Assist Prof Dr. Mahmoud Emam | Image Generation | Best Researcher Award

Assist Prof Dr. Mahmoud Emam : Leading Researcher in Image Generation

Hangzhou Dianzi University  at Image Generation, School of Computer Science and Technology, China

He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Dr. Mahmoud Emam is an Assistant Professor with a strong background in Computer Science and Technology. He earned his Ph.D. from the Research Institute of Information Countermeasure Techniques at the School of Computer Science and Technology, Harbin Institute of Technology, Harbin, P.R. China, where he conducted research in his field. Prior to his doctoral studies, Dr. Emam completed his M.Sc. in Computer Science at the Computer Science Division, Faculty of Science, Menoufia University, Shebin Elkoom, Menoufia, Egypt, where he laid the foundation for his academic journey. He also underwent pre-courses for M.Sc. in Computer Science at the same institution. Dr. Emam’s academic journey began with a B.Sc. in Pure Mathematics and Computer Science from the Computer Science Division, Faculty of Science, Menoufia University, Shebin Elkoom, Menoufia, Egypt, where he developed a strong foundation in his field. His academic pursuits and research contributions reflect his dedication to advancing knowledge in Computer Science and Technology.

Research Interests:

Dr. Mahmoud Emam‘s research interests are centered around several key themes in computer science, including Digital Image Processing, Multimedia Security, Pattern Recognition, and Computer Vision. His expertise extends to the specialized area of Digital Image and Video Forensics, where he applies his knowledge to analyze and enhance the security of digital media. Dr. Emam’s work in these fields demonstrates his commitment to advancing the understanding and application of computer science principles, particularly in the context of digital media and information security.

Experience:

Dr. Mahmoud Emam has a diverse professional background spanning both teaching and research roles. His career began in 2007 when he served as a Teaching Assistant in computer science at the Computer Science Division, Faculty of Science, Menoufia University, Egypt, where he contributed to the education and development of students in the field of computer science. In 2013, he transitioned into a research-focused role as a Research Associate (Ph.D. Candidate) at the Research Institute of Information Countermeasure Techniques, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, P.R. China. During this time, he was actively engaged in research activities related to his doctoral studies. Following the completion of his Ph.D., Dr. Emam assumed the role of Assistant Professor of Computer Science at the Computer Science Division, Faculty of Science, Menoufia University, Egypt, where he continued to contribute to both teaching and research. His dedication to academia and research led to his appointment as an Assistant Professor at the Machine Intelligence Department, Faculty of Artificial Intelligence, Menoufia University, Egypt, starting in January 2022. In November 2022, he took on the position of a Postdoctoral Research Fellow at the Shangyu Institute of Science and Engineering Co., Ltd., Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, China, where he is involved in advanced research endeavors. Throughout his career, Dr. Emam has demonstrated a strong commitment to both academic instruction and cutting-edge research, positioning himself as a valuable contributor to the fields of computer science, artificial intelligence, and machine intelligence.

Publication:

Fabric defect detection based on saliency map and keypoints

Frame Duplication Forgery Detection in Surveillance Video Sequences Using Textural Features

Anti-pruning multi-watermarking for ownership proof of steganographic autoencoders

Fast Frequency Domain Screen-Shooting Watermarking Algorithm Based on ORB Feature Points

Spatiotemporal fusion for spectral remote sensing: A statistical analysis and review

A Novel Hybridoma Cell Segmentation Method Based on Multi-Scale Feature Fusion and Dual Attention Network

A Sketch-Based Generation Model for Diverse Ceramic Tile Images Using Generative Adversarial Network

Data Augmentation and Few-Shot Change Detection in Forest Remote Sensing

Semi-Supervised Remote Sensing Image Semantic Segmentation Method Based on Deep Learning

Mr. Sebastian Vacca | Neuroimaging

🎉🏆 Congratulations, Mr. Sebastian Vacca , on Your Outstanding Achievement as the Best Researcher! 🏆🎉
Mr. Sebastian Vacca : Leading Researcher in Social Work

Medical Student at Neuroimaging, UniversitĂ  degli Studi di Cagliari, Italy

Your remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 Your successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Research Collaborator at Mayo Clinic

At Mayo Clinic, I serve as a Research Collaborator, contributing to a focused Deep Learning Project aimed at enhancing the segmentation of brain tumors, with a particular emphasis on intracranial meningiomas. Under the guidance of Supervisor Gian Marco Conte, MD PhD, my role involves applying advanced techniques to improve the accuracy of brain tumor segmentation.

Research Assistant at Cagliari State University – Radiology Department

As a Research Assistant at Cagliari State University’s Radiology Department, I actively participate in multiple projects investigating radiological anomalies. Employing Statistical methods and Machine Learning models, I analyze clinical and imaging data from patients with neurologic lupus. Additionally, I lead efforts in conducting systematic reviews with meta-analysis, specifically focusing on the application of radiomics in carotid atherosclerotic disease. I am also involved in constructing a machine learning model based on radiomics and automated segmentation to predict atherosclerotic plaque at risk for stroke, working under the guidance of Professor Luca Saba, MD.

Scientific Collaborator at One Medic – The One Health Community

In my role as a Scientific Collaborator at One Medic, I am an active member of the Research and Podcast Team. I contributed to a Bibliometric study, exploring the most cited articles in the field of One Health. Additionally, I played a crucial role in organizing and supporting podcast activities, combining research insights with effective communication strategies.

Diverse Research and Academic Contributions

Research Trainee – International Journal of Clinical Research [ 03/2023 – 12/2023 ] As the Group Leader for a Neurology Research Working Group, I led a comprehensive review on treatment options for Multiple Sclerosis. This role allowed me to delve into the intricacies of neurological research, contributing valuable insights to the field.

Visiting Medical Student – Technische Universität MĂĽnchen [ 01/09/2022 – 30/11/2022 ] During my tenure as a student researcher in the Functional Neuronavigation and Monitoring Working Group, I played a crucial role in analyzing clinical, DTI, and Tractography data from patients with a Corpus Callosum GBM. Responsible for data collection, I also contributed to CC segmentation using ITK-SNAP, tumor segmentation, Fiber-Tracking on BrainLab Elements, and performed statistical analysis under the guidance of Prof Dr. Med Sebastian Ille.

Publication

Title: SBM vs VBM for highlighting similarities and differences between Chronotype and Parkinson’s MRI scans: a preliminary analysis

Publication Date: 2023

Authors: Sebastiano Vacca, Jyoti Suri, Luca Saba

Journal: International Journal of Neuroscience