Mohtasham Khanahmadi | signal processing | Best Researcher Award

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Mohtasham Khanahmadi | signal processing | Best Researcher Award

Mr.Mohtasham Khanahmadi, Semnan University, Iran.

Mr.Mohtasham Khanahmadi is an Iranian civil engineering researcher specializing in structural health monitoring, damage detection, and signal processing. With over five years of experience, he focuses on nondestructive evaluation, inverse problems, and modal analysis of thin-walled and composite structures. He holds a B.Sc. in Civil Engineering from Velayat University and an M.Sc. in Structural Engineering from Semnan University. Proficient in MATLAB, Abaqus, and computational modeling, he has authored impactful research on damage localization and interfacial debonding detection. Passionate about enhancing structural integrity, his contributions advance the field of applied and computational mathematics in civil engineering. 🔍🛠️

Publication Profile

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Education & Experience 🎓👷‍♂️

📌 B.Sc. in Civil Engineering – Velayat University, Iran (2011–2015)
📌 M.Sc. in Structural Engineering – Semnan University, Iran (2015–2018)
📌 Researcher in Structural Health Monitoring & Damage Detection (5+ years)
📌 Expert in Computational Mathematics & Signal Processing for Civil Structures
📌 Published Research in High-Impact Structural Engineering Journals.

Suitability Summary

Dr. Mohtasham Khanahmadi is a distinguished civil engineering researcher recognized for his outstanding contributions to structural health monitoring, damage detection, and signal processing. With over five years of dedicated research, he has demonstrated exceptional expertise in nondestructive evaluation, applied and computational mathematics, inverse problems, and modal analysis of thin-walled and composite structures, including plates, beams, and columns. His pioneering methodologies have significantly advanced the assessment of structural integrity and performance, making him a highly deserving candidate for the Best Researcher Award.

Professional Development 📈🔬

Mr.Mohtasham Khanahmadi actively contributes to the advancement of structural health monitoring through cutting-edge research in damage detection and localization techniques. His expertise spans signal processing,  nverse problems, and modal analysis, with a strong focus on nondestructive evaluation of civil structures. Skilled in MATLAB, Abaqus, and Microsoft Office tools, he integrates computational methods to enhance structural performance. His work in analyzing thin-walled and composite structures under axial loads has led to significant advancements in interfacial debonding detection and modal curvature-based irregularity indices. Dedicated to academic excellence, he continuously engages in professional learning and knowledge dissemination. 📊🏗️.

Research Focus  🔍🏢

Mr.Mohtasham Khanahmadi’s research centers on structural health monitoring 🏗️, emphasizing damage detection and localization in civil engineering structures. His work involves signal processing 📡, nondestructive evaluation 🛠️, and computational mathematics 🔢 to enhance the integrity of thin-walled and composite structures such as plates, beams, and columns. He specializes in inverse problem-solving to assess structural behavior under different conditions, including modal analysis of concrete-filled steel tubular (CFST) columns. By developing advanced methodologies, he contributes to the early detection of structural failures, leading to safer and more efficient engineering solutions. 🚧🔬.

Awards & Honors 🏆🎖️

🏅 Recognized for impactful research in structural health monitoring & damage detection
🏅 Published in high-impact journals, including Measurement & IJSSD
🏅 Contributions to computational civil engineering methodologies acknowledged in academia
🏅 Active collaborator in multidisciplinary structural engineering research projects
🏅 Recognized for advancing nondestructive evaluation techniques for damage localization.

Publication Top Notes

📌 A numerical study on vibration-based interface debonding detection of CFST columns using an effective wavelet-based feature extraction technique – 2024

📌 Interfacial Debonding Detection in Concrete-Filled Steel Tubular (CFST) Columns with Modal Curvature-Based Irregularity Detection Indices – 2024

📌 Vibration-based damage localization in 3D sandwich panels using an irregularity detection index (IDI) based on signal processing – 2024

📌 Vibration-based health monitoring and damage detection in beam-like structures with innovative approaches based on signal processing: A numerical and experimental study – 2024

 

 

 

Assist. Prof. Dr. Chaofeng Zhao | Signal Processing | Best Researcher Award

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Assist. Prof. Dr. Chaofeng Zhao | Signal Processing | Best Researcher Award

Assist. Prof. Dr. Chaofeng Zhao | Luoyang Normal University | China

Zhao Chaofeng is a dedicated academic and researcher specializing in digital communications, signal processing, and image processing. 📡🔍 He holds a Ph.D. in Control Engineering from Xi’an University of Technology (2020), an M.S. in Applied Mathematics from Beifang University for Nationalities (2012), and a B.S. in Applied Mathematics from Fuyang Normal University (2005). 🎓 Currently serving as a lecturer at Luoyang Normal University, he has authored 20 research papers, including 10 in prestigious journals like ND, IJBC, and CIS. 📖✍️ Additionally, he holds 4 authorized invention patents, contributing significantly to technological advancements. 🔬💡

Professional Profile:

ORCID

Suitability for Best Researcher Award

Dr. Zhao Chaofeng is a highly accomplished researcher in the fields of digital communications, signal processing, and image processing. His strong academic background, with a Ph.D. in Control Engineering, along with his M.S. and B.S. in Applied Mathematics, demonstrates a solid foundation in mathematical modeling and engineering applications.

Education & Experience 📚👨‍🏫

  • 🎓 Ph.D. in Control Engineering – Xi’an University of Technology, 2020
  • 🎓 M.S. in Applied Mathematics – Beifang University for Nationalities, 2012
  • 🎓 B.S. in Applied Mathematics – Fuyang Normal University, 2005
  • 👨‍🏫 Lecturer – School of Information Technology, Luoyang Normal University, China
  • ✍️ Published 20 research papers, including 10 in ND, IJBC, CIS, and other top journals
  • 🔬 Holds 4 authorized invention patents in the fields of signal and image processing

Professional Development 📡🔬📖

Zhao Chaofeng continuously expands his expertise in digital communications and signal processing through active research and publications. 📝 He contributes to the academic community by mentoring students and participating in technological advancements. 💡 His research explores innovative applications in coding and engineering mathematical methods, driving progress in modern communication systems. 📶 As a lecturer at Luoyang Normal University, he is committed to knowledge-sharing and academic excellence. 🏫 His work has received recognition through multiple patents, and he remains engaged in interdisciplinary studies to enhance the efficiency and accuracy of digital signal applications. 🚀🔍

Research Focus 🔬📡📊

Dr. Zhao’s research revolves around digital communications, signal processing, and image processing, aiming to enhance modern technology’s efficiency and reliability. 📡 His work integrates coding techniques and mathematical modeling to optimize communication systems. 📊 Through cutting-edge innovations, he explores advanced signal filtering, noise reduction, and image enhancement for various applications. 🖼️📡 His interdisciplinary approach bridges mathematics, engineering, and computational methods to develop robust solutions in data transmission and processing. 📶🔍 His contributions have significantly impacted theoretical advancements and practical applications in the field, fostering progress in modern digital communication. 🚀💡

Awards & Honors 🏆🎖️

  • 🏅 Published 20 research papers, including 10 in ND, IJBC, CIS, and other prestigious journals
  • 📜 4 authorized invention patents in digital communications and signal processing
  • 🎓 Recognized for contributions in mathematical modeling and engineering applications
  • 🌍 Active participant in international conferences and research collaborations
  • 🏆 Awarded research grants for innovative work in digital signal and image processing

Publication Top Notes:

🔐 Delayed Chaotic Image Encryption Using Cross-Layer and DNA Coding Techniques
🖼 A Novel Image Encryption Algorithm by Delay Induced Hyper-chaotic Chen System
📖 Weakness Analyzing and Performance Improvement for Image Encryption with Chaos Across Cylinder
📊 Optimal Control of Stochastic System with Fractional Brownian Motion
📸 Image Encryption Based on Hyper-chaotic Multi-attractors

 

 

Dr. Pardhu Thottempudi | RADAR Signal Processing | Best Researcher Award

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Dr. Pardhu Thottempudi | RADAR Signal Processing | Best Researcher Award

Dr. Pardhu Thottempudi, BVRIT HYDERABAD College of Engineering for Women, India

Dr. Pardhu Thottempudi holds a Ph.D. in Electronics and Communications Engineering from Vellore Institute of Technology, where he specialized in Hybrid Optimization Algorithms for Human Motion Identification using IR UWB RADAR. He also earned an M.Tech. in Embedded Systems, focusing on RADAR testing using FPGA, and a B.Tech. in Electronics and Communications Engineering with a project on automated vehicles for the physically and visually challenged. Dr. Thottempudi has extensive teaching experience at institutions such as BVRIT Hyderabad College of Engineering for Women and SR University. He holds multiple patents for innovations in safety devices, power-efficient compressors, and AI-based humanoid robots. His extensive publication record includes books and research chapters on various topics in electronics and communications, underscoring his significant contributions to the field.

Suitability for the Best Researcher Award:

Dr. Pardhu’s extensive research output, including high-impact journal articles, patents, and books, demonstrates a significant impact on his field. His work on human motion identification, radar technology, and embedded systems showcases both innovative and practical advancements. His ongoing research efforts and academic contributions align well with the criteria for the Best Researcher Award, making him a strong candidate for recognition.

Professional Profile🌍

Google Scholar
Orcid
Scopus

Educational Background 🎓

Dr. Pardhu Thottempudi holds a Ph.D. in Electronics and Communications Engineering from Vellore Institute of Technology, where his research focused on Hybrid Optimization Algorithms for Human Motion Identification using IR UWB RADAR. He also earned an M.Tech. in Embedded Systems, completing a thesis on the Generation and Simulation of Clutter for RADAR Testing using FPGA. Dr. Thottempudi’s expertise lies in advanced radar technologies and embedded systems, contributing to significant advancements in human motion identification and radar testing methodologies.

Professional Experience 💼

Dr. Thottempudi has extensive teaching and research experience as an Assistant Professor at various reputable institutions, including BVRIT Hyderabad College of Engineering for Women, SR University, MLR Institute of Technology, St. Peter’s Engineering College, and Marri Laxman Reddy Institute of Technology & Management.

Patents and Innovations 📜

He holds multiple patents in innovative technologies such as women’s safety devices, power-efficient compressors, and AI-based humanoid robots for surveillance, demonstrating a strong focus on practical and impactful innovations.

Publications and Authorship 📚

Dr. Thottempudi has authored several research books and chapters on topics including RADAR testing, compressor design, MIMO environment parameter estimation, object detection in surveillance videos, and spectral analysis of water bodies from satellite images. His work reflects a broad and deep expertise in various aspects of electronics and communications engineering.

Dr. Pardhu Thottempudi’s distinguished career in academia, coupled with his innovative research and extensive publication record, highlights his significant contributions to the field of electronics and communications engineering.

Publication Top Notes: