Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

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Dr. Somayeh Bahramnejad | Survival Analysis and Reliability | Editorial Board Member

Sirjan University of Technology | Iran

Dr. Somayeh Bahramnejad is an accomplished Assistant Professor in the Department of Computer Engineering at Sirjan University of Technology, recognized for her scholarly impact and multidisciplinary contributions across reliability engineering, machine learning, image processing, computer architecture, and computer networks. She completed her B.S. degree in Computer Hardware Engineering at Ferdowsi University of Mashhad, earned her M.Sc. in Computer Architecture from Amirkabir University of Technology, and later obtained her Ph.D. in Computer Architecture from the University of Isfahan. With a steadily expanding academic portfolio, she has published influential research in reputable international journals, including Microelectronics Reliability, SN Computer Science, Computing, Computers & Electrical Engineering, and Scientia Iranica, contributing to a total of six peer-reviewed journal publications. According to her Google Scholar profile, she has accumulated 29 citations, an h-index of 3, and an i10-index of 1, demonstrating the visibility and growing influence of her research contributions. Dr. Bahramnejad has significantly advanced the field through innovative work on reliability improvement of SRAM-based FPGAs, reliability analysis of CR-VANETs, and the application of machine-learning methods for evaluating digital circuit reliability. She provides academic consultancy to seven M.Sc. students, supporting high-quality research, technical development, and scholarly productivity. Her professional presence on Google Scholar and ORCID ensures transparent documentation of her academic achievements and research outputs. Committed to interdisciplinary collaboration and impactful scientific inquiry, she focuses on designing robust, scalable, and reliable computing systems informed by both theoretical insight and practical need. With her dedication to excellence, mentorship, innovation, and long-term contributions to engineering research, Dr. Bahramnejad stands as a strong candidate for distinctions such as the Reliability Analysis Award, Best Researcher Award, Best Paper Award, Women Researcher Award, and Innovative Research Award, reflecting her potential for continued leadership within the global research community.

Profiles: Scopus | Orcid

Featured Publications

Bahramnejad, S. (2025). A fuzzy-arithmetic-based reliability assessment model for digital circuits (FARAM-DC). Microelectronics Reliability.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2024). An LSTM-based method for automatic reliability prediction of cognitive radio vehicular ad hoc networks. SN Computer Science.

Bahramnejad, S., Movahhedinia, N., & Naseri, A. (2023). A deep learning method for automatic reliability prediction of CR-VANETs. Research Square.

Bahramnejad, S., & Movahhedinia, N. (2022). A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): Case study, cognitive radio vehicular networks with drivers. Computing.

Bahramnejad, S., & Movahhedinia, N. (2022). A reliability estimation framework for cognitive radio V2V communications and an ANN-based model for automating estimations. Computing.

BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

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Mr. BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

SRM Institute of Science and Technology (SRMIST) | India

Mr. Bhaskar A is a highly accomplished academic and industry professional with over two decades of experience in mechanical engineering, manufacturing, and Agile methodologies. Currently serving as an Assistant Professor (Selection Grade) and Scrum Master at SRM Institute of Science and Technology (SRMIST), Ramapuram, he has played a pivotal role in integrating Agile practices into engineering education, mentoring teams, and enhancing organizational productivity. His educational journey includes an MBA from Annamalai University, an M.E. in Manufacturing Engineering from Madras Institute of Technology, and a B.E. in Mechanical Engineering from the University of Madras, and he is presently pursuing a part-time Ph.D. in Lean Manufacturing from Anna University. Over his career, he has held positions as an Assistant Professor at several engineering colleges and worked in industry roles including Production Engineer, contributing to process improvements and team management. Dr. Bhaskar has made significant research contributions in lean manufacturing, mechanical properties of materials, and the application of Agile methodologies, with numerous publications in journals and conferences. Beyond research and teaching, he is dedicated to continuous professional development, having completed multiple Faculty Development Programs, workshops, and online courses in project management, digital manufacturing, materials science, and other emerging technologies, reflecting his commitment to advancing knowledge and fostering innovation in engineering education.

Profiles:  Google Scholar | Linked In

Featured Publications

Alexpandian, A. S., Rajesha, M., Loganathan, P., Hariram, V., & [Y.R.]. (2023). Optimization of machining parameters to improve surface quality in the abrasive water jet cutting of AA6351 aluminium alloy. International Journal of Vehicle Structures & Systems, 15(4), 547–551.

Devaraju, A. B. A. (2025). Integrated ERP lean model for quality enhancement and operational excellence in SME based automotive mould manufacturing. Scientific Reports, 15(35979), 1–16.

Jeffrey, V. P. S. S. J. A., Govindaraj, S., Mahesh, R., Bhaskar, A., Arunkumar, K., & [R.]. (2025). Influence of Fe2O3 nanoparticle-infused waste cooking oil biodiesel on the emission, performance, and combustion aspects towards a cleaner environment. Journal of Environmental Nanotechnology, 14(3), 466–476.

Yoganjaneyulu, G., Perumal, V. S., Sivasankaran, S., Annamalai, B., & Niranjan, T. (2025). Strategic method to enhancing the formability of Nitinol foils via micro-incremental sheet forming processes and evaluation of structure–property. Metals and Materials International, 1–15.

Hepsi, B. M. J., Bhaskar, A., Rekha, R. S., & Vasanthi, P. (2024). Wear behavior of hemp-flax-glass fibre hybrid composite material. Advances in Additive Manufacturing Technologies, 75–79.

Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

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Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.

Martin Ferrand| Statistical Modeling and Simulation | Best Researcher Award

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Dr. Martin Ferrand | Statistical Modeling and Simulation | Best Researcher Award

EDF R&D | France

Dr. Martin Ferrand is an accomplished researcher and engineer whose academic and professional journey has been defined by excellence in fluid dynamics, smoothed particle hydrodynamics (SPH), and computational modelling, and he is currently affiliated with the University of Manchester in the MACE Department, where he has undertaken advanced research as part of his MPhil studies, focusing on SPH with the specialized software SPARTACUS developed at EDF R&D; his academic foundations were laid at École des Ponts ParisTech, one of France’s most prestigious engineering institutions, where he specialized in mechanics, fluid mechanics, and data processing, complemented by intensive preparatory studies in advanced mathematics and physics at Lycée du Parc, Lyon, following his French Scientific Baccalaureate with distinction in 2004, which marked the start of a career shaped by intellectual rigor and scientific curiosity. Professionally, Ferrand has gained diverse and impactful experience, including at EDF R&D in Chatou, France, where he developed turbulence models incorporating buoyancy effects and enhanced the hydrodynamic reproduction of the Berre lagoon using TELEMAC3D, and at Imperial College London, where he expanded his expertise into stochastic processes by designing models to reproduce rainfall patterns for optimizing sewage infrastructure, while his immersion at Bouygues Construction gave him early exposure to industry practices, broadening his adaptability. His academic impact is evident through a strong research record comprising 70 scholarly documents, collectively cited 749 times, with an h-index of 11, reflecting the recognition, influence, and sustained relevance of his work in computational and environmental fluid mechanics; his expertise extends across theoretical, computational, and applied domains, establishing him as a versatile contributor to advancing both scientific understanding and engineering practice. In addition to his technical accomplishments, Ferrand is multilingual, fluent in French and English with working knowledge of German, enabling him to collaborate effectively in international research environments, while his interests outside academia, including football, cooking, and model train construction, showcase his creativity, discipline, and appreciation for teamwork, all of which complement his professional excellence. Overall, Martin Ferrand stands as a dedicated scholar and engineer whose combination of intellectual achievement, technical expertise, and international experience continues to make a significant contribution to his field and positions him as a rising figure in the global scientific community.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

“Unified semi‐analytical wall boundary conditions for inviscid, laminar or turbulent flows in the meshless SPH method”

“Unified semi-analytical wall boundary conditions applied to 2-D incompressible SPH”

“An innovative method based on CFD to simulate the influence of photovoltaic panels on the microclimate in agrivoltaic conditions”

“A time-step-robust algorithm to compute particle trajectories in 3-D unstructured meshes for Lagrangian stochastic methods”

“Unsteady open boundaries for SPH using semi-analytical conditions and Riemann solver in 2D”