Janmejaya Mishra | Cybersecurity | Best Researcher Award

Mr. Janmejaya Mishra | Cybersecurity | Best Researcher Award

Capella University | United States

Mr. Janmejaya Mishra is a Principal Engineer with extensive expertise in developing and architecting high-performance web applications, combining strong academic foundations with professional excellence. He holds a Master of Science in Information Assurance and Cybersecurity from Capella University, graduating with distinction, and is currently pursuing a Doctor of Information Technology at the same institution. His career spans leadership in building scalable, secure, and high-traffic systems across education, telecom, healthcare, and finance sectors, with a specialization in Drupal, PHP, JavaScript, MySQL, and modern frameworks. He has delivered numerous Drupal projects from concept to production while ensuring cloud performance and application security through platforms such as Cloudflare, Splunk, and New Relic. A certified AWS Solutions Architect, Scrum Master, and Acquia Drupal Developer, he has earned recognition for advancing enterprise solutions and implementing innovative frameworks. His blend of research, technical mastery, and practical contributions positions him as an influential leader in cybersecurity and software engineering.

Profile: Scopus | Orcid

Featured Publications

1. Mohapatra, K., Mishra, J., Pattanaik, S. R., Pati, A., Panigrahi, A., & Sahu, B. (2025). EFSMLHA: Ensembled feature selected machine learning hybrid approaches for heart disease prediction. 2025 International Conference in Advances in Power Signal and Information Technology (APSIT 2025). IEEE.

2. Mishra, J., Biswal, B. B., & Padhy, N. (2025). Machine learning for fraud detection in banking cyber security: Performance evaluation of classifiers and their real-time scalability. 2025 5th International Conference on Emerging Systems and Intelligent Computing (ESIC 2025) Proceedings. IEEE.

3. Sahu, B., Mishra, J., Parveen, S., Das, B., Panigrahi, A., & Pati, A. (2025). STIR-MO: An enhanced hybrid cancer predictive model. 2025 3rd International Conference on Intelligent and Cloud Computing (ICoICC 2025). IEEE.

Jamshed AliShaikh | Cybersecurity | Best Researcher Award

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

Google Scholar

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.

Jing Li | Cybersecurity | Best Researcher Award

Dr. Jing Li | Cybersecurity | Best Researcher Award

Dr. Jing Li, University Technology Malaysia, China

🎓 Dr. Jing Li is pursuing his PhD in Computer Science at University Technology Malaysia (UTM) since 2021. He holds a Master’s in Information Management from ZheJiang University and a Bachelor’s in Computer Science from China JiLiang University. With over 15 years in the ICT industry, he specializes in networking, cybersecurity, and IoT. His research interests span IoT security, digital forensics, big data, and machine learning. Dr. Li has authored several publications in prestigious journals and is an active member of IEEE. He is also proficient in AI-based scientific research tools

Publication profile

Scopus

Education 🎓

Dr. Jing Li is currently pursuing his PhD in Computer Science at University Technology Malaysia (UTM), where he also holds an International Doctoral Scholarship. He earned his Master’s degree in Information Management from ZheJiang University and a Bachelor’s in Computer Science from China JiLiang University, Hangzhou.

Professional Experience 💼

Dr. Li has held roles including Technical Co-founder at Hangzhou Yunmei Technology Co., Ltd., Product Architect at ArcSoft (Hangzhou) Technology Co., Ltd., and Software Engineer at Aerohive Networks, inc. His expertise spans networking, cybersecurity, IoT, and machine learning.

Research Focus

Dr. Jing Li’s research focuses on enhancing IoT security through advanced machine learning techniques. His work primarily explores feature selection and reduction methods for improving intrusion detection systems in IoT environments. Through critical reviews and comparative studies, Dr. Li aims to optimize classification models, contributing significantly to the fields of cybersecurity and digital forensics. His research, published in prestigious journals like the Journal of Big Data and Intelligent Systems with Applications, underscores his expertise in applying AI-driven solutions to mitigate IoT security risks. Dr. Li’s efforts are pivotal in advancing the understanding and implementation of robust security measures in interconnected systems. 🔒

Publication Top Notes

Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning

Enhancing IoT security: A comparative study of feature reduction techniques for intrusion detection system

A critical review of feature selection methods for machine learning in IoT security