her research has focused on advancing large-scale computation and data-intensive systems.  The Key Research and Development Program of Zhejiang Province, the Yangtze River Delta Project, and the Natural Science Foundation of Zhejiang Province. Her academic influence is reflected in 173 citations by 161 documents, 42 published papers, and an h-index of 9, demonstrating strong research impact and visibility. With 10 peer-reviewed publications in SCI and Scopus-indexed journals, Yan Zeng’s scholarly output showcases innovation in computational frameworks and distributed systems. Furthermore, she has been actively involved in practical technological advancements, holding 34 patents that bridge theoretical insights with industrial applications. Through her extensive research, publication record, and innovation-driven approach, Yan Zeng continues to play a pivotal role in shaping advancements in computer science and data engineering.

Profile: Scopus

Featured Publications

Zeng, Y., et al. (2025). FedAMM: Federated learning for brain tumor segmentation with arbitrary missing modalities [Conference paper]. Proceedings of the International Conference on Artificial Intelligence and Machine Learning.

Zeng, Y., et al. (2025). TransAware: An automatic parallel method for deep learning model training with global model structure awareness [Conference paper]. Proceedings of the International Conference on Advanced Computing and Applications.

Zeng, Y., et al. (2025). A correlation analysis-based federated learning framework for defending against collusion-free-riding attacks. Cybersecurity, 2025(1), 1–12.

Zeng, Y., et al. (2025). FedAEF: Optimizing federated learning with mining and enhancing local data features. Cluster Computing, 2025(1), 1–15.

Mr. Chaohui Zhao | Structural Engineering | Best Researcher Award

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Mr. Chaohui Zhao | Structural Engineering | Best Researcher Award

Mr. Chaohui Zhao | shanghai dianji university | China

Mr. Chaohui Zhao is a distinguished researcher specializing in power electronics, motion control, and the design and control of special electric machines. His work encompasses advanced motion control systems, high-performance power conversion technologies, and energy-efficient electric machine design. He has contributed to multiple research projects focused on integrating power electronics with motion control to improve system performance, reliability, and efficiency. Professor Zhao has authored several technical publications and holds patents such as CN119834502A, demonstrating his focus on translating research into practical engineering solutions. His research has impacted the development of intelligent drive technologies, precision control of electromechanical devices, and optimization of industrial electrification systems. By bridging theoretical innovation with applied engineering, his work advances knowledge in power electronics and specialized electric machines while addressing practical challenges in automation and electrical system design.

Profile: Orcid

Featured Publications

Gao, H., Zhao, C., & Cao, Z. (2025). Research on motor torque performance of AHRPM motor based on MFS effect. IEEJ Transactions on Electrical and Electronic Engineering. Advance online publication.

Tan, F., Ma, Y., & Zhao, C. (2025). Research on speed control of PMSM based on super-twisting sliding mode corrected differential linear active disturbance rejection. Energies, 18(17455).

Cao, Z., Zhao, C., & Gao, H. (2025). Structural optimization and characteristic analysis of TMPS-HEG based on particle swarm optimization algorithm. Journal of Electrical Engineering & Technology. Advance online publication.

Xie, S., Zhang, W., Feng, X., Zhang, W., Gu, P., Lei, Z., & Zhao, C. (2025). Torque ripple suppression of open-winding permanent magnet synchronous motor with common DC bus based on field circuit coupling method. International Journal of Circuit Theory and Applications. Advance online publication.

Ma, Y., Zhao, C., Gu, P., Lei, Z., & Zhang, W. (2025). Speed control of PMSM based on series lead correction doubly fed differential LADRC. International Journal of Circuit Theory and Applications. Advance online publication.

Cao, Z., Zhao, C., & Gao, H. (2025). Research on the four-quadrant operating mechanism of a hybrid excitation generator with magnetic field modulation and the power distribution ratio between permanent magnet and magnetic field modulation. International Journal of Circuit Theory and Applications. Advance online publication.

Dr. S. Thirunavukkarasu | AI in Engineering | Best Researcher Award

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Dr. S. Thirunavukkarasu | AI in Engineering | Best Researcher Award

Dr. S. Thirunavukkarasu | Indira Gandhi Centre for Atomic Research | India

Dr. S. Thirunavukkarasu research focuses on quantitative nondestructive evaluation (NDE), finite element (FE) modeling, digital signal and image processing, and the development of innovative sensors and instrumentation for advanced inspection applications. His work emphasizes multi-parametric linear and nonlinear regression, radial basis function (RBF), and multidimensional RBF neural networks for accurate flaw sizing in eddy current testing. He has contributed to FE modeling of electromagnetic NDE phenomena, including the optimization of remote field eddy current probe parameters for ferromagnetic steam generator tube inspections and modeling of magnetic flux leakage considering nonlinear magnetic permeability. His studies extend to the simulation of pulsed and sweep frequency eddy current methods to improve detection efficiency. Additionally, his research in wavelet transform–based digital signal processing enhances the interpretation of eddy current signals from complex regions such as bends and support plate intersections. He has also advanced in-house development of remote field eddy current techniques for the inspection of modified 9Cr-1Mo steel steam generator tubes. His computational expertise includes MATLAB, Python, and LabVIEW, alongside specialized software such as COMSOL, FEMM, and CIVA for modeling and simulation in electromagnetic and NDE applications.

Profile: Orcid

Featured Publications

Arun, A. D., Rajiniganth, M. P., Chandra, S., & Thirunavukkarasu, S. (2025). A numerical model of parallel disc capacitor probe used in nondestructive dielectric permittivity evaluation by algebraic topological method. International Journal of Applied Electromagnetics and Mechanics, 2025-09.

Sharatchandra Singh, W., Haneef, T. K., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ measurement of tensile deformation-induced magnetic fields in high strength low alloy steels using GMR based metal magnetic memory technique. International Journal of Applied Electromagnetics and Mechanics, 2025-09-10.

Arun, A. D., Chandra, S., Thirunavukkarasu, S., Rajiniganth, M. P., Malathi, N., & Sivaramakrishna, M. (2025). A novel algebraic topological method-based approach for evaluating stored electrostatic energy and 3D Maxwellian capacitance. Journal of Electrostatics, 2025-06.

Thirunavukkarasu, S., Kumar, A., Martin, J. P., Harini, T., Reddy, S., Emil, S., & Balu, C. (2025). Automated detection of defects in eddy current inspection data using machine learning methods. International Journal of Applied Electromagnetics and Mechanics, 2025-06-03.

Balakrishnan, S., Das, C. R., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ hardness evaluation of hard-faced coatings through eddy current NDE. International Journal of Applied Electromagnetics and Mechanics, 2025-05-23.

Vijayachandrika, T., Arjun, V., Thirunavukkarasu, S., & Kumar, A. (2025). Design, fabrication, and characterization of staggered array radial coil RFEC probe for small diameter ferritic steel tube. IEEE Sensors Journal, 2025-05-01.

Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

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Dr. Zahra Beheshti | AI in Engineering | Best Researcher Award

Dr. Zahra Beheshti | Islamic Azad University | Iran

Dr. Zahra Beheshti is an Assistant Professor at the Islamic Azad University, Najafabad Branch, with a distinguished background in computer engineering and artificial intelligence. She holds a B.Sc. and M.Sc. in Computer Engineering (Software) and a Ph.D. in Computer Science with a focus on Artificial Intelligence, followed by postdoctoral research in Soft Computing. Dr. Beheshti has made significant contributions to the field, including the compilation of the book Centripetal Accelerated Particle Swarm Optimization and Applications. Her academic excellence has been recognized through scholarships awarded to top international Ph.D. students. She is actively involved in knowledge dissemination, having conducted multiple workshops on advanced topics such as Machine Learning, Fuzzy Expert Systems and their application in algorithm parameter determination, and Introduction to Fuzzy Logic along with the Design and Implementation of Fuzzy Expert Systems. Her research output includes 34 documents, cited 1,865 times by 1,698 publications, with an h-index of 20, reflecting the significant impact of her work. Through her teaching, research, and publications, Dr. Beheshti demonstrates a strong commitment to advancing computational intelligence, fostering innovation, and mentoring the next generation of researchers in AI and soft computing, combining both academic rigor and practical application.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Z Beheshti, SMH Shamsuddin, A review of population-based meta-heuristic algorithms, Int. J. Adv. Soft Comput. Appl 5 (1), 1-35, 744 citations, 2013

  • H Abedinpourshotorban, SM Shamsuddin, Z Beheshti, DNA Jawawi, Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm, Swarm and Evolutionary Computation 26, 8-22, 414 citations, 2016

  • M Jafarzadegan, F Safi-esfahani, Z Beheshti, Combining Hierarchical Clustering approaches using the PCA Method, Expert Systems with Applications 137, 1-10, 156 citations, 2019

  • Z Beheshti, SM Shamsuddin, S Hasan, Memetic binary particle swarm optimization for discrete optimization problems, Information Sciences 299, 58-84, 129 citations, 2015

  • Z Beheshti, SMH Shamsuddin, CAPSO: centripetal accelerated particle swarm optimization, Information Sciences 258, 54-79, 120 citations, 2014

  • M Banaie-Dezfouli, MH Nadimi-Shahraki, Z Beheshti, R-GWO: Representative-based grey wolf optimizer for solving engineering problems, Applied Soft Computing 106, 1-28, 108 citations, 2021

 

 

Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

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Dr. Priya Tyagi | Sustainable Engineering | Best Researcher Award

Dr. Priya Tyagi | Sharda University | India

Dr. Priya Tyagi is a dedicated sustainable architect with extensive academic and professional expertise in sustainable design and rural housing development. She earned her Doctor of Philosophy from Malaviya National Institute of Technology, Jaipur, focusing on a decision-making framework for design quality assessment of rural houses in India, following her Master of Architecture in Sustainable Architecture from Deenbandhu Chhotu Ram University of Science and Technology, Murthal, and Bachelor of Architecture from Shri Ram Group of Colleges, Lucknow. She has actively contributed to research and practice in architecture, including a joint research project on municipal waste management at Massachusetts Institute of Technology, Boston, and holds professional credentials as a Green Rating for Integrated Habitat Assessment certified professional. Currently, she serves as Assistant Professor at Sharda School of Design, Architecture and Planning, Greater Noida, having previously held academic positions at Sanskar College of Architecture and Planning and practical experience with Shelter Architects and M/s Raj Architects and Builders. Dr. Tyagi has been recognized for her expertise through appointments as a reviewer for Scopus-indexed journals, including the Journal of Infrastructure, Policy and Development, and the Journal of Civil, Construction and Environmental Engineering. Her research output includes 9 documents with 6 citations and an h-index of 2, reflecting her growing impact in sustainable architecture, design quality assessment, and environmentally responsible building practices in India.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). Investigating rural housing quality indicators in the Indian scenario for inclusive imageability. Environment, Development and Sustainability, 26(10), 25609-25643.

Tyagi, P., Shrivastava, B., & Kumar, N. (2023). Towards creating inclusive villages: The types of rural settlements in India. ISVS e-Journal, 10(2), 91-106.

Bhyan, P., Tyagi, P., Doddamani, S., Kumar, N., & Shrivastava, B. (2023). Life cycle assessment of lightweight and sustainable materials. Lightweight and Sustainable Composite Materials, 117-142.

Tyagi, P., Shrivastava, B., & Kumar, N. (2024). A comprehensive investigation of rural and low-rise housing design quality: A thematic and bibliometric analysis. Journal of Housing and the Built Environment, 39(3), 1323-1353.

Tyagi, P., Shrivastava, B., & Kumar, N. (2025). Optimizing rural housing design quality: Indicators and parameters for comprehensive assessment. Environment, Development and Sustainability, 1-43.

Dr. Mulugundam Siva Surya | Advanced Composites | Best Researcher Award

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Dr. Mulugundam Siva Surya | Advanced Composites | Best Researcher Award

Dr. Mulugundam Siva Surya | GITAM University | India

Dr. Mulugundam Siva Surya is an accomplished academic and researcher currently serving as an Assistant Professor at GITAM University, Hyderabad, with a strong commitment to teaching and advancing research in mechanical and manufacturing engineering. He earned his PhD from JNTU Anantapur in 2022, following an M.Tech in Manufacturing Engineering from the National Institute of Technology, Warangal, and a B.Tech in Mechanical Engineering from KSRM College of Engineering, Kadapa. Dr. Mulugundam began his academic career as a Lecturer in the Mechanical Engineering Department at Rajiv Gandhi University, Hyderabad, from 2010 to 2013, and has since been dedicated to mentoring students and contributing to innovative research. With 557 citations from 421 documents, 33 publications, and an h-index of 16, his work reflects a strong impact in mechanical and materials engineering. [Scopus ID: 57194031396; ORCID: 0000-0003-2960-7298]. His research expertise includes composite materials, functionally graded materials, and thermal protection systems. He holds an Indian patent (No. 468849) for developing a novel method to fabricate layered Al7075/SiC functionally graded materials using powder metallurgy. He has also served as Co-Principal Investigator for two DRDO-funded projects under the CARS scheme, focusing on experimental and finite element design optimization of epoxy-based composites and AI-driven multi-scale simulations of ablative thermal protection systems for missile nose cones.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

Mulugundam, M. S., & Gugulothu, S. K. (2023). Fabrication, mechanical and wear characterization of silicon carbide reinforced aluminium 7075 metal matrix composite. Silicon, 14(5), 2023–2032.

Nutakki, P. K., Gugulothu, S. K., Ramachander, J., & Sivasurya, M. (2022). Effect of n-amyl alcohol/biodiesel blended nano additives on the performance, combustion and emission characteristics of CRDi diesel engine. Environmental Science and Pollution Research, 29(1), 82–97.

Ramachander, J., Gugulothu, S. K., Sastry, G. R. K., Panda, J. K., & Surya, M. S. (2021). Performance and emission predictions of a CRDI engine powered with diesel fuel: A combined study of injection parameters variation and Box-Behnken response surface methodology. Fuel, 290, 120069.

Surya, M. S., Prasanthi, G., & Gugulothu, S. K. (2021). Investigation of mechanical and wear behaviour of Al7075/SiC composites using response surface methodology. Silicon, 13(7), 2369–2379.

Surya, M. S., & Prasanthi, G. (2022). Effect of SiC weight percentage on tribological characteristics of Al7075/SiC composites. Silicon, 14(3), 1083–1092.

Mulugundam, T. V. N. Siva Surya. (2019). Synthesis and mechanical behaviour of (Al/SiC) functionally graded material using powder metallurgy technique. Materials Today: Proceedings, 18(7), 3501–3506.

Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

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Prof. Ouajdi Korbaa | AI in Engineering | Innovative Research Award

Prof. Ouajdi Korbaa | University of Sousse | Tunisia

Prof. Ouajdi Korbaa is a distinguished researcher and professor at the Institute of Computer Science and Communication Techniques, University of Sousse, Tunisia, and a member of the Modeling of Automated Reasoning Systems Laboratory. His research focuses on modeling, discrete optimization, scheduling, and artificial intelligence, contributing significantly to the development of advanced methodologies in these areas. He has supervised numerous Master’s and PhD students and actively participates in academic juries, reflecting his commitment to mentoring the next generation of researchers. Prof. Korbaa has authored 157 documents cited by 998 sources, achieving an h-index of 18, demonstrating his strong impact and influence in the field. His work integrates theoretical foundations with practical applications, advancing computational techniques for problem-solving and decision-making. Recognized for his expertise in optimization and AI, he has made substantial contributions to both the academic community and the broader field of computer science, fostering innovation in modeling and automated reasoning systems.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Nssibi, M., Manita, G., & Korbaa, O. (2023). Advances in nature-inspired metaheuristic optimization for feature selection problem: A comprehensive survey. Computer Science Review, 49, 100559.

  • Jemili, F., Meddeb, R., & Korbaa, O. (2024). Intrusion detection based on ensemble learning for big data classification. Cluster Computing, 27(3), 3771–3798.

  • Benzarti, S., Triki, B., & Korbaa, O. (2017). A survey on attacks in Internet of Things based networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

  • Meddeb, R., Jemili, F., Triki, B., & Korbaa, O. (2023). A deep learning-based intrusion detection approach for mobile Ad-hoc network. Soft Computing, 27(14), 9425–9439.

  • Abid, A., Jemili, F., & Korbaa, O. (2024). Real-time data fusion for intrusion detection in industrial control systems based on cloud computing and big data techniques. Cluster Computing, 27(2), 2217–2238.

  • Korbaa, O., Camus, H., & Gentina, J. C. (1997). FMS cyclic scheduling with overlapping production cycles. In Proceedings of the 18th International Conference on Application and Theory of Automation in Technology (pp. 1–10).

  • Lee, J., & Korbaa, O. (2004). Modeling and scheduling of ratio-driven FMS using unfolding time Petri nets. Computers & Industrial Engineering, 46(4), 639–653.

  • Meddeb, R., Triki, B., Jemili, F., & Korbaa, O. (2017). A survey of attacks in mobile ad hoc networks. In Proceedings of the 2017 International Conference on Engineering & MIS (ICEMIS) (pp. 1–7).

 

Mr. Bimal Kumar Dora | AI in Engineering | Best Researcher Award

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Mr. Bimal Kumar Dora | AI in Engineering | Best Researcher Award

Mr. Bimal Kumar Dora | Visvesvaraya National Institute of Technology | India

Mr. Bimal Kumar Dora is a dedicated researcher in Electrical Engineering, currently pursuing his Doctor of Philosophy at Visvesvaraya National Institute of Technology, Nagpur, after completing his Master of Technology in Control, Power and Electric Drives from the National Institute of Technology, Sikkim, and a Bachelor of Technology in Electrical Engineering from Biju Patnaik University of Technology, Odisha. He recently broadened his international research experience as a Visiting Researcher at the Montefiore Institute, University of Liège, Belgium, where he contributed to advanced studies in renewable energy integration and the development of global electricity grids. His doctoral research, titled Global Electricity Interconnection with Renewable Energy Generation, emphasizes methods such as the Enhanced Critical Time Window Framework, Weibull distribution analysis, and temporal variability indexing to identify and optimize renewable energy sites across Indian onshore and offshore regions. He has designed several innovative hybrid algorithms including Modified Pelican Optimization Algorithm, Novel Modified Pelican Driven Optimization Algorithm, Enhanced Pelican Foraging Algorithm, Enhanced Dragonfly and Moth Optimization Algorithm, Modified Reptile Optimization Algorithm, Modified Harris Hawk and Pelican Optimization Algorithm, and Enhanced Harris Hawk and Pelican Optimization Algorithm.  With 97 citations from 75 documents, 16 publications, and an index rating of 7, he is building a growing academic reputation that combines computational intelligence, renewable energy, and futuristic large-scale power system design.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  1. Dora, B. K., Rajan, A., Mallick, S., & Halder, S. (2023). Optimal reactive power dispatch problem using exchange market based butterfly optimization algorithm. Applied Soft Computing, 147, 110833.

  2. Halder, S., Bhat, S., & Dora, B. K. (2022). Inverse thresholding to spectrogram for the detection of broken rotor bar in induction motor. Measurement, 198, 111400.

  3. Halder, S., Bhat, S., & Dora, B. (2023). Start-up transient analysis using CWT and ridges for broken rotor bar fault diagnosis. Electrical Engineering, 105(1), 221–232.

  4. Halder, S., Dora, B. K., & Bhat, S. (2022). An enhanced pathfinder algorithm based MCSA for rotor breakage detection of induction motor. Journal of Computational Science, 64, 101870.

  5. Dora, B. K., Bhat, S., Halder, S., & Srivastava, I. (2024). A solution to multi objective stochastic optimal power flow problem using mutualism and elite strategy based pelican optimization algorithm. Applied Soft Computing, 158, 111548.

  6. Dora, B. K., Bhat, S., Halder, S., & Sahoo, M. (2023). Solution of reactive power dispatch problems using enhanced dwarf mongoose optimization algorithm. 2023 International Conference for Advancement in Technology (ICONAT), 1–6.

Dr. Mahmoud Alhalabi | Photonic Engineering | Best Researcher Award

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Dr. Mahmoud Alhalabi | Photonic Engineering | Best Researcher Award

Dr. Mahmoud Alhalabi | Istanbul Sabahattin Zaim University | Turkey

Dr. Mahmoud Alhalabi is a distinguished researcher and academic in Electrical and Electronics Engineering, specializing in Communication Engineering and Optical Communication Systems. He earned his PhD from Erciyes University in 2023, focusing on Peak-to-Average Power Ratio reduction using intelligent optimization techniques in optical communication systems. He also holds a Master’s degree in Electrical Engineering (Communication field) and a Bachelor’s degree in Electrical Engineering from the Islamic University of Gaza, where his research included performance improvement of Wavelength Division Multiplexer Passive Optical Networks. Dr. Alhalabi has accumulated broad academic and professional experience, serving as a Research Assistant at the Islamic University of Gaza, an Academician at Namma University of Science and Technology, and an Electrical Engineer at Al Zahra Municipality. Currently, he is a Postdoctoral Researcher at Istanbul Sabahattin Zaim University, contributing to cutting-edge research in optical communications. His work has resulted in 30 citations across 28 documents, 5 indexed publications, and an h-index of 3, demonstrating the impact and recognition of his research. Fluent in Arabic, Turkish, and English, he possesses strong cross-cultural communication and collaborative skills, enhancing both his academic and professional engagements. With a proven record of scholarly achievement, Dr. Alhalabi continues to advance knowledge in optical communication systems, intelligent optimization methods, and advanced electrical engineering technologies, positioning him as a forward-looking researcher with substantial potential for innovation and contribution to the global engineering community.

Profile: Scopus | Google Scholar | ORCID

Featured Publications 

  • Alhalabi, M., El-Nahal, F. I., & Taşpınar, N. (2019). Comparison of different modulation techniques for optical OFDM Intensity Modulation and Direct Detection IM/DD system. 2019 IEEE 7th Palestinian International Conference on Electrical and Computer Engineering (PICECE).

  • Taşpınar, N., & Alhalabi, M. (2021). Performance investigation of long-haul high data rate optical OFDM IM/DD system with different QAM modulations. Journal of Electrical Engineering, 72(3), 192–197.

  • El-Nahal, F. I., Alhalabi, M., & Husein, A. H. M. (2015). Wavelength Division Multiplexing Passive Optical Network (WDM-PON) technologies for future access networks. Journal of Engineering Research & Technology, 2(1).

  • Alhalabi, M. (2014). Performance Improvement of Wavelength Division Multiplexing Passive Optical Networks (WDM PONs) [Master’s thesis, Islamic University of Gaza].

  • Taşpınar, N., & Alhalabi, M. (2024). Peak-to-Average Power Ratio (PAPR) reduction using discrete invasive weed optimization (DIWO) in coherent detection optical OFDM (CO-OFDM) communication systems. Wireless Personal Communications.

  • Alhalabi, M., & Taşpınar, N. (2022). Performance investigation of bidirectional hybrid long-haul optical IM/DD OFDM WDM-PON using OOK-RSOA remodulation. Mühendislik Bilimleri ve Araştırmaları Dergisi, 4(1), 54–61.

Prof. Dr. Rehan Ahmad Khan | Structural Engineering | Best Researcher Award

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Prof. Dr. Rehan Ahmad Khan | Structural Engineering | Best Researcher Award

Prof. Dr. Rehan Ahmad Khan | Aligarh Muslim University | India

Prof. Dr. Rehan Ahmad Khan is a distinguished Professor of Civil Engineering at the Zakir Husain College of Engineering and Technology, Aligarh Muslim University. He earned his Ph.D. from the Indian Institute of Technology Delhi with a specialization in the reliability analysis of cable-stayed bridges under earthquake forces, and has since built expertise in reliability analysis, recycled aggregate concrete, self-healing and bacterial concrete, structural dynamics, and earthquake engineering. His teaching spans both undergraduate and postgraduate programs, covering areas such as strength of materials, structural analysis, reinforced concrete design, earthquake and wind engineering, disaster preparedness, advanced construction materials, and applied numerical methods. He has undertaken several consultancy projects, including structural audits, third-party inspections of buildings, bridges, retaining walls, wastewater treatment plants, and overhead tanks, contributing to engineering practice and safety standards. A recognized reviewer for reputed journals under Springer and Elsevier, he has authored 30 publications with 218 citations and an h-index of 8, reflecting his research impact and academic contributions to civil engineering.

Profile: Scopus

Featured Publications

Khan, R. A., (2025) Investigation of microstructural characterization, strength and durability of self-healing self-compacting conventional concrete Structures

Khan, R. A., (2025) Reliability analysis of nuclear power plant subjected to earthquake shocks Iranian Journal of Science and Technology, Transactions of Civil Engineering

Khan, R. A., (2024) Mechanical and microstructural performance of bacterial self-compacted concrete incorporating mineral admixtures Innovative Infrastructure Solutions