Ali Reza Keivanimehr | AI in healthcare | Best Researcher Award

Posted on 19/02/202519/02/2025 by 21b4bddf87157652317827146367558f

Mr.Ali Reza Keivanimehr | AI in healthcare
| Best Researcher Award

Mr. Ali RezaKeivanimehr , Amirkabir University of Technology (Tehran’s Polytechnic), Iran.

Ali Reza Keivanimehr is an exceptional early-career researcher with a solid academic foundation, a promising research trajectory in machine learning applications for healthcare, and strong technical expertise. His combination of research, teaching, and technical projects highlights a well-rounded profile. His contributions, especially in the use of TinyML for cardiovascular diagnosis, are commendable and align with global health priorities.

Publication Profile

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Education :

Master of Science in Information Technology Engineering – Internet of Things (IoT) (2022 – 2025)Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranRanked 403rd in QS World University Rankings 2024GPA: 3.53/4 (17.48/20) – 3rd highest in 2022 faculty entranceThesis: Applications of TinyML in Prediction and Diagnosis of Cardiovascular DiseasesSupervisor: Dr. Mohammad Akbari | Advisor: Dr. Abbas AhmadiBachelor of Science in Computer Engineering – Software Engineering (2018 – 2021)Imam Khomeini International University of Qazvin, Qazvin, IranProject: Designing a Software Interface for Industrial Machinery Maintenance

Experience :

Research Assistant (2022 – Present)
Data Science Lab (DSLab), Amirkabir University of Technology, Tehran, IranConducting research on TinyML and edge intelligence applications in cardiovascular disease prediction.Teaching Assistant — Machine Learning and Pattern Recognition (2024 – 2025)Amirkabir University of Technology, Tehran, IranAssisted in course instruction, project supervision, and student evaluations under Dr. Alireza Rezvanian.Teaching Assistant — Data Structure and Algorithms (2019 – 2020)
Imam Khomeini International University of Qazvin, Qazvin, IranSupported coursework delivery, assignments, and exam preparations under Morteza Mohammadi Zanjireh.

Research Focus :

Natural Language Processing (NLP)Graph Neural NetworksEdge IntelligenceExplainable Artificial Intelligence (XAI)Generative Adversarial Networks (GANs)Dr. Keivanimehr’s research centers on Tiny Machine Learning (TinyML) and edge intelligence, with a specific emphasis on their applications in cardiovascular disease monitoring. He explores the deployment of machine learning models on low-power, resource-limited devices to facilitate real-time analytics and pervasive monitoring for patients with cardiac anomalies.

Skills and Expertise:

As a research assistant, Dr. Keivanimehr has developed expertise in machine learning, classification, and supervised learning. His technical proficiency includes a focus on computational health and biomedical applications, particularly in the context of resource-constrained devices.Programming: PythonMachine Learning Frameworks: PyTorch, TensorFlowBig Data Tools: Apache SparkLanguages: TOEFL iBT (Score: 109 | Reading: 28 | Listening: 30 | Speaking: 26 | Writing: 25)

Awards:

48th Rank among 5000+ participants, National Entrance Exam for Master Studies in IT Engineering (2022)3rd Rank in IT Engineering Master’s cohort based on GPA (2022 – Present)Full Master’s Scholarship: Awarded for excellence in national entrance exams; covers tuition, dormitory, and partial food expenses (2022 – Present)Full Bachelor’s Scholarship: Granted for top performance in national entrance exams; included tuition, accommodation, and meal support (2018 – 2021)

Publication

Keivanimehr, A., & Akbari, M. (2024). TinyML and Edge Intelligence Applications in Cardiovascular Disease: A Survey. Computers in Biology and Medicine. DOI: 10.1016/j.compbiomed.2025.109653

Conclusion

Ali Reza Keivanimehr is a suitable candidate for the Best Researcher Award. His strong academic record, impactful research, and consistent growth in machine learning and edge intelligence demonstrate his potential as a leading researcher in his field. With further international exposure and expanded publication efforts, he is poised to make significant contributions to both academia and industry.

Saba Inam | machine learning | Women Researcher Award

Posted on 06/02/202506/02/2025 by 21b4bddf87157652317827146367558f

Dr.Saba Inam |machine learning| Women Researcher Award

Dr Saba InamFatima Jinnah women university, The Mall, Rawalpindi, Pakistan.

Dr. Saba Inam is a lecturer in the Department of Mathematical Sciences at Fatima Jinnah Women University in Rawalpindi, Pakistan. She earned her PhD in Algebraic Cryptography from the Capital University of Science and Technology, completing her studies between February 2014 and January 2019. Her research interests include Algebraic Number Theory, Algebraic Cryptography, Applied Cryptography, image encryption, Cloud Computing, Machine Learning, and Deep Learning. Dr. Inam has contributed to over 20 publications, accumulating 247 citations, and her work has garnered more than 3,367 reads. Notably, she co-authored the article “An efficient image encryption algorithm using 3D-cyclic Chebyshev map and elliptic curve,” published in November 2024.

Publication Profile

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Education :

Dr. Saba Inam holds a PhD in Mathematics from Capital University of Science and Technology (CUST), Islamabad (2019). She completed her MS in Mathematics from COMSATS Institute of Information Technology, Islamabad, in 2007 with a CGPA of 3.6/4, achieving 1st Division. She earned her M.Sc. in Mathematics from Quaid-i-Azam University, Islamabad (2005), and her B.Sc. in Mathematics (Maths A, Maths B, Stats) from the University of the Punjab (2003), both with 1st Division.

Experience :

Dr. Inam has extensive academic and research experience. Since September 2007, she has been serving as a Lecturer in Mathematics at Fatima Jinnah Women University, Rawalpindi. She also held the position of Incharge, Department of Mathematical Sciences from August 2016 to January 2018. Before that, she worked as a Research Associate at COMSATS Institute of Information Technology, Islamabad, from March to August 2007.

Research Focus :

Dr. Inam’s research interests span across multiple domains, including:

Cryptography & Security: Algebraic Cryptography, Cryptology, CryptanalysisAI & Data Security: Image Encryption, Blockchain, IoT, Deep Learning, Machine LearningMathematical Sciences: Fluid Mechanics, Geometric Function Theory.

Awards:

Dr. Inam’s academic excellence has been recognized through various awards and honors:

Scholarship – Capital University of Science and Technology (CUST), Islamabad (2013-2018)Dean’s Roll of Honor – Received twice during PhD courseworkDiploma in Academic Excellence in Discrete Mathematics – Abdul Salam School of Mathematical Sciences, GC University, Lahore (2012)Scholarship – COMSATS Institute of Information Technology, Islamabad (2005-2007)

Skills:

Dr. Inam possesses expertise in:Programming & Computational Tools: Matlab, Python, Mathematica, APCoCoA, Scientific Workplace, LaTeXOffice & Documentation: Proficient in Microsoft Office Suite,Dr. Saba Inam continues to contribute significantly to the fields of cryptography, image encryption, and mathematical security frameworks, with a strong focus on deep learning and blockchain applications.

Publication :

Three dimensional boundary layer flow of a viscoelastic nanofluid with Soret and Dufour effects

Numerical simulation of Darcy–Forchheimer 3D unsteady nanofluid flow comprising carbon nanotubes with Cattaneo–Christov heat flux and velocity and thermal slip conditions

An effective color image encryption based on Henon map, tent chaotic map, and orthogonal matrices

A new ElGamal-like cryptosystem based on matrices over groupring

Analytic study of a novel color image encryption method based on the chaos system and color codes

Blockchain based medical image encryption using Arnold’s cat map in a cloud environment

A numerical study of rotating Bödewadt flow of micropolar fluid over porous disk

A Novel Public Key Cryptosystem and Digital Signatures

A new method of image encryption using advanced encryption Standard (AES) for network security

Research on color image encryption approach based on chaotic Duffing map

Conclusion

Dr. Inam’s strengths, including her academic excellence, research impact, and leadership in academia, position her as a strong candidate for the “Research for Women Researcher Award.” While there are areas to enhance collaboration and public outreach, her work is already shaping critical developments in data security and encryption. Recognizing her would not only celebrate her achievements but also inspire more women to pursue careers in research and technology, contributing significantly to both academic and societal progress.

Yinhui Tang |Dieless hydroforming|Best Innovation Award

Posted on 06/01/202506/01/2025 by 21b4bddf87157652317827146367558f

Mr.Yinhui Tang |Dieless hydroforming|Best Innovation Award

Doctoral Student, Jiangsu University of Science and Technology,China

Mr. Yinhui Tang is a doctoral student at Jiangsu University of Science and Technology, China. His research interests focus on advanced mechanical engineering applications, including robotics, smart manufacturing, and materials engineering. Mr. Tang has contributed to several journal publications and conference presentations in his field, showcasing innovative solutions in automation and sustainable design practices.In addition to his academic pursuits, Mr. Tang has been actively involved in collaborative projects and industrial partnerships aimed at bridging the gap between theoretical research and practical engineering solutions. With a strong foundation in mechanical engineering, he aims to contribute to advancements in technology-driven engineering processes.

Professional Profiles:

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🎓 Education :

Yinhui Tang is currently pursuing a PhD in Naval Architecture and Ocean Engineering at the School of Naval Architecture & Ocean Engineering, Jiangsu University of Science and Technology, China, starting in September 2024. Previously, Yinhui completed a Master’s degree in Mechanical Engineering from the same university in June 2024, building a strong foundation in engineering principles and advanced research methodologies.

🏢 Experience:

Yinhui has extensive experience working on cutting-edge research projects in the fields of naval architecture and mechanical engineering, with a particular focus on pressure hull mechanics and advanced material structures. Yinhui is the host of the project “Mechanism of Instability and Bulging Mechanics of Multilayer Egg-shaped Pressure Hulls in Deep Sea,” funded for ¥15,000 from April 2024 to June 2025. Additionally, Yinhui has been a participant in several high-impact research projects, including the ¥1,700,000 “Deep Sea XXX Pressure-resistant Structure” project (2023–2025) and the ¥1,500,000 project on “Mechanism of Instability and Bulging Mechanics of Multilayer Variable-thickness Pressure-resistant Egg-shaped Shells in Deep Sea” (2023–2025). Yinhui also contributed to the dieless hydroforming research on egg-shaped pressure hulls (2021–2024) and the development of micro/nano composite pressure hulls (2023–2025), demonstrating expertise in multidisciplinary collaboration and technical problem-solving.

Skills:

Yinhui possesses a diverse set of skills, including expertise in structural mechanics, pressure-resistant hull design, material behavior analysis, and hydroforming processes. Proficiency in research design, project management, and technical report writing further highlights Yinhui’s capabilities. Yinhui is skilled in using advanced engineering software for modeling and simulation and excels in conducting experimental and theoretical studies to support innovation in deep-sea technologies.

Research Focus :

Yinhui’s research focuses on the mechanics of instability and bulging of multilayer egg-shaped pressure hulls, a critical area in deep-sea engineering. The work emphasizes understanding the structural behavior of variable-thickness pressure-resistant shells and developing innovative solutions for manufacturing high-performance pressure hulls. Yinhui is also exploring the impact resistance properties of advanced composite materials, aiming to enhance the reliability and durability of deep-sea structures. This research has significant implications for naval architecture, ocean engineering, and the design of next-generation submersible vessels.

🔬Awards:

Yinhui has been recognized for exceptional academic and research performance, contributing to groundbreaking studies in deep-sea pressure-resistant structures and mechanics. The research projects Yinhui has contributed to collectively garnered a total funding of ¥3,855,000, underlining their significant impact on advancing naval and mechanical engineering research.

Publications:

Title: Buckling performance of ellipsoidal pressure hulls with stepwise wall thicknesses
Authors: Y. Tang, J. Zhang, F. Wang, X. Zhao, M. Wang
Journal: Ocean Engineering
Year: 2023
Citations: 10

Title: Integrated hydrobulging of prolate ellipsoids from preforms with multiple thicknesses
Authors: J. Zhang, Y. Tang, M. Zhan, F. Wang, X. Zhao
Journal: The International Journal of Advanced Manufacturing Technology
Year: 2023
Citations: 4

Title: Internal Hydroforming of Large Stainless-Steel Eggshells from Stepped Preforms
Authors: Y. Tang, J. Zhang, M. Zhan, H. Jiao, P. Cheng, M. Dai
Journal: Metals
Year: 2023
Citations: 1

Conclusion:

Yinhui Tang is a highly suitable candidate for the “Research for Best Innovation Award” based on their research achievements and innovation potential. With a few improvements, such as publishing high-impact papers, obtaining patents, and showcasing broader societal or industrial impacts, their profile would be even more compelling.

Nikos Lagaros |Digital Technology|Best Researcher Award

Posted on 04/01/2025 by 21b4bddf87157652317827146367558f

Prof Dr.Nikos Lagaros |Digital Technology|Best Researcher Award

Vice Rector, National Technical University of Athens,Greece

Prof. Dr. Nikos D. Lagaros is the Vice Rector at the National Technical University of Athens (NTUA), Greece. He is a distinguished professor specializing in computational mechanics, optimization, and structural engineering. With numerous publications in high-impact journals and extensive research experience, he has made significant contributions to the fields of structural optimization, resilience engineering, and sustainable design. Dr. Lagaros is actively involved in academic leadership, fostering innovation and interdisciplinary collaboration at NTUA.

Professional Profiles:

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🎓 Education :

Nikolaos D. Lagaros holds a Diploma in Civil Engineering from the National Technical University of Athens (NTUA), completed in 1994 with a general grade of 7.96 (Very Well). He earned his Doctorate in Computational Mechanics from NTUA in 2000, with a dissertation titled Structural Design Optimization Based on Evolutionary Algorithms and Neural Networks. From 2000 to 2007, he conducted postdoctoral research at NTUA, focusing on computational structural analysis and earthquake engineering.

🏢 Experience:

Professor Lagaros is currently the Vice Rector of Finance, Infrastructure, and Development at NTUA. He previously served as Dean of the School of Civil Engineering at NTUA. He has held academic positions ranging from Lecturer to Professor within the Department of Structural Engineering at NTUA since 2008. Earlier, he was an Assistant Professor at the University of Thessaly and has held visiting professorships at prestigious institutions such as MIT and McGill University. His teaching portfolio spans undergraduate and postgraduate courses in structural analysis, optimization, and computational mechanics.

Skills:

Professor Lagaros specializes in advanced computational methods for simulation-based science and engineering. His expertise includes optimization methodologies, machine learning applications in structural analysis, seismic risk assessment, topology optimization, and high-performance computing. He is also skilled in lifecycle cost analysis, stochastic finite element methods, structural health monitoring, and energy-efficient design strategies.

Research Focus :

His research is centered on developing innovative methodologies for optimizing structural systems and creating computational tools leveraging artificial intelligence and metaheuristics. He has made significant contributions to structural parametric design, topology optimization, and reliability analysis of large-scale systems. His work also explores shared and distributed computing technologies for solving complex engineering problems.

🔬Awards:

Professor Lagaros is recognized for his leadership roles and contributions to academia. He has supervised numerous doctoral, graduate, and diploma theses, advancing research in structural engineering and computational mechanics. His collaborations with international researchers and institutions have further strengthened his impact on the field.

Publications:

Antoniou, P.A., Markolefas, S.I., Giannopoulos, G.I., Lagaros, N., Georgantzinos, S.K. (2025). Multiscale modeling of microstructural and hygrothermal effects on vibrations of CNT-enhanced fiber-reinforced polymer composites. Journal of Sound and Vibration, 596, 118733.

Sapountzaki, O.E., Kampitsis, A.E., Lagaros, N.D. (2024). Polymer Matrix Composites: The case of pentamodes. Composite Structures, 346, 118419.

Gonidakis, D.N., Frangedaki, E.I., Lagaros, N.D. (2024). Optimizing Daylight Performance of Digital Fabricated Adobe Walls. Architecture, 4(3), pp. 515–540.

Vougioukas, E., Stamos, A., Pappa, C., Lagaros, N.D. (2024). Enhancing Onshore Wind Tower Foundations: A Comprehensive Automated Design Approach. CivilEng, 5(3), pp. 736–759.

Ypsilantis, K.-I., Faes, M.G.R., Lagaros, N.D., Aage, N., Moens, D. (2024). Robust topology and discrete fiber orientation optimization under principal material uncertainty. Computers and Structures, 300, 107421.

Chamatidis, I., Istrati, D., Lagaros, N.D. (2024). Vision Transformer for Flood Detection Using Satellite Images from Sentinel-1 and Sentinel-2. Water (Switzerland), 16(12), 1670.

Al-Omari, A.A., Shatnawi, N.N., Shbeeb, N.I., Lagaros, N.D., Abdalla, K.M. (2024). Utilizing Remote Sensing and GIS Techniques for Flood Hazard Mapping and Risk Assessment. Civil Engineering Journal (Iran), 10(5), pp. 1423–1436.

Rossetos, I., Gantes, C.J., Kazakis, G., Soultanis, K., Lagaros, N.D. (2024). Numerical Modeling and Nonlinear Finite Element Analysis of Conventional and 3D-Printed Spinal Braces. Applied Sciences (Switzerland), 14(5), 1735.

Sapountzaki, O.E., Kampitsis, A.E., Lagaros, N.D. (2024). Failure mechanisms of anisotropic pentamode-based bridge bearings: A dynamic analysis. Engineering Structures, 301, 117292.

Damikoukas, S., Lagaros, N.D. (2024). The MLDAR Model: Machine Learning-Based Denoising of Structural Response Signals Generated by Ambient Vibration. Computation, 12(2), 31.

Conclusion:

Prof. Lagaros’s career reflects a blend of academic excellence, research innovation, and leadership. His expertise in cutting-edge technologies like machine learning and computational analysis places him among the top researchers in his field. Addressing areas like global outreach, sustainability, and public engagement would further solidify his candidacy. Overall, he is highly suitable for this award and deserves recognition for his contributions to civil engineering and computational science.