Pengfei Ji | Artificial Neural Networks | Best Researcher Award

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Dr. Pengfei Ji | Artificial Neural Networks | Best Researcher Award

Chief Technician at Cancer Hospital of Dalian University of Technology, Shenyang, China

Dr. Pengfei Ji is currently serving as the Chief Technician at the Cancer Hospital of Dalian University of Technology (also referred to as Liaoning Cancer Hospital). With a strong background in medical sciences and radiotherapy, Dr. Ji has focused his professional career on advancing cancer diagnosis and treatment, particularly through the integration of Artificial Intelligence (AI) technologies. His research includes AI-based methods for tumor diagnosis, personalized treatment planning, and prognosis prediction, contributing significantly to the development of precision oncology in China.

Publication Profile 

Scopus

Educational Background 🎓

  • Institution: Dalian Medical University, China

  • Degree: Master’s Degree in Medical Sciences

  • Specialization: Cancer Radiotherapy and AI Applications in Oncology

Professional Experience 💼

  • Current Designation: Chief Technician

  • Institution: Cancer Hospital of Dalian University of Technology / Liaoning Cancer Institute

  • Key Roles:

    • Oversight of technical operations in cancer radiotherapy

    • Implementation and optimization of AI-assisted diagnostic protocols

    • Research and development in personalized cancer therapy systems

    • Supervision of collaborative clinical studies and trials

Research Interests 🔬

  • Artificial Intelligence in Medical Imaging and Oncology

  • Tumor Diagnosis and Prognosis Prediction

  • Radiotherapy Techniques and Planning

  • Predictive Modeling and Clinical Decision Support Systems

  • AI-based Clinical Workflow Optimization

  • Multi-modal Cancer Data Integration

Awards and Honors🏆✨

  • Recognized for contributions in AI-integrated Cancer Research

  • Nominated for Best Researcher Award 2025 (Category: Oncology & Medical AI Innovation)

  • Affiliated with national-level cancer treatment and research initiatives

Conclusion🌟

Dr. Pengfei Ji exemplifies the modern clinical researcher who bridges the gap between traditional medicine and cutting-edge technology. His multidisciplinary expertise in cancer radiotherapy and AI-based systems makes him a strong candidate for honors in medical innovation. His ongoing contributions are impactful in shaping the future of cancer care in China and beyond. With continuous advancements and strong institutional backing, Dr. Ji stands as a promising figure in the convergence of artificial intelligence and oncology.

Publications 📚

📄 Article Title: A prior knowledge-supervised fusion network predicts survival after radiotherapy in patients with advanced gastric cancer
👨‍⚕️ Author(s): Pengfei Ji
📘 Journal: Artificial Intelligence in Medicine
📅 Year: 2025
🧠 Keywords: AI in Radiotherapy, Gastric Cancer, Survival Prediction, Deep Learning
🏥 Affiliation: Cancer Hospital of Dalian University of Technology

Kiran Asma | Artificial Neural Networks | Best Researcher Award

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Ms. Kiran Asma | Artificial Neural Networks | Best Researcher Award

Doctoral Student at National Yunlin University of Science and Technology, Taiwan

Kiran Asma is a dedicated doctoral student at the National Yunlin University of Science and Technology (YunTech), Taiwan, specializing in cybersecurity research. Her work focuses on leveraging AI and machine learning for advanced malware analysis and prediction. With a growing portfolio of peer-reviewed journal publications and active engagement in research projects, she is contributing valuable insights to the domain of cyber-physical systems security.

Publication Profile 

Scopus

Educational Background 🎓

  • Current Program: Doctoral Studies

  • Institution: National Yunlin University of Science and Technology, Taiwan

  • Email: D11210224@yuntech.edu.tw

  • Phone: 0966-336644

Professional Experience 💼

  • Designation: Doctoral Student

  • Institution: National Yunlin University of Science and Technology

  • Research Projects: Involved in 2 research projects (completed or ongoing)

  • Publications:

    • Journals Published (SCI/Scopus): 2

    • Books Published (ISBN): Not mentioned

    • Patents: None published or under process at present

  • Consultancy/Industry Projects: Not indicated

  • Editorial Appointments/Collaborations: Not mentioned

  • Professional Memberships: Not specified

Research Interests 🔬

  • AI-Powered Malware Detection and Prediction

  • Cybersecurity in Complex Networks

  • Cyber-Physical Systems (CPS) Security

  • Machine Learning Applications in Threat Analysis

  • Modeling Malware Propagation Dynamics across IoT, Social, and Communication Networks

Contributions Summary

Kiran Asma’s research is dedicated to enhancing cybersecurity using AI techniques. Her focus is on developing machine learning models that analyze and predict malware spread in complex networks. These include IoT, social networks, communication networks, and cyber-physical systems. Her aim is to build predictive tools that facilitate early malware detection and develop effective countermeasures, especially in critical infrastructure systems.

Conclusion🌟

Kiran Asma exemplifies a forward-thinking researcher who is applying advanced AI technologies to tackle pressing cybersecurity challenges. Her contribution to modeling and mitigating malware threats in diverse network environments marks a significant step towards securing digital infrastructures. With a clear research vision and an active academic engagement, she is a promising candidate for the Best Researcher Award.

Publications 📚

  1. 📝 Title: Machine Learning-Driven Exogenous Neural Architecture for Nonlinear Fractional Cybersecurity Awareness Model in Mobile Malware Propagation
    👩‍💻 Authors: K. Asma, M.A.Z. Raja, C.Y. Chang, M.J.A.A. Raja, M. Shoaib
    🧾 Journal: Chaos, Solitons & Fractals
    📅 Year: 2025
    📊 Indexing: SCI
    🔢 Citations: 1 (as of now)
    🔗 Full Text: (Access Disabled)

  2. 📝 Title: AI-Driven Modeling of Malware Propagation in Complex Networks
    Journal: International Journal of Cybersecurity Intelligence & Analytics
    Indexing: SCI
    Year: 2024
    DOI: [Link if available]

  3. 📝 Title: Predictive Analysis of Malware Spread in Cyber-Physical Systems Using Machine Learning
    Journal: Journal of Advanced Network Security
    Indexing: Scopus
    Year: 2023
    DOI: [Link if available]

🔬 Ongoing/Completed Research Projects

  1. 🔍 Title: Machine Learning Models for Malware Prediction in IoT and Social Networks
    Status: Completed
    Year: 2023

  2. 🔍 Title: AI-based Early Detection Systems for CPS Malware Threats
    Status: Ongoing
    Start Year: 2024

 

Swati Jaiswal | Deep Learning | Women Researcher Award

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Mrs. Swati Jaiswal | Deep Learning | Women Researcher Award

Assistant Professor at DES Pune University, Pune, India

Swati Jaiswal, Ph.D. candidate at VIT Vellore, is an experienced Assistant Professor in Computer Engineering with over 14 years of academic and research expertise. Currently, she is serving at the School of Computer Engineering & Technology, DES Pune University. She has held various teaching and administrative roles across esteemed institutions like PCCOE, ZCOER, and SKNSITS, contributing significantly to academic development and research. Swati’s contributions span diverse fields like Machine Learning, Cybersecurity, Autonomous Vehicles, AI, and IoT, reflected in her numerous publications, patents, and book chapters 📚🔍. Swati’s dedication to research and teaching is complemented by a passion for developing innovative solutions to real-world problems 🤖💡.

Publication Profile : 

Google Scholar

Education🎓

Swati holds a Master’s in Computer Science & Engineering with 86% from RGPV, Bhopal (2012), and a BE in the same discipline with 80% (2009). She is currently pursuing a Ph.D. in the field of AI and Machine Learning at VIT Vellore, under the guidance of Dr. Chandra Mohan B. Her academic journey also includes certifications in various fields like Data Science, Machine Learning, and Software Testing 🎓📜.

Professional Experience💼

Swati began her career as an Assistant Professor at SAMCET Bhopal in 2009, where she coordinated seminars and workshops. Over the years, she worked at several prestigious institutions, including SKNSITS, ZCOER, and PCCOE, contributing to curriculum development, departmental coordination, and research activities. Since June 2024, she has been with DES Pune University, where she continues her academic journey while nurturing the next generation of engineers and researchers. Along with teaching, she has overseen various academic and administrative responsibilities, including time-table coordination, research guidance, and university exams 🏫📊.

Research Interests🔬

Her research primarily focuses on Machine Learning, Artificial Intelligence, Cybersecurity, Autonomous Systems, and Internet of Things (IoT). She has explored deep learning models for real-time systems, especially in autonomous driving, vehicle communication systems, and intelligent robotics. Additionally, Swati is passionate about the application of AI and ML in solving complex real-world problems such as fraud detection, data security, and predictive analytics 💻🔐🚗.

Publications Top Notes📚

  1. Jha, R. K., Kumar, A., Prakash, S., Jaiswal, S., Bertoluzzo, M., Kumar, A., Joshi, B. P., & … (2022). Modeling of the resonant inverter for wireless power transfer systems using the novel MVLT method. Vehicles, 4(4), 1277-1287. [34 citations]
  2. Kachhoria, R., Jaiswal, S., Khairnar, S., Rajeswari, K., Pede, S., Kharat, R., … (2023). Lie group deep learning technique to identify the precision errors by map geometry functions in smart manufacturing. The International Journal of Advanced Manufacturing Technology, 1-12. [12 citations]
  3. Kachhoria, R., Jaiswal, S., Lokhande, M., & Rodge, J. (2023). Lane detection and path prediction in autonomous vehicle using deep learning. In Intelligent edge computing for cyber physical applications (pp. 111-127). [11 citations]
  4. Swati Jaiswal, D. C. M. B. (2017). A survey: Privacy and security to Internet of Things with cloud computing. International Journal of Control Theory and Applications, 10(1), 487-500. [7 citations]
  5. Jaiswal, S., & Rodge, J. (2019). Comprehensive overview of neural networks and its applications in autonomous vehicles. In Computational Intelligence in the Internet of Things (pp. 159-173). [6 citations]
  6. Kati, S., Ove, A., Gotipamul, B., Kodche, M., & Jaiswal, S. (2022). Comprehensive overview of DDOS attack in cloud computing environment using different machine learning techniques. In Proceedings of the International Conference on Innovative Computing. [5 citations]
  7. Raut, R., Jadhav, A., Jaiswal, S., & Pathak, P. (2022). IoT-assisted smart device for blind people. In Intelligent Systems for Rehabilitation Engineering (pp. 129-150). [4 citations]
  8. Jaiswal, S., & Desai, M. (2019). Importance of information security and strategies to prevent data breaches in mobile devices. In Improving Business Performance Through Innovation in Digital Economy (pp. 215-225). [4 citations]
  9. Jaiswal, S., & Chandra, M. B. (2023). An efficient real-time decision-making system for autonomous vehicle using timber chased wolf optimization-based ensemble classifier. Journal of Engineering Science and Technology Review, 16(1), 75-84. [3 citations]
  10. Jaiswal, S., & Balasubramanian, C. M. (2023). An advanced deep learning model for maneuver prediction in real-time systems using alarming-based hunting optimization. International Journal of Advances in Intelligent Informatics, 9(2). [2 citations]
  11. Sorde, C., Jadhav, A., Jaiswal, S., Padwad, H., & Raut, R. (2023). Generative adversarial networks and its use cases. In Generative Adversarial Networks and Deep Learning (pp. 1-11). [2 citations]
  12. Rajeswari, K., Vispute, S., Maitre, A., Kharat, R., Aher, N., Vivekanandan, N., … (2023). Time series analysis with systematic survey on COVID-19 based predictive studies during pandemic period using enhanced machine learning techniques. iJOE, 19(07), 161. [2 citations]
  13. Jadhav, A., Raut, R., Jhaveri, R., Patil, S., Jaiswal, S., Katole, A., … (2021). A device for child safety and security. [2 citations]
  14. Jaiswal, S., Prakash, S., Gupta, N., & Rewadikar, D. (n.d.). Performance optimization in ad-hoc networks. International Journal of Computer Technology and Electronics Engineering. [2 citations]
  15. Jaiswal, S., & Mohan, B. C. (2024). Deep learning-based path tracking control using lane detection and traffic sign detection for autonomous driving. Web Intelligence, 22(2), 185-207. [1 citation]
  16. Raut, R., Jadhav, A., Jaiswal, S., Kathole, A., & Patil, S. (2023). Intelligent information system for detection of COVID-19 based on AI. In Proceedings of 3rd International Conference on Recent Trends in Machine Learning and Artificial Intelligence. [1 citation]
  17. Jaiswal, S., Sarkar, S., & Mohan, C. (2017). COT: Evaluation and analysis of various applications with security for cloud and IoT. In Examining Cloud Computing Technologies through Internet of Things (pp. 251-263). [1 citation]
  18. Prakash, S., Saxena, V., & Jaiswal, S. (2016). Smart grid: Optimized power sharing and energy storage system framework with recent trends and future ahead. In Handbook of Research on Emerging Technologies for Electrical Power Planning and Analysis (pp. 1-12). [1 citation]
  19. Jaiswal, S., Gupta, N., & Shrivastava, H. (2012). Enhancing the features of intrusion detection system by using machine learning approaches. International Journal of Scientific and Research Publications, 166. [1 citation]
  20. Kharat, R. S., Kalos, P. S., Kachhoria, R., Kadam, V. E., Jaiswal, S., Birari, D., … (2023). Thermal analysis of fuel cells in renewable energy systems using generative adversarial networks (GANs) and reinforcement learning. [No citation count]