Early Academic Pursuits

Dr. Sajid Ullah Khan embarked on his academic journey with a strong foundation in computer science. He earned his B.I.T. degree from Gomal University, Pakistan, followed by an M.S. in Computer Science from the University of Science & Technology, Bannu. His quest for knowledge led him to University Malaysia Sarawak (UNIMAS), Malaysia, where he obtained his Ph.D. in Image Processing & Computer Vision (2011-2015). Further enhancing his expertise, he completed two postdoctoral fellowships at UNIMAS (2016-2017) and Chosun University, South Korea (2022-2023), focusing on advanced research in image analysis and artificial intelligence.

 Professional Endeavors

With over nine years of teaching experience, Dr. Khan has held significant academic positions. He currently serves as an Associate Professor at Prince Sattam bin Abdulaziz University, KSA. Previously, he contributed as a faculty member at University of Lakki Marwat and CECOS University, Pakistan, and as a Tutor at UNIMAS, Malaysia. His dedication to education and research has helped shape the careers of many students in computer science and engineering.

 Contributions and Research Focus

Dr. Khan’s research interests lie in digital image processing, computer vision, data mining, and artificial intelligence applications. His notable projects include semantic extraction for road density estimation, floodplain mapping using GIS, and intelligent automation in medical image analysis. He has been actively involved in research groups such as MIP Lab at Chosun University and CoIMAST at UNIMAS, contributing to groundbreaking innovations in AI-driven image analysis.

 Impact and Influence

Dr. Khan’s scholarly contributions have been recognized on both national and international platforms. His research has enhanced the field of AI-driven image processing, leading to practical applications in medical diagnostics, automation, and smart surveillance. His work has also been instrumental in advancing ICT solutions and digital transformation in academia and industry.

Academic Cites & Recognitions

• 6th Position in DICE-IET 2020 at COMSATS University, Lahore
• Best Researcher Award at CECOS University (2018)
• UNIMAS Graduate Scholarship (ZSU) for Ph.D. studies

 Technical Skills

Dr. Khan is proficient in Matlab, Python, C, and C++, with expertise in data warehousing, HCI, database management systems, and advanced operating systems. His technical acumen allows him to develop and implement AI-based solutions in image processing and pattern recognition.

 Teaching Experience

Throughout his career, Dr. Khan has taught a variety of computer science courses, including Programming Fundamentals, Digital Image Processing, Human-Computer Interaction, Advanced Computer Architecture, and Data Structures & Algorithms. His pedagogical approach integrates theory with real-world applications, preparing students for careers in AI and computational sciences.

Leadership and Administrative Roles

• Director Administration, University of Lakki Marwat
• Associate Dean (Academics), University of Lakki Marwat
• Department Chairman at University of Lakki Marwat & CECOS University

 Legacy and Future Contributions

Dr. Khan continues to pioneer research in AI-driven image analysis, striving to bridge the gap between academia and industry. His future work aims to advance intelligent automation in medical imaging, real-time object detection, and deep learning applications. His vision is to mentor the next generation of AI researchers and contribute to global advancements in computational sciences. With a commitment to excellence and innovation, Dr. Sajid Ullah Khan remains a driving force in computer vision, AI research, and academic leadership.

Summary

Mr. Shuhuan Wang is a Ph.D. candidate in Biomedical Engineering at Northeastern University, specializing in ultrasound and medical image analysis. His work focuses on leveraging advanced engineering techniques to enhance diagnostic accuracy and clinical decision-making.

Education

• Ph.D. in Biomedical Engineering – Northeastern University (Ongoing)
• Master’s in Electronic Information – Tohoku University

Professional Experience

• Contributor to key R&D projects, including:
  • Jiangxi Provincial Project on ultrasound diagnosis for thyroid nodules.
  • Liaoning Provincial Project on AI-based cardiac assessment.
• Collaborations with prestigious hospitals like the Second Affiliated Hospital of Nanchang University and the General Hospital of the People’s Liberation Army Northern War Area.

Research Interests

• Ultrasound Image Analysis: Intelligent segmentation, enhancement, and classification for medical diagnosis.
• AI in Medicine: Developing innovative algorithms for accurate and efficient disease detection.

Summary

Prof Dr. Jinyuan Liao is a seasoned radiologist with 28 years of expertise in abdominal CT and MRI diagnostics. He has led multiple national and provincial research projects and authored 15 SCI-indexed publications with a total impact factor of 59. His work focuses on advancing diagnostic accuracy through radiomics and quantitative imaging.

Education

• Doctor of Medicine (M.D.): Guangxi Medical University

Professional Experience

• Radiologist: Specializing in abdominal imaging and diagnostics
• Research Leader: Directed three Natural Science Foundation projects

Research Interests

• Quantitative Imaging & Radiomics: Developing multi-modal radiomics models for liver and endometrial cancer diagnosis and prognosis
• Algorithmic Innovation: Enhancing lymph node metastasis prediction through diverse machine learning approaches

Early Academic Pursuits

Assoc Prof Dr. Zheng Wang began his academic journey with a Bachelor’s degree in Computational Mathematics from 1994 to 1998. His passion for mathematics and computational sciences set a strong foundation for his future endeavors. He further pursued a Master’s degree in Informatics at a German institution, completing his Diplom-Informatiker program between 2000 and 2005. This period also included a stay in Germany from August 1999 to May 2005, where he undertook the DSH exam and immersed himself in advanced informatics studies. His academic pursuits culminated in a Doctorate in Computational Mathematics from 2018 to 2022, marking a significant milestone in his scholarly achievements.

Professional Endeavors

Currently serving as an Associate Professor under Work Contract SYB2022440, Dr. Wang has dedicated his professional career to advancing medical imaging analysis and bioinformatics. His work focuses on developing computational models for multimodal data fusion in the medical field, significantly contributing to disease identification and diagnostic technologies. His commitment to academic excellence is evident through his engagement in teaching, research, and project leadership.

Contributions and Research Focus

Assoc Prof Dr. Wang’s research portfolio showcases a profound dedication to innovation in medical imaging and artificial intelligence. His ongoing projects, funded by prestigious organizations, include:

• Research on Intelligent Recognition of Pigment Ring Patterns (2024-2027)
• Clinical Application of AI for Pancreatic Biological Age Prediction (2025-2028)
• Graph Neural Network-Based Computer-Aided Diagnosis (2022-2024)

Additionally, his finalized projects highlight his expertise in deep learning applications for medical diagnostics, including esophageal manometry and medical image-based diagnoses.

Impact and Influence

Assoc Prof Dr. Wang’s contributions to computational mathematics and medical imaging have not only advanced academic knowledge but also provided practical solutions for medical diagnostics. His work has influenced peers and institutions, fostering interdisciplinary collaboration and inspiring the next generation of researchers in computational and medical sciences.

Academic Cites

Assoc Prof Dr. Wang’s scholarly works have been cited in numerous academic journals and conferences, reflecting the significance and applicability of his research. His work bridges computational theories and medical practices, garnering recognition within and beyond the academic community.

Technical Skills

• Advanced programming in Java, Python, and MATLAB
• Deep learning frameworks such as TensorFlow and PyTorch
• Multimodal data fusion techniques
• Graph neural networks and bioinformatics tools

Teaching Experience

Assoc Prof Dr. Wang has actively contributed to teaching reform, particularly in project-driven Problem-Based Learning (PBL). His efforts in Java course reform (2020-2024) have enhanced student engagement and learning outcomes, equipping students with practical, industry-relevant skills.

Legacy and Future Contributions