Dr Lili Zhao | Biomedical Engineering |

Dr Lili Zhao | Biomedical Engineering | Women Researcher Award

Department of Computer Science, Nantong University, China

Dr. Lili Zhao, born in Xinxiang, China, is a distinguished researcher specializing in Artificial Intelligence, Computer Vision, and Biomedical Image Processing. Currently serving in the Department of Computer Science at Nantong University, she has built a career dedicated to innovative research and teaching. She earned her Doctor of Engineering from the National University of Defense Technology and completed her postdoctoral research at Shanghai Jiao Tong University. With an international research stint at the University of Leicester, UK, Dr. Zhao has strengthened global academic ties. Her work has led to impactful publications in SCI-indexed journals and international conferences. Known for her contributions to medical imaging—particularly in fetal ultrasound and cervical cancer diagnostics—she integrates deep learning and algorithmic optimization in her projects. Beyond research, she passionately teaches courses in machine learning, C++, and digital image processing, fostering the next generation of computer scientists.

🎓 Education

Dr. Lili Zhao’s academic journey reflects a strong foundation in Computer Science and Artificial Intelligence. She earned her Bachelor of Engineering (2007) from Xinyang Normal University, followed by a Master of Engineering (2011) from Henan Normal University, majoring in Computer Application Technology. Her thirst for advanced research led her to pursue a Doctor of Engineering (2017) in Computer Science at the National University of Defense Technology, one of China’s top institutions. From 2018 to 2024, she conducted postdoctoral research in Artificial Intelligence at Shanghai Jiao Tong University, focusing on medical image processing. She also spent 2022–2023 as an academic visitor at the University of Leicester, UK, further enriching her international perspective in AI research. Her consistent academic excellence and cross-disciplinary training uniquely position her to address challenges at the intersection of computing and biomedical engineering.

💼 Experience

Dr. Zhao currently serves in the Department of Computer Science at Nantong University, where she is involved in both teaching and research within the School of Artificial Intelligence and Computer Science. Over the years, she has held various academic positions, with hands-on experience in research laboratories focused on biomedical image processing, deep learning, and AI-powered healthcare diagnostics. During her postdoctoral work at Shanghai Jiao Tong University, she developed advanced frameworks for fetal ultrasound image assessment and cervical cancer detection. She also collaborated internationally during her academic visit to the University of Leicester, contributing to joint projects in algorithmic optimization and uncertainty quantification. Her teaching record includes courses such as Machine Learning, C++ Programming, and Digital Image Processing, emphasizing her balanced engagement in both scientific innovation and student mentorship.

🔬 Research Focus

Dr. Lili Zhao’s research is centered on the development of AI-driven solutions for biomedical image analysis, particularly in fetal imaging and cervical cell diagnostics. Her work combines image processing, computer vision, and algorithm optimization to enable early and accurate diagnosis of medical conditions. She employs deep learning techniques to address challenges such as image quality assessment, segmentation, and classification under uncertainty or label shift. Her projects integrate multi-phase detection, extreme learning machines, and MRF-based segmentation for cytological images, contributing significantly to early cancer detection and maternal health monitoring. These solutions have the potential to be integrated into smart diagnostic systems and telemedicine platforms. Dr. Zhao’s research not only improves diagnostic efficiency but also ensures cost-effective healthcare delivery, particularly in under-resourced settings.

📄 Publication Top Notes

 

 

Umar Islam | Computer Science | Best Researcher Award

Mr. Umar Islam | Computer Science | Best Researcher Award

Senior Lecturer, IQRA National University Swat Campus, Pakistan

Mr. Umar Islam is a passionate and accomplished educator and researcher in the field of Computer Science, currently serving as a Lecturer at Iqra National University (INU) Swat Campus, Pakistan. With an impressive academic background spanning 18 years in Computer Science, Mr. Islam has become a recognized expert in AI, machine learning, blockchain security, IoT, bioinformatics, and financial analytics. His work has been published in over 15 research articles, including several in top-tier journals. A dedicated researcher, he focuses on real-time AI solutions, particularly in healthcare and cybersecurity. Mr. Islam is also a committed mentor, providing supervision and guidance to students in advanced topics such as Python programming, machine learning, and AI applications. His contributions to the academic community and his research endeavors demonstrate his commitment to pushing the boundaries of knowledge and solving real-world problems.

Profile

Education

Mr. Umar Islam has an extensive academic journey, earning 18 years of education in Computer Science. His academic path began with a Bachelor’s degree in Computer Science, followed by a Master’s degree, where he built the foundation of his knowledge in various aspects of computing. Mr. Islam’s thirst for knowledge and his passion for research led him to pursue advanced studies in areas like AI, machine learning, IoT, and cybersecurity, with a strong focus on applying these technologies to solve real-world challenges. His educational journey has equipped him with the skills to lead cutting-edge research projects and to innovate in fields like bioinformatics and financial analytics. Currently, he is working toward a PhD, which will further deepen his understanding and expertise in these areas. Through his education, Mr. Islam has gained a comprehensive understanding of theoretical and applied Computer Science, which he integrates into both his teaching and research.

Experience

With six years of teaching experience at the higher education level, Mr. Umar Islam has played a pivotal role in shaping the future of numerous students at Iqra National University (INU) Swat Campus. As a lecturer, he has delivered comprehensive lessons in Computer Science topics such as AI, machine learning, and cybersecurity. His commitment to academic excellence is reflected in his success as a supervisor, guiding students through complex topics like Python programming, e-learning analytics, and AI-driven applications. In addition to teaching, Mr. Islam has gained four years of extensive research experience, with a focus on AI applications in healthcare, cybersecurity, and blockchain security. He has led multiple research projects, producing groundbreaking results, and has contributed significantly to the academic community with over 15 published research articles. His academic experience extends beyond teaching, positioning him as a thought leader in his field.

Research Focus

Mr. Umar Islam’s research is deeply focused on the intersection of artificial intelligence (AI), cybersecurity, healthcare, and financial analytics. One of his key research areas includes AI-driven solutions in healthcare, particularly the development of federated learning-based intrusion detection systems and epileptic seizure prediction models. He is also actively exploring AI in cybersecurity, specifically in blockchain security, to mitigate data tampering risks. His work in financial analytics uses AI and machine learning to predict market trends, including cryptocurrency values, demonstrating his interdisciplinary approach to solving real-world problems. In addition to these topics, Mr. Islam is involved in pioneering research in IoT security and bioinformatics. His research aims to address key global challenges such as healthcare delivery, data security, and economic stability through cutting-edge AI applications. His innovative contributions to various fields have resulted in multiple published articles in prestigious journals, demonstrating the far-reaching impact of his work.

Publication Top Notes

  • Detection of distributed denial of service (DDoS) attacks in IoT-based monitoring system of banking sector using machine learning models 🌐🔐📊
  • IOTA-Based Mobile Crowd Sensing: Detection of Fake Sensing Using Logit-Boosted Machine Learning Algorithms 🤖📱💡
  • Real-time detection schemes for memory DoS (M-DoS) attacks on cloud computing applications ☁️💻🛡️
  • Detection of renal cell hydronephrosis in ultrasound kidney images: a study on the efficacy of deep convolutional neural networks 🏥🧠📸
  • A novel anomaly detection system on the internet of railways using extended neural networks 🚆🔍⚙️
  • NeuroHealth guardian: A novel hybrid approach for precision brain stroke prediction and healthcare analytics 🧠💓📈
  • An intelligent approach for preserving the privacy and security of a smart home based on IoT using LogitBoost techniques 🏠🔐💡
  • Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets 💰📊📉
  • Investigating the Effectiveness of Novel Support Vector Neural Network for Anomaly Detection in Digital Forensics Data 💾🔎👨‍💻
  • Empowering global ethereum price prediction with EtherVoyant: a state-of-the-art time series forecasting model ⛓️💹🔮