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

Orcid

🎓 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.

Hussain Ahmad | Software Engineering | Best Researcher Award

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Mr. Hussain Ahmad | Software Engineering | Best Researcher Award

PhD Student at The University of Adelaide, Australia

🛡️ Hussain Ahmad is a cybersecurity and software engineering expert with a strong background in cloud computing, machine learning, robotics, and autonomous systems. Currently pursuing a PhD at the University of Adelaide (2021-2025), his research focuses on self-adaptive cybersecurity and software scalability. He has led 15+ R&DI projects, published 10 high-impact papers with 500+ citations, and secured AUD 200k+ in funding from Google, Amazon, and Cyber Security CRC. A Professional Electronics Engineer (Engineers Australia), he has supervised 12+ students and received the Outstanding International Student Award. His industry roles include Cyber Security Engineer, Chief Project Officer (Migrova), and Software Engineer (Kindship). 🌍🔐🤖

 

Publication Profile

Scopus

 

🎓 Education

Hussain Ahmad is currently pursuing a Doctor of Philosophy (PhD) in Cybersecurity and Software Engineering at The University of Adelaide, Australia (2021-2025). His research focuses on self-adaptive cybersecurity and software scalability, under the supervision of Claudia Szabo, Christoph Treude, and Markus Wagner. Prior to this, he earned a Bachelor of Science in Electronic Engineering (2013-2017) from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan, achieving a High Distinction. His bachelor’s degree is accredited by Engineers Australia, reflecting his strong foundation in electronic engineering and advanced computing systems. 📡🔐📊

 

💼 Work Experience

Hussain Ahmad is an R&D Scholar in Software Security & Scalability at The University of Adelaide (2021-2025), leading 15+ R&DI projects at the intersection of Cybersecurity, Software Engineering, and Machine Learning, with high-impact findings published in leading journals. As a Research Supervisor (2022-2025), he mentors students on industry-focused R&DI projects in collaboration with CSIRO’s Data61, Migrova, and Schlumberger. He also serves as Chief Project Officer at Migrova (2023-2024), securing AUD 100k for AI-driven cybersecurity solutions. Additionally, he developed an ML-enabled therapist recommendation engine as a Software Engineer at Kindship (2022-2023). 🔐💻🚀

 

🏆 Awards & Achievements

Hussain Ahmad has received numerous prestigious accolades for his contributions to R&DI, cybersecurity, and academic excellence. He was featured in a leading newspaper and honored with the Outstanding International Student Award at The University of Adelaide. He won the Exceptional HDR Representative Award and secured People’s Choice & Second Place in the 2024 Visualise Your Thesis Competition. His achievements include a Google Cloud Grant, AUD 100k Seed-Start grant, and three RTP Scholarships. Additionally, he is an accredited Professional Electronics Engineer, a recipient of six Dean’s Excellence Awards, and was awarded a GIKI Fully Funded Financial Assistance Award. 🏅🔬🚀

 

🔍 Research Focus

 

Hussain Ahmad’s research primarily focuses on cybersecurity, software engineering, and microservice architectures. His work on Microservice Vulnerability Analysis in IEEE Access (2024) highlights security risks, threat modeling, and empirical insights into software vulnerabilities. His expertise extends to self-adaptive cybersecurity, cloud computing, machine learning, and autonomous systems. With multiple high-impact publications and industry collaborations, he contributes to secure software scalability, cyber defense mechanisms, and AI-driven security solutions. His interdisciplinary approach bridges software security, electronic engineering, and automation, making him a key researcher in next-generation secure computing systems. 🔐💻📡

 

Publication Top Notes

1️⃣ A Review on C3I Systems’ Security: Vulnerabilities, Attacks, and Countermeasures – ACM Computing Surveys, 2023 🏆 
2️⃣ Smart HPA: A Resource-Efficient Horizontal Pod Auto-scaler for Microservice Architectures – ICSA, 2024 🏆 
3️⃣ Towards Resource-Efficient Reactive and Proactive Auto-scaling for Microservice Architectures – Journal of Systems and Software, 2024 🏆 
4️⃣ Microservice Vulnerability Analysis: A Literature Review with Empirical Insights – IEEE Access, 2024 🏆 
5️⃣ Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures – Cluster Computing, 2024 🏆
6️⃣ A Survey on Immersive Cyber Situational Awareness Systems – Submitted to IEEE Access, 2024 🏆 🛡️
7️⃣ ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large Language Models – 2024 🏆
8️⃣ Machine Learning Driven Smishing Detection Framework for Mobile Security – Submitted to Cluster Computing, 2024 🏆 
9️⃣ What Skills Do Cyber Security Professionals Need? – Submitted to Neurocomputing, 2025 🏆 
🔟 Exploring Sentiments of ChatGPT Early Adopters using Twitter Data – 2023 🏆

 

 

 

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.