Prof. Sharmila S P | Computer Engineering | Editorial Board Member

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Prof. Sharmila S P | Computer Engineering
| Editorial Board Member

Siddaganga Institute of Technology Tumakuru | India

Prof. Sharmila S P the research work focuses on advancing cybersecurity through AI-driven, explainable, and resilient detection mechanisms capable of addressing modern, highly obfuscated threats. Central contributions include the development of memory-forensic-based feature extraction techniques that enhance the transparency and interpretability of obfuscated malware detection models, enabling isolated family distinction and reducing false positives. The work explores multi-class classification frameworks for malware analysis, leveraging machine learning paradigms to identify sophisticated adversarial behaviors across diverse threat categories. Additional research investigates Hidden Markov Model–based intrusion detection, employing a randomized Viterbi algorithm to strengthen anomaly recognition in dynamic network environments. Studies on cyber-attack prediction further analyze prevalent forecasting techniques to improve proactive defense capabilities. Complementary research examines Android malware behavior, distributed ledger applications for secure banking operations, and lightweight authentication mechanisms rooted in keystroke dynamics for user verification. With a strong emphasis on AI, machine learning, GNNs, NLP-driven analysis, reverse engineering, and volatile memory forensics, the overall body of work contributes toward building robust, explainable, and scalable cybersecurity systems capable of safeguarding digital infrastructures against evolving threats in cloud environments, embedded systems, mobile platforms, and large-scale networked ecosystems.

 Profile:  Orcid 

Featured Publications

Sharmila, S. P., Gupta, S., Tiwari, A., & Chaudhari, N. S. (2025). Unveiling evasive portable documents with explainable Kolmogorov–Arnold networks resilient to generative adversarial attacks. Applied Soft Computing, 138, 113537. https://doi.org/10.1016/j.asoc.2025.113537

Sharmila, S. P., Gupta, S., Tiwari, A., & Chaudhari, N. S. (2025). Leveraging memory forensic features for explainable obfuscated malware detection with isolated family distinction paradigm. Computers and Electrical Engineering, 121, 110107. https://doi.org/10.1016/j.compeleceng.2025.110107

Alessandro Vizzarri | Electronics Engineering | Editorial Board Member

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Prof. Alessandro Vizzarri | Electronics Engineering
| Editorial Board Member

University of Rome Tor Vergata | Italy

Prof. Alessandro Vizzarri is a distinguished researcher and academic in telecommunications engineering, intelligent networks, and artificial intelligence. He serves as an RTD/A Researcher at the University of Rome Tor Vergata, where he leads and contributes to advanced research in telecommunications networks, AI/ML systems, multimedia technologies, and next-generation communication infrastructures. He also teaches courses in Radiomobile Multimedia Networks, Telecommunications and Internet, and Artificial Intelligence.With extensive experience across academia, research institutes, and industry, Prof. Vizzarri’s work encompasses AI-driven network optimization, edge computing, satellite–terrestrial integration, 5G/LEO hybrid systems, and cybersecurity. He has held key technical and management roles in major national and European research initiatives, including projects funded by EUSPA, ESA, Horizon 2020/Horizon Europe, and the Italian Ministry of Enterprises. His contributions span diverse sectors such as autonomous mobility, railway signalling, satellite communications, immersive digital heritage, and smart city infrastructure.Beyond research, Prof. Vizzarri is actively involved in innovation management and technology transfer. He delivers training and seminars on AI/ML, digital transformation, intellectual property strategies, and research project development. His career includes substantial achievements in system architecture, platform design, multidisciplinary coordination, and the development of future-ready communication technologies.

 Profile:  Scopus 

Featured Publications

Andre Guimaraes | Emerging Technologies & Innovations | Editorial Board Member

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Mr. Andre Guimaraes | Emerging Technologies & Innovations | Editorial Board Member

University of Beira Interior | Portugal

Mr. André Guimarães is a Portuguese researcher and academic specializing in Industrial Engineering, Digital Transformation, and Industry 4.0. He is currently pursuing a Ph.D. in Industrial Engineering and Management at the University of Beira Interior, where he also contributes as a Researcher at the Electromechatronic Systems Research Centre. In addition, he collaborates with the Centre for Research in Digital Services at the Polytechnic Institute of Viseu, where he serves as an Invited Assistant Lecturer. With a strong background in Mechanical Engineering and Industrial Management, supported by extensive training in Lean, Quality Management, Six Sigma, and digital technologies, Mr. Guimarães has developed a multidisciplinary expertise that bridges engineering practice and technological innovation. His professional experience includes more than a decade in production leadership roles within the metal manufacturing sector, along with consultancy work in quality systems and organizational improvement. He has authored and co-authored numerous scientific publications, including articles in international journals, conference papers, and a technical book. His research focuses on Industry 4.0 readiness, digital maturity assessment, asset management, process optimization, and advanced manufacturing practices. A member of the Portuguese Order of Engineers, he is also a recipient of an FCT Research Fellowship and actively contributes to national and international scientific events.

 Profile:  Orcid | Scopus 

Featured Publications

Pereira, M. T., Pereira, M. G., Ferreira, F. A., Silva, F. G., & Guimarães, A. (2026). A hybrid strategy for oven optimization in aerospace manufacturing: Lean principles and mathematical modelling. In [Book title unavailable] (Chapter 37). https://doi.org/10.1007/978-3-032-05610-8_37

Pereira, M. T., Gabriel, N. M., Pereira, M. G., Ramos, F. R., & Guimarães, A. (2026). Enhancing third-party logistics efficiency: A digital approach to transport costing. In [Book title unavailable] (Chapter 14). https://doi.org/10.1007/978-3-032-07144-6_14

Pereira, M. G., Pereira, M. T., Fernandes, M. A., Silva, F. G., Guimarães, A., & Ferreira, F. A. (2026). Optimization of metal sheet cutting processes using integer linear programming: Reducing waste and enhancing production efficiency. In [Book title unavailable] (Chapter 65). https://doi.org/10.1007/978-3-032-05610-8_65

Sarra Senouci | Mechanical Engineering | Editorial Board Member

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Mrs. Sarra Senouci | Mechanical Engineering
| Editorial Board Member

University of Electronic Science and Technology of China | Algeria

Mrs. Sarra Senouci the research work centers on advanced cryptographic systems, network security, and intelligent detection frameworks, with a strong emphasis on chaotic dynamics, pseudo-random number generation, and secure data transmission. The studies include the development of a novel pseudo-random number generator (PRNG) for fiber optic communication, leveraging nonlinear chaotic behavior to enhance cryptographic strength and improve resistance to prediction attacks. Additional contributions explore a chaotic-based cryptographically secure PRNG designed for high-performance applications requiring strong randomness and low computational overhead. In the domain of cybersecurity, the research introduces deep convolutional neural network architectures for high-precision and real-time DDoS attack detection within software-defined networking environments. This includes models optimized for both feature extraction and rapid classification to mitigate large-scale network threats. Further advancements incorporate feature engineering and ensemble learning techniques to achieve robust, scalable, and resilient DDoS detection frameworks capable of adapting to evolving attack patterns. Earlier academic work includes the design and construction of autonomous sensor networks and the implementation of chaotic systems on FPGA platforms, highlighting strong integration of hardware, communication technologies, and nonlinear system modeling across multiple layers of modern electronic and communication systems.

 Profile:  Google Scholar 

Featured Publications

Senouci, S., Madoune, S. A., Senouci, M. R., Senouci, A., & Tang, Z. (2025). A novel PRNG for fiber optic transmission. Chaos, Solitons & Fractals, 192, 116038. https://doi.org/10.1016/j.chaos.2025.116038

Madoune, S. A., Senouci, S., Dingde, J., & Senouci, A. (2024). Deep convolutional neural network-based high-precision and speed DDOS detection in SDN environments. 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 1–6. https://doi.org/10.1109/iccwamtip64812.2024.10873789

Madoune, S. A., Senouci, S., Setitra, M. A., & Dingde, J. (2024). Toward robust DDOS detection in SDN: Leveraging feature engineering and ensemble learning. 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 1–7. https://doi.org/10.1109/iccwamtip64812.2024.10873648

Alla Solovyeva | Specialized and Interdisciplinary Fields | Best Researcher Award

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Dr. Alla Solovyeva | Specialized and Interdisciplinary Fields | Best Researcher Award

All-Russian N.I.Vavilov Research Institute of Plant Genetic Resources, Ministry of Science and Superior Education | Russia

Dr. Alla Solovyeva research conducted at the Department of Biochemistry and Molecular Biology, All-Russian N.I. Vavilov Institute of Plant Genetic Resources (VIR), focuses on the biochemical characterization and evaluation of global plant genetic resources, with an emphasis on vegetable crops. The work involves comprehensive biochemical screening of cultivated and wild plant accessions to identify valuable genetic materials for breeding and practical applications in agriculture, medicine, and food industries. Research directions include studying nutrient, antinutrient, and biologically active substances in major and minor vegetable crops such as beet, cabbage, tomato, cucumber, pumpkin, lettuce, and amaranth. Advanced analytical techniques including spectrophotometry, gas-liquid chromatography, and high-performance liquid chromatography (HPLC) are utilized for the extraction, purification, and identification of key biochemical compounds. Investigations explore the genetic diversity, nutritional value, and bioactive potential of these crops, focusing on the accumulation of anthocyanins, carotenoids, glucosinolates, and other phytochemicals. The research aims to uncover genetic mechanisms regulating the biosynthesis of these compounds and their role in plant quality, stress tolerance, and pest resistance. This work contributes to understanding the biochemical basis of genetic biodiversity and supports modern breeding programs targeting improved crop quality, biofortification, and sustainable agricultural development.

 Profile:  Scopus | Orcid 

Featured Publications

Solovyeva, A. E. (2025). Bioactive compounds in Jerusalem artichoke (Helianthus tuberosus L.) tubers from the VIR collection. Proceedings on Applied Botany, Genetics and Breeding.

Solovyeva, A. E. (2025). Biochemical characteristics of tea from amaranth leaves (Amaranthus cruentus L.) of the ‘Frant’ variety. Food Systems.

Mohamed Gomaa | Electric | Best Researcher Award

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Prof. Mohamed Gomaa | Electric
| Best Researcher Award

National Research Centre | Egypt

Prof. Mohamed Gomaa’s research focuses on the electrical and geophysical characterization of rocks, minerals, and natural composites, with particular emphasis on modeling and simulation of subsurface materials to understand their physical and dielectric properties under varying environmental conditions. His studies advance knowledge in the field of applied geophysics by exploring the influence of grain texture, porosity, mineral composition, temperature, and frequency-dependent electrical responses on the behavior of geological formations. A significant aspect of his work involves developing predictive models to assess the AC and DC electrical properties of heterogeneous mixtures, composite media, phosphate-bearing formations, and sand-hematite mixtures for applications in mineral exploration, groundwater assessment, and environmental geoscience. His research contributes to enhancing the accuracy of petrophysical interpretation, improving mixture laws, and understanding conductivity mechanisms within dry and saturated geological samples. By investigating grain size effects, dielectric relaxation, and the influence of temperature on electrical conductivity, his studies provide critical insights into subsurface characterization and resource evaluation. His published contributions in international journals present novel methodologies in laboratory simulation and field data analysis, offering practical frameworks for interpreting geoelectric signals and identifying economically valuable mineral deposits. His work on synthetic and natural geological mixtures establishes advanced correlations between microstructural properties and macroscopic electrical responses, supporting sustainable exploration strategies and contributing to advancements in Earth materials science and applied geophysics.

 Profile:  Scopus 

Featured Publications

Gomaa, M. M. (2025). Temperature and AC electrical properties effects on phosphate natural mixture, Abu Tartur plateau, Western Desert, Egypt. Scientific Reports, 15(1), 27952. https://doi.org/10.1038/s41598-025-09313-3

Gomaa, M. M. (2024). Grain size effect on electrical properties of dry friable sand. European Physical Journal Special Topics. [Details such as volume, issue, pages, and DOI were not provided; please provide if available for completion.]

Gomaa, M. M. (2023). Electrical properties of hematite and pure sand synthetic homogeneous mixture. Applied Water Science. [Volume, issue, page numbers, and DOI needed for full citation.]

Gomaa, M. M. (2022). Frequency response of electrical properties of some granite samples. Journal of the Earth and Space Physics. [Volume, issue, pages, and DOI needed for full reference.]

Chaitanya Kumar Mankala | Machine Learning | Best Computer Engineering Award

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Dr. Chaitanya Kumar Mankala | Machine Learning
| Best Computer Engineering Award

Villanova University | United States

Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.

 Profile:  Orcid | Google Scholar 

Featured Publications

Mankala, C. K., & Silva, R. J. (2025). Sustainable real-time NLP with serverless parallel processing on AWS. Information, 16(10). https://doi.org/10.3390/info16100903

Mankala, C. K. (2025). Evolutionary artificial neuroidal network using serverless architecture [Doctoral dissertation].

Mankala, C. K., & Silva, R. (2023, November 16). Next generation artificial neural network. In Proceedings of the ICEHTMC Conference.

Majid Aghababaie | Power Electronics | Best Researcher Award

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Assist. Prof. Dr. Majid Aghababaie | Power Electronics
Science | Best Researcher Award

Iran University of Science and Technology | Iran

Assist. Prof. Dr. Majid Aghababaie, a distinguished scholar in Electrical and Electronic Engineering, currently serves as a faculty member at Imam Khomeini Maritime Sciences University, Noshahr, Iran, while pursuing his Ph.D. at the Iran University of Science and Technology (IUST), Tehran. He obtained his B.Sc. and M.Sc. degrees in Electrical and Electronic Engineering from the Sharif University of Technology in 1992 and 1995, respectively. With over two decades of teaching and research experience, Dr. Aghababaie has made impactful contributions to the fields of digital signal processing and power electronics. His ongoing research focuses on electrical propulsion systems for ships, contributing to advancements in energy-efficient maritime technology. He has also led consultancy and industrial projects, including the development of industrial drivers and soft-starters for electrical motors, demonstrating strong integration of academic insight with industrial applications. Dr. Aghababaie has authored several papers in reputable journals, including the Iranian Journal of Science and Technology Transactions of Electrical Engineering, where his article “A Common Grounded High Step-Up Switched Boost Converter with Low Voltage Stress on Semiconductors” reflects his expertise in power converter design. His Scopus profile (ID: 25633940700) lists 7 publications, 10 citations from 10 documents, and an h-index of 2, underscoring his growing research influence and academic excellence in electrical engineering innovation.

 Profile:  Orcid | Scopus 

Featured Publication

Aghababaie, M. (2025). A common grounded high step-up switched boost converter with low voltage stress on semiconductors. Iranian Journal of Science and Technology, Transactions of Electrical Engineering. https://doi.org/

Zaharia Marius | Materials Science | Best Researcher Award

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Dr. Zaharia Marius | Materials Science | Best Researcher Award

Petru Poni Institute of Macromolecular Chemistry | Romania

Dr. Zaharia Marius is a distinguished Scientific Researcher at the “Petru Poni” Institute of Macromolecular Chemistry in Iași, Romania, where he conducts pioneering research in polymer and organic synthesis, ion-exchanger materials, and environmental chemistry. His scientific expertise encompasses the synthesis and characterization of functional ion-exchangers for water purification and medical applications, as well as the development of composite materials based on CaCO₃ and multilayer polyelectrolyte coatings for advanced functional surfaces. He has extensive experience in analytical and instrumental techniques, including HPLC, FT-IR, UV-Vis, XRD, GC-TCD, and atomic absorption spectrometry. Dr. Zaharia has authored or co-authored 32 ISI-indexed journal articles (12 in Q1 and 12 in Q2 journals), 8 conference proceedings papers, 39 oral presentations, 31 posters, and holds 1 patent. His scholarly impact is reflected in 274 citations and an h-index of 13, underlining the significance of his work. He has been involved in eight national research grants, one international PNRR project, and served as director of a national grant (WHIERTARN, 2019–2022) focused on wastewater heavy metal ion decontamination. Recognized with multiple awards for oral and poster presentations and excellence in research, Dr. Zaharia continues to advance innovative solutions for environmental sustainability and green chemistry. ORCID: 0000-0002-4964-8874.

 Profile:  Orcid 

Featured Publications

  1. Bucatariu, F., Petrila, L.-M., Ciobanu, T.-A., Zaharia, M.-M., & Mihai, M. (2025). Dynamic ultra-fast sorption/desorption of indigo carmine onto/from versatile core-shell composite microparticles. Applied Sciences, 15(19), 10725. https://doi.org/10.3390/app151910725

  2. Zaharia, M.-M., Bucatariu, F., Karayianni, M., Lotos, E.-D., Mihai, M., & Pispas, S. (2024). Synthesis of thermoresponsive chitosan-graft-poly(N-isopropylacrylamide) hybrid copolymer and its complexation with DNA. Polymers, 16(10), 1315. https://doi.org/10.3390/polym16101315

  3. Mihai, M., Lotos, E.-D., Zaharia, M.-M., Bucatariu, F., & Vasiliu, A.-L. (2024). Alginate-based composite hydrogels formed by in situ CaCO₃ crystallization. Crystal Growth & Design, 24(3), Article 3c01518. https://doi.org/10.1021/acs.cgd.3c01518

  4. Pelin, I. M., Popescu, I., Calin, M., Rebleanu, D., Voicu, G., Ionita, D., Zaharia, M.-M., Constantin, M., & Fundueanu, G. (2023). Tri-component hydrogel as template for nanocrystalline hydroxyapatite deposition using alternate soaking method for bone tissue engineering applications. Gels, 9(11), 905. https://doi.org/10.3390/gels9110905

  5. Zaharia, M.-M., Bucatariu, F., Vasiliu, A.-L., & Mihai, M. (2023). Versatile zwitterionic beads for heavy metal ion removal from aqueous media and soils by sorption and catalysis processes. ACS Applied Polymer Materials, 5(10), 8183–8193. https://doi.org/10.1021/acsapm.3c01375

Liangwen Qi | Nuclear Engineering | Best Research Article Award

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Assoc. Prof. Dr. Liangwen Qi | Nuclear Engineering  | Best Research Article Award

Lanzhou Jiaotong University | China

Assoc. Prof. Dr. Liangwen Qi, Ph.D., earned his doctorate in Plasma Physics from Dalian University of Technology in 2022 and currently serves as an active researcher in the field of high-power pulsed discharge and plasma-material interaction. His primary research interests encompass the control of magnetohydrodynamic (MHD) instability in coaxial gun high-current pulse discharge plasma, the interaction between high-energy-density plasma and materials, and the generation of spheromak plasma using magnetized coaxial guns. Over the past five years, Dr. Qi has made significant contributions to the advancement of plasma physics, publishing more than ten SCI-indexed papers in prestigious international and domestic journals, including Plasma Physics and Controlled Fusion, Physics of Plasmas, Journal of Plasma Physics, Fusion Engineering and Design, and Chinese Journal of Physics. Notably, six of these works were authored as first author, demonstrating his leadership in innovative plasma diagnostics and experimental methodologies. His representative paper, “Characteristics of a Repetitive ELM-like Pulsed Plasma Source and Its Damage Effects on Tungsten Target,” exemplifies his commitment to understanding plasma-material interactions relevant to fusion energy systems. Dr. Qi has also filed two national patents as the first inventor, reflecting the practical impact of his work. With 41 citations across 29 documents and an h-index of 4, his research continues to contribute meaningfully to the development of advanced plasma technologies.

 Profile: Scopus |  Orcid 

Featured Publications

Qi, L., Liu, S., Wen, X., Du, M., Guo, D., & Ren, C. (2026). Characteristics of a repetitive ELM-like pulsed plasma source and its damage effects on tungsten target. Fusion Engineering and Design. https://doi.org/10.1016/j.fusengdes.2025.115456

Du, M.-Q., Wei, W.-F., Ding, Z.-F., Qi, L.-W., Wen, X.-D., Xia, G.-Q., & Sun, B. (2025, September 1). Temporal evolution of harmonic characteristics in atmospheric pressure pulsed RF discharges. Physics of Plasmas. https://doi.org/10.1063/5.0272472

Liu, S., Liu, K., Qi, L., & Yang, L. (2025, April 8). Synthesis of high-entropy oxide nanopowders with different crystal structures by electrical explosion of wires. Nanomaterials. https://doi.org/10.3390/nano15080571

Qi, L., Song, J., Zhao, F., Yu, S., Zhao, C., Yan, H., & Wang, D. (2024, October). Experimental study on the formation and evolution of unconfined counter-helicity spheromaks merging using magnetized coaxial plasma gun. Journal of Plasma Physics. https://doi.org/10.1017/S0022377824000813

Liu, S., Qi, L., Zhang, G., Xiao, D., & Yu, S. (2024, October 28). Effects of discharge parameters on plasma acceleration and transmission characteristics of a coaxial gun operated in gas-prefilled mode. Journal of Applied Physics. https://doi.org/10.1063/5.0229983