Rounak Raman | Information Technology | Outstanding Scientist Award

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Mr. Rounak Raman | Information Technology | Outstanding Scientist Award

Netaji Subhas University of Technology | India

Mr. Rounak Raman is an emerging researcher specializing in computer networking, IoT security, wireless sensor networks, AI-driven network management, and Generative AI. His scholarly contributions include CONTEXT-NET, a context-aware aggregation protocol for opportunistic networks, and ARMor-IoT, a trust-optimized mechanism enhancing IoT reliability, reflecting innovation in secure communication systems. He has also developed EAHCP, an energy-aware hybrid clustering protocol improving network lifetime, and HKRISRP, a hierarchical key-rotation framework for strengthened WSN security. His interdisciplinary work spans neurofeedback analytics, semantic search, YOLO-based computer vision, and enterprise generative AI tools. Overall, his research demonstrates strong technical depth, real-world impact, and a focus on secure, intelligent, and energy-efficient networked systems.

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Featured Publications

ARMor-IoT: Aggregated Reliable Mechanism for Optimized Trust in IoT
– International Conference on Artificial Intelligence and Its Application, 2025

Jamshed AliShaikh | Cybersecurity | Best Researcher Award

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Dr. Jamshed AliShaikh | Cybersecurity | Best Researcher Award

Dr. Jamshed AliShaikh at Chongqing University, China

Jamshed Ali  is a Ph.D. candidate in Computer Science & Technology at Chongqing University, China 🇨🇳, with over 7 years of research experience and 4+ years of industry and academic roles. His work bridges AI 🤖, cybersecurity 🔐, and healthcare technologies 🏥. He has contributed to high-impact projects funded by Chinese research councils and has published multiple Q1-ranked journal articles 📚. Jamshed is known for his collaborative spirit, technical versatility, and commitment to using AI for societal benefit 🌍. He is fluent in programming and simulation tools and is a recognized young researcher from Pakistan 🇵🇰.

Publication Profile

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Academic Background

Jamshed Ali earned his Ph.D. in Computer Science & Technology (2020–2025) from Chongqing University, focusing on intelligent intrusion detection for IoMT healthcare networks 🛡️🏥. He completed his MS in Electrical Engineering (2018–2020) at the same university, working on AI-based optimization in smart grids ⚡ using fuzzy logic and control systems. He holds a BS in Electronics (2010–2014) from the University of Sindh, Pakistan, where he explored smart robotics 🤖 for disaster response. His academic path reflects a strong foundation in electronics, AI, and system-level problem-solving 💡 across interdisciplinary domains.

Professional Background

Jamshed Ali has over 4 years and 5 months of professional experience 🧠💻, including work as a Lecturer and IT In-Charge 👨‍🏫 at HIMAS-CON (3+ years), where he taught computer science and led IT operations. He worked as a PHP Developer 💻 at Geeks of Kolachi, managing web development projects. During his internship at Chongqing Kaixinderui, he gained practical experience in engineering teamwork and cultural integration 🤝🇨🇳. Alongside his academic research, these roles reflect a hands-on approach to both technical development and educational leadership in IT and cybersecurity domains 🔐🧑‍🏫.

Awards and Honors

Jamshed Ali received a fully funded 🎓 Chinese Government Scholarship for both his MS and Ph.D. studies in 2018 and 2020 🇨🇳. He was named the “Outstanding Student of the Year” 🥇 in 2020 at Chongqing University for academic excellence and leadership. He also won “Best Speaker” 🎤 at the China-Pakistan Culture and Technology Conference, where he presented on AI’s transformative role across healthcare, education, and manufacturing 🚀. These accolades reflect his academic impact, communication skills, and international recognition 🌍 in the field of intelligent systems and research innovation 🧪.

Research Focus

Jamshed’s research centers on cybersecurity in IoMT and Industrial IoT 🌐, with a focus on machine learning and deep learning 🔍 for intrusion detection, especially detecting zero-day attacks 🚨. He explores federated learning, edge/cloud computing ☁️, secure communication protocols, and medical image processing 🖼️ to enhance healthcare data security 🛡️. His work contributes to intelligent, privacy-preserving healthcare systems, backed by publications in high-impact journals 📘. Jamshed combines theory and application, building intelligent systems that respond to real-world threats while pushing the boundaries of AI in digital health and critical infrastructure 💡🧠.

Publication Top Notes

🔋 Voltage Stability Index using new single-port equivalent based on component peculiarity and sensitivity persistence
Year: 2021 | 📖 Cited by: 11

🌡️ Temperature field simulation and ampacity optimization of 500kV HVDC submarine transmission cable
Year: 2021 | 📖 Cited by: 10

🛰️ A UAV-Assisted Stackelberg Game Model for Securing IoMT Healthcare Networks
Year: 2023 | 📖 Cited by: 9

🌞 A Reliable Approach to Protect and Control of Wind Solar Hybrid DC Microgrids
 Year: 2019 | 📖 Cited by: 9

Conclusion

Based on his outstanding academic record, impactful research in cybersecurity and IoMT, high-quality publications in Q1 journals, and significant involvement in both funded research projects and technical roles, Jamshed Ali stands out as a highly deserving candidate for the Best Researcher Award. His work on intelligent intrusion detection systems using AI and deep learning contributes to a critical and emerging field, particularly in healthcare network security. Coupled with his strong technical proficiency, 7 years of research experience, multiple honors—including CSC scholarships and recognition as an outstanding student and speaker—Jamshed Ali exemplifies excellence in early-career research and innovation.

Yanchun Chen | Technology | Best Researcher Award

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Dr. Yanchun Chen | Technology | Best Researcher Award

Dr. Yanchun Chen, Communication University of China, China

Yanchun Chen is a Ph.D. student in Information Communication at the Communication University of China (CUC), specializing in digital public opinion. With a background in computational communication, she has contributed extensively to public opinion analysis and media convergence research. She has published in high-impact journals, including Cities and Ethics and Information Technology. Yanchun has presented her research at IAMCR, AEJMC, and ICA conferences, receiving the IAMCR Urban Communication Award. Her expertise lies in digital media ethics, risk communication, and the socio-political impact of emerging technologies.

Publication Profile

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🎓 Education

Yanchun Chen is pursuing her Ph.D. in Information Communication at CUC (2024–Present), focusing on digital public opinion. She holds an M.S. in Communication (Computational Communication) from the State Key Laboratory of Media Convergence and Communication, CUC (2022–2024), where she analyzed communication data to interpret public sentiment. She completed her B.S. in Tourism Management from Minjiang University (2017–2021), developing foundational insights into media’s impact on cultural narratives. Her academic journey reflects an interdisciplinary approach, integrating communication theories with computational methodologies.

💼 Experience

Yanchun has conducted extensive data analysis at the State Key Laboratory of Media Convergence and Communication, focusing on public opinion trends. At the National Broadcast Media Language Resources Monitoring and Research Center, she developed a systematic media monitoring ledger. She has collaborated on international research, applying social network analysis and topic modeling to urban communication and media ethics. Her studies on deepfake resurrection, AI-generated narratives, and crisis communication have contributed to scholarly discourse in media ethics. Additionally, she has served as a research assistant on digital geopolitics projects, addressing trust issues in global media.

🏆 Awards and Honors

Yanchun has received the prestigious IAMCR Urban Communication Award (2024) for her groundbreaking research. She has been recognized with first-class scholarships, an Outstanding Graduate award, and the highest-level alumni scholarship at CUC. She also holds a National Computer Level II certificate and a bilingual tour guide certification. Her research has been nominated for the Best Researcher Award at the International Academic Awards. These accolades underscore her contributions to media studies, computational communication, and digital ethics.

🔬 Research Focus

Yanchun’s research explores urban memory in digital media, risk communication, and ethical implications of AI-generated content. She examines visual representation in short-form media and its role in shaping public perceptions. Her work on deepfake resurrection delves into digital immortality and narrative ethics. Additionally, she investigates media trust, particularly in global crisis communication, using computational methods like DTM topic modeling and social network analysis. Her studies contribute to understanding media convergence, digital ethics, and the socio-political impact of emerging communication technologies.

Publication Top Note

Urban visual representation and ethical narrative risks

Conclusion

Dr. Yanchun Chen demonstrates exceptional research contributions, global academic recognition, and innovative methodologies in digital communication and public opinion studies. Their publications in top-tier journals, prestigious awards, and interdisciplinary research focus make them a highly suitable candidate for the Best Researcher Award.

Ahcene Bounceur | Cybersecurity | Best Researcher Award

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Dr. Ahcene Bounceur | Cybersecurity | Best Researcher Award

Associate Professor at  University of Sharjah, United Arab Emirates.

Dr. Ahcene Bounceur is an Associate Professor at the University of Sharjah, specializing in cybersecurity, IoT, smart cities, and data science. Previously, he held faculty positions at KFUPM and University of Western Brittany (UBO), where he was a senior associate professor and qualified for professorship .He earned his Ph.D. in Micro and Nano Electronics from Grenoble INP, France, in 2007 and an HDR (State PhD) in Computer Science in 2014. His research includes Digital Twin tools for smart infrastructure security, pseudo-polygons for cybersecurity, and simulation tools for WSN and IoT. Dr. Bounceur is the main developer of Cup Carbon, a renowned IoT network simulator, and has led projects like ANR PERSEPTEUR and Suidia. He has 200+ publications, served as a keynote speaker, and held editorial roles in journals like MDPI Sensors. Recognized for his contributions, he won 3rd place in the IEEE TTTC Doctoral Thesis Contest and holds a patent for an IoT-based digital health platform.

Publication Profile

Scopus

🎓Academic Qualifications of Ahcene Bounceur

Dr. Ahcene Bounceur is a distinguished computer scientist with expertise in microelectronics, data mining, and wireless sensor networks. He earned his HDR (State PhD) in Computer Science from the University of Western Brittany (UBO) in 2014, focusing on models and simulation for mixed circuit testing. In 2007, he obtained a PhD in Micro and Nanoelectronics from the TIMA Laboratory (Grenoble), specializing in computer-aided test platforms. His M.Sc. in Operations Research (2003) and Engineering degree (2002) were awarded in Grenoble and Bejaia, respectively. Additionally, he gained early programming experience in 1995 at the Micro-Services School of Béjaia. 💻📡

Professional Background

Dr. Ahcene Bounceur is an Associate Professor at the University of Sharjah (2024–Present) and previously held the same role at KFUPM (2023–2024). Since 2014, he has been qualified for professorship at the University of Western Brittany (UBO), where he served as a Senior Associate Professor (2020–2023) and Associate Professor (2008–2020). His earlier roles include Assistant Professor at ENSERG (2007–2008) and Postdoctoral Researcher at TIMA Laboratory (2006–2007). He has also held leadership roles, including Head of Computer Science at UBO (2011–2023) and Member of France’s National Council of Universities (2021–2023). 🏫📡

🔬 Research Focus of Ahcene Bounceur

Dr. Ahcene Bounceur’s research spans Artificial Intelligence , Cybersecurity , Data Mining , and Circuit Testing . Since 2012, he has focused on Collaborative AI (CupCarbon Klines simulator), Digital Twin IoT for cybersecurity in critical infrastructures, pseudo-polygons for polygonal hull determination, and statistical modeling for sensor networks. From 2002–2012, his work emphasized manufacturing process variations, Monte Carlo simulations for test metrics, and non-linear circuit modeling using copula theory. His interdisciplinary expertise integrates AI, IoT, cybersecurity, and statistical modeling to enhance smart infrastructures and sensor networks. 🚀📡

Publication Top Notes

🔹 A Secure and Lightweight ZKP-based Mutual Authentication Scheme with Key Agreement
      Year: 2025 |  Arabian Journal for Science and Engineering |

🔹 Integrating Homomorphic Encryption in IoT Healthcare Blockchain Systems
      Year: 2024 | Ingenierie des Systemes d’Information |

🔹 Blockchain Use Cases in the Sports Industry: A Systematic Review
     Year: 2024 |  International Journal of Networked and Distributed Computing | 🔍 Citations: 3

Conclusion

Ahcene Bounceur is a distinguished researcher with a strong record of high-impact publications, including multiple papers in Q1 journals, some ranking in the top 4%, 8%, and 12%, highlighting his significant research influence. His expertise spans diverse areas such as watermarking, wireless sensor networks (WSN), digital twins, security protocols, data mining, and circuit design, demonstrating interdisciplinary proficiency. His recent and consistent contributions, particularly in 2024 and 2025, reflect his sustained excellence in research. Additionally, his collaborations with leading researchers and institutions showcase his global research impact and networking strength. These achievements make him a strong contender for the Best Researcher Award. 🚀

 

 

 

Noor .A. Rashed | Computer Science Award | Women Researcher Award

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Dr . Noor .A. Rashed | Computer Science Award | Women Researcher Award

Dr. Noor Rashid, Iraq

Dr. Noor Rashid is a Ph.D. candidate at the University of Technology, Baghdad, specializing in Computer Science. She earned her master’s degree from the University of al-Anbar in 2018. Her research covers areas such as Artificial Intelligence, secure data systems, machine learning, data mining, image processing, and project management automation. Her current focus is on optimization algorithms, particularly multi-objective optimization (2022-2023). Dr. Rashid has contributed significantly to the field, including her recent publication on evolutionary and swarm-based algorithms. She continues to advance AI and optimization research in her academic journey.

 

Publication profile

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Employment

Dr. Noor Rashid is currently employed at the University of Technology, Baghdad, Iraq, in the Department of Computer Science. As a dedicated researcher and educator, she contributes to the university’s mission by advancing studies in Artificial Intelligence, secure data systems, and optimization algorithms. Her role involves teaching and mentoring students while conducting innovative research in multi-objective optimization and machine learning. Dr. Rashid’s work continues to impact both the academic community and the broader technological landscape through her involvement in cutting-edge computer science projects.

 

Education and Qualifications 🎓📜

Dr. Noor Rashid is currently pursuing her Ph.D. in Computer Science at the University of Technology, Baghdad, Iraq, from November 2021 to November 2024. Her doctoral research focuses on advanced areas such as optimization algorithms and Artificial Intelligence, contributing to cutting-edge technological advancements. Prior to this, Dr. Rashid earned her master’s degree from the College of Computer Science and Information Technology at the University of al-Anbar in 2018. Her academic background equips her with a strong foundation in secure data, machine learning, and project management systems, preparing her for continued success in the field.

 

Research Focus 🎯🔬

Dr. Noor Rashid’s research primarily focuses on Artificial Intelligence (AI), particularly in machine learning, optimization algorithms, and data mining. Her studies delve into complex areas such as multi-objective optimization and evolutionary algorithms, aiming to solve real-world computational problems. Additionally, Dr. Rashid has worked extensively on medical image processing, applying AI techniques like ANN and SVM to detect and classify diseases like diabetic retinopathy. Her research bridges the gap between AI and healthcare, making significant contributions to secure data, networks, and advanced algorithmic developments. 🚀🧠

 

Publication Top Notes

  • Diagnosis retinopathy disease using GLCM and ANN – N. Rashed, S. Ali, A. Dawood – J. Theor. Appl. Inf. Technol 96, 6028-6040, 2018 (Cited by: 4) 📖
  • Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems – N.A. Rashed, Y.H. Ali, T.A. Rashid, A. Salih – arXiv preprint, 2024 (Cited by: 2) 🌐
  • Advancements in Optimization: Critical Analysis of Evolutionary, Swarm, and Behavior-Based Algorithms –  Rashed, Y.H. Ali, T.A. Rashid – Algorithms 17(9), 416, 2024 📑
  • ANN and SVM to recognize Texture features for spontaneous Detection and Rating of Diabetic Retinopathy –  Rashed (Upcoming) 🔍