Mrs. Guoqin Chang | AI Security | Shaanxi Science and Technology Holding Institute | China

Mrs. Guoqin Chang holds a Ph.D. in Cyberspace Security from the School of Cybersecurity at Xidian University and currently leads the Artificial Intelligence Research Group at Shaanxi KeKong Technology Industry Research Institute, while also serving as Technical Advisor to the Shaanxi Printing Science and Technology Research Institute. Over her career, Chang Guoqin has built expertise in natural language processing (NLP), domain-specific large language model deployment, prompt engineering, fine-tuning and adaptation of models, AI model security, detection of text generated by large language models, adversarial text attacks/defenses, and multimodal information fusion. She is skilled in designing and evaluating robust NLP pipelines, adversarial-robust model architectures, secure model deployment, domain adaptation techniques, and text classification systems with security-aware defenses. Her professional experience spans research and development, project leadership, and peer-reviewing for major journals including Information Sciences and Computer Engineering and Design, and she has contributed to both academic publications and applied software/patents through her inventive activity. Through her publication record, patent filings, software copyrights, and R&D project involvement, Chang Guoqin has demonstrated a strong commitment to improving the security, robustness, and domain-adaptability of modern AI. In conclusion, Chang Guoqin brings together advanced academic training, deep technical skills in NLP security and model adaptation, and real-world engineering experience positioning her as a leading researcher/engineer in secure, domain-specific artificial intelligence and robust natural language processing solutions.

Professional Profiles: ORCID | Google scholar

Selected Publications

Chang, G., Gao, H., Yao, Z., & Xiong, H. (2023). TextGuise: Adaptive adversarial example attacks on text classification model.
Chang, G., Gao, H., Pei, G., … & Guo, Q. (2024). The robustness of behavior-verification-based slider CAPTCHAs. Journal of Information Security and Applications.
Cheng, L., Zhang, Z., & Chang, G. (2019). Multimedia Social Network Authorization Scheme of Comparison-based Encryption.
Cheng, N., Chang, G., & Gao, H. (2020). WordChange: Adversarial Examples Generation Approach for Chinese Text Classification.
Chang, G., Gao, H., & Li, B. (2025). TextShelter: Text Adversarial Example Defense Based on Input Reconstruction.
Chang, G., & colleagues. (2019). A Survey of Research on CAPTCHA Designing and Breaking Techniques.
Cheng, N., Chang, G., Gao, H., … & Zhang, Y. (2020). WordChange: Adversarial Examples Generation Approach for Chinese Text Classification.

Ms. Raghi K R | Federated Learning | Research Excellence Award

Ms. Raghi K R | Federated Learning | Sathyabama Institute of Science and Technology | India

Mrs. Raghi K.R. is a dedicated computer science educator and researcher with strong experience in both teaching and applied research. She holds a B.E. in Computer Science and Engineering (Anna University), an M.E. in Computer Science and Engineering (PSN Engineering College / Anna University), and has submitted her Ph.D. synopsis in Computer Science and Engineering at College of Engineering, Guindy, Anna University. Her professional journey includes roles as Assistant Professor and Teaching Fellow across several institutions: PSN Engineering College (CSE), College of Engineering Guindy, and currently at St. Joseph’s College of Engineering, Chennai giving her over a decade of teaching experience, spanning undergraduate and postgraduate courses. Her research interests lie in Artificial Intelligence, Deep Learning, Machine Learning, Cloud Security, and Web Mining. She possesses robust technical skills including programming in Python, Java, C, C++, web technologies (HTML), and experience with simulation platforms such as NS2 and MATLAB, as well as familiarity with open-source operating systems. Through her career she has mentored and guided multiple innovative and funded projects — for example leading a seed-research project titled “StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring,” and supervising award-winning student projects such as “Trash Triage: Trailblazing Waste Management with Real-Time Street Waste Monitoring” and “Identification of Fake Medicinal Raw Materials Using Machine Learning.” These recognitions reflect her commitment to practical, socially relevant research. Her academic repertoire includes teaching diverse subjects like Artificial Intelligence, Mobile Computing, Information Security, Web Programming, Soft Computing, Software Project Management, Cyber Security, Web Technology, and more. She has also supervised substantial academic work: a Ph.D. thesis on “Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments,” a secure payment-scheme design in multihop networks, and semantic similarity computation for natural language. As a scholar and mentor, Mrs. Raghi combines strong theoretical foundations with hands-on applied research, striving to develop secure, intelligent, and socially impactful computing solutions. Her involvement in both education and research along with project funding, awards, and diverse technical competencies — positions her as a proactive and forward-looking professional in the fields of AI, cybersecurity, and data-driven intelligent systems, committed to nurturing student talent and contributing to technological advancement.

Professional Profiles: ORCID | Google Scholar

Selected Publications

Thomas, R. K. L., Sanjay, G. J., Pandeeswaran, C., & Raghi, K. R. (2024). Advanced CCTV Surveillance Anomaly Detection, Alert Generation and Crowd Management using Deep Learning Algorithm.
Vethavikashini, A. M., Jamal, S. M., & Raghi, K. R. (2024). Huntington’s Disease Prediction Using Xception CNN.
Devi, S. R., Geetha Priya, S., Sathi, G., Naveen Kumar, S., Dinesh, M., & Raghi, K. R. (2024). Design and Development of a Touch Free Smart Home Controlling System Based on Virtual Reality (VR) Technology.
Raghi, K. R., Sudha, K., Sreeram, A. M., Steve Joshua, S. (2024). Software Development Automation Using Generative AI.
Raghi, K. R. (2023). Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments.
Anitha, T., Sai Srihitha, G. R. P. Lakshmi Aiswarya, & Raghi, K. R. (2025). Predictive Modeling of Social Media Data Using Machine Learning Techniques.
(As mentor) StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring.