Mr. Jiahao Nie is a dedicated Ph.D. candidate at Hangzhou Dianzi University (HDU) and Hanyang University (HYU), specializing in computer vision, 2D image processing, and 3D point cloud processing. Under the guidance of Prof. Zhiwei He and Assoc. Prof. Dong-Kyu Chae, he is actively engaged in cutting-edge research in autonomous driving and object tracking.
Education
Ph.D. in Electronic Science and Technology (HDU, 2022-2025)
Joint Ph.D. in Computer Science (HYU, 2024-2025)
B.Eng. in Electronic Information Engineering (HDU, 2020-2022)
Research Interests
His research is primarily focused on computer vision, including 2D image processing, 3D point cloud processing, and object tracking for autonomous driving.
Honors & Awards
Ph.D. National Scholarship (Rank: 1/75) | Full Postgraduate Scholarship (2020-2025)
First-Class Academic Scholarship (Top 3%) | National Scholarship for Studying Abroad (2023)
Academic Contributions
Reviewer for ICCV, CVPR, ICLR, ICML, ECCV, NeurIPS, AAAI, ACM MM
Presenter at ICLR (2024), IJCAI (2023), AAAI (2023)
Publications
TTSNet: state-of-charge estimation of Li-ion battery in electrical vehicles with temporal transformer-based sequence network
Dr. Hua Ren is a dedicated researcher and lecturer specializing in image security, encryption, and data hiding. His expertise lies in visually secure encryption and authentication technologies, contributing significantly to high-impact journals and research projects in these domains.
Education
Ph.D. in Computer Science and Technology, Beijing University of Posts and Telecommunications (2019-2023)
Masterโs in Computer Science and Technology, Henan Normal University (2016-2019)
Bachelorโs in Computer Science and Technology, Henan Normal University (2012-2016)
Work & Research Experience
Lecturer (2023-Present) โ School of Computer and Information Engineering, Henan Normal University
Principal Investigator โ Henan Science and Technology Research Project on image reversible authentication (2025-2026)
Research Interests
Image Security & Encryption
Reversible Data Hiding
Visual Authentication & Cryptography
Digital Image Processing
Publications
A novel reversible data hiding method in encrypted images using efficient parametric binary tree labeling
Authors: Hua Ren, Zhen Yue, Feng Gu, Ming Li, Tongtong Chen, Guangrong Bai
Journal: Knowledge-Based Systems
Year: 2024
Multi-scale attention context-aware network for detection and localization of image splicing
Prof. Nema Salemโs academic journey began with a strong foundation in engineering and medical imaging. She earned her B.Sc. with honors in 1987 and later obtained her M.Sc. in 1990 from Alexandria University (AU), Egypt, specializing in mitral valve diagnosis. She further pursued her Ph.D. in โClassification of Breast Tumors by Acutance Measure and Shape Factorsโ through a joint program between the University of Calgary, Canada, and AU in 1996. Her early research laid the groundwork for advancements in medical diagnostics, particularly in breast cancer detection, setting the stage for a distinguished academic and research career.
Professional Endeavors
Prof. Salemโs professional trajectory spans multiple prestigious institutions. Since 1987, she has held progressive academic roles at AU, the Asian Institute of Technology (AIT), Hadramout University in Yemen, and Effat University in Saudi Arabia, where she has been an Assistant Professor since 2008. She has also served as the Chair of the Electrical and Computer Engineering Department at Effat University, contributing to curriculum development and accreditation processes such as NCAAA and ABET. Her leadership extends beyond academia, as she has organized international competitions like the IET GCC Robotics Challenge and the World Robot Olympiad, promoting innovation among young engineers.
Contributions and Research Focus
Prof. Salemโs research portfolio is marked by interdisciplinary contributions in medical imaging, artificial intelligence, control systems, and renewable energy. She has pioneered AI-driven applications, including ECG analysis, skin lesion segmentation, and glaucoma detection, enhancing the accuracy of medical diagnostics. Additionally, she has played a crucial role in renewable energy advancements, optimizing solar power generation and thermoelectric systems. Her expertise in robotics and control engineering is evident in her work on PID and LQR controllers for performance enhancement in automation and energy-efficient designs.
Impact and Influence
Prof. Salemโs influence extends beyond her research, as she actively mentors students, supervises masterโs and Ph.D. theses, and collaborates with international researchers. Her dedication to fostering innovation has resulted in students winning prestigious awards, including a bronze medal at the 49th International Exhibition in Geneva. She has also contributed significantly to the academic community through her editorial roles and peer-reviewing for high-impact journals. Her recognition includes the Queen Effat Award for Teaching Excellence (2019-2020, 2022-2023) and a UK Fellowship for teaching excellence, affirming her commitment to quality education and research.
Academic Citations and Publications
Prof. Salemโs research is well-documented in reputable journals and conferences. She has published extensively in IEEE Transactions on Medical Imaging, PLOS ONE, Sensors, and IEEE Access, with a strong presence in high-impact publications. Her work is widely cited, reflecting its significance in medical imaging, artificial intelligence, and renewable energy. Her research contributions are accessible via Google Scholar and the AD Scientific Index 2024, demonstrating her academic reach and influence.
Technical Skills and Expertise
Prof. Salem possesses a diverse technical skill set, encompassing AI-driven signal and image processing, robotics, logic design, and renewable energy optimization. She has expertise in developing machine learning models for medical diagnostics, implementing control strategies for automation, and designing CMOS-based circuits. Her ability to integrate interdisciplinary approaches has made her a sought-after researcher in multiple domains, from biomedical engineering to energy-efficient systems.
Teaching and Mentorship
With over three decades of teaching experience, Prof. Salem has played a pivotal role in shaping the next generation of engineers. She has designed and delivered courses in signal processing, artificial intelligence, control systems, and electronics. Her student-centered approach has been recognized through multiple teaching awards. She actively engages in student mentorship, encouraging innovative research projects and guiding them to success in international competitions and academic publishing.
Legacy and Future Contributions
Prof. Salemโs legacy is defined by her relentless pursuit of innovation and knowledge dissemination. Her research continues to push the boundaries of technology, particularly in AI-driven healthcare and renewable energy systems. She remains committed to mentoring students, expanding research collaborations, and advancing engineering education. Through her leadership, she aims to drive impactful change in medical diagnostics, sustainable energy, and robotics, ensuring a lasting influence in academia and industry.
Publications
Artificially Intelligent Detection of Retinal Pigment Sign Using P3S-Net for Retinitis Pigmentosa Analysis
Authors: Syed Muhammad Ali Imran, Abida Hussain, Nema Salem, Muhammad Arsalan Journal: Results in Engineering Year: 2025
Causal Speech Enhancement Using Dynamical-Weighted Loss and Attention Encoder-Decoder Recurrent Neural Network
Authors: Fahad Khalil Peracha, Abdullah M. Mutawa, Muhammad Irfan Khattak, Nema Salem, Nasir Saleem Journal: PLOS ONE Year: 2023
Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization
Authors: Abeer Mushtaq, Maria Mumtaz, Ali Raza, Nema Salem, Muhammad Naveed Yasir Journal: Sensors Year: 2022
Automated Diagnosis of Leukemia: A Comprehensive Review
Authors: Afshan Shah, Syed Saud Naqvi, Khuram Naveed, Nema Salem, Mohammad A. U. Khan, Khurram S. Alimgeer Journal: IEEE Access Year: 2021
DAVS-NET: Dense Aggregation Vessel Segmentation Network for Retinal Vasculature Detection in Fundus Images
Authors: Mohsin Raza, Khuram Naveed, Awais Akram, Nema Salem, Amir Afaq, Hussain Ahmad Madni, Mohammad A. U. Khan, Mui-zzud-din Journal: PLOS ONE Year: 2021