Zainab El Arbi | Medicine and Health Sciences | Women Researcher Award

Mrs. Zainab El Arbi | Medicine and Health Sciences | Women Researcher Award

enseignante ISSEP-KS (Higher Institute of Sport and Physical Education of Ksar Saïd) Tunisia

Zaineb El Arbi is a dedicated educator and researcher at the Higher Institute of Physical Activity and Sport, Ksar Said, Tunisia, with a strong commitment to child motor development and adapted physical education. Beginning her career as a swimming coach and a teacher for deaf children, she has spent over a decade observing and addressing motor and behavioral challenges in young children. Her passion lies in shaping inclusive and intervention-based physical activity programs for preschoolers, especially those with special needs like deafness and autism.

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🎓 Education

Zaineb’s academic journey is rooted in the Sciences and Technics of Physical Activities and Sport, where she developed expertise in early childhood motor development and adaptive physical education. Her research is also deeply connected to her ongoing thesis, emphasizing practical, community-driven solutions for children’s physical well-being in Tunisia.

💼 Experience

Zaineb started her career as a swimming coach and an adapted physical education teacher at a special school for deaf children. Over the years, her hands-on work with children displaying motor and behavioral difficulties inspired her research into early intervention. Currently, she serves as a teacher and researcher at her institution, combining practical experience with scientific inquiry to support inclusive education in early childhood.

🔬 Research Interests

Zaineb’s primary research interests include motor development, motor impairments, and disabilities in preschoolers. Her work focuses on early detection and intervention strategies for Tunisian children, particularly those facing developmental challenges due to deafness or autism. She collaborates with specialized labs like Pearson Laboratory, using tools like the MABC-2 battery to assess motor competence in young children.

🏆 Awards

Zaineb is applying for the Prix de la femme chercheuse (Women Researcher Award) in recognition of her impactful work in child motor development. Her mission to improve early childhood education and public health through physical activity programs stands as a meaningful contribution to Tunisian society.

📚 Publications Top Notes: 

Zaineb recently published an article in the SpringerNature journal, Sport Sciences for Health, titled:
“Assessment of motor competence in Tunisian preschoolers using MABC-2 battery”
📖 Read Publication (2025)
📰 Journal: Sport Sciences for Health
🔗 Cited by: ResearchGate Article

Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Dr. Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Assistant Prof Mayo clinic, Rochester United States

Yashbir Singh is an Assistant Professor in Radiology with extensive experience in biomedical engineering and computational deep learning methods for medical imaging analysis. His research focuses on AI-driven approaches for early cancer detection, particularly in liver cancer, and has made substantial contributions to the integration of topological data analysis with deep learning. With a background in pharmaceutics, bioinformatics, and biomedical engineering, Yashbir brings a unique interdisciplinary perspective to medical imaging. His work is instrumental in advancing AI methodologies for clinical applications and patient-specific risk assessments in liver diseases. 🌐💡

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Education

Yashbir Singh completed his Bachelor’s in Pharmaceutics and Drug Design from M.J.P. Rohilkhand University, Bareilly, India, followed by a Master’s in Bioinformatics from the Indian Institute of Information Technology, Allahabad. He then earned his PhD in Biomedical Engineering from Chung Yuan Christian University, Taiwan. After completing his postdoctoral work in AI Radiology at Mayo Clinic, he continued his research at the same institution as a Postdoctoral Fellow in AI Radiology. 🎓🔬

Experience

Yashbir Singh has held various prestigious positions, including visiting faculty at Harvard Medical School and a medical scientist at WVU Medicine, West Virginia. He has also been a junior research fellow at IIT Mandi, India, and a teaching assistant at IIIT Allahabad, India, and Chung Yuan Christian University, Taiwan. His diverse experiences across academia and clinical environments have significantly shaped his research in medical imaging and AI. 🌍👨‍⚕️

Research Interest

Dr. Singh’s research interests lie in the intersection of artificial intelligence, medical imaging, and oncology. He has pioneered the use of algebraic topology-based machine learning for predicting clinical outcomes, specifically in liver diseases like primary sclerosing cholangitis. His current work focuses on developing deep learning frameworks for early cancer detection, integrating machine learning with topological data analysis, and improving patient-specific diagnostic tools. 🔍💻🧬

Award

Yashbir Singh has received several prestigious awards, including the 2024 Research Award from RSNA and Best Paper Presenter at IEEE CCWC 2022. His work has been recognized for its innovation in AI-driven medical imaging and clinical applications. In addition, he has received Best Reviewer Awards from ICSPIS and the 2020 Medical Imaging Best Paper Award from SPIE. These accolades highlight his leadership in the field of AI-based medical research. 🏆📜

Publication Top Notes:

Yashbir Singh has contributed to over 20 high-impact publications. Some notable works include:

Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions

Mitigating bias in radiology machine learning: 1. Data handling

Mitigating bias in radiology machine learning: 2. Model development

The future of gpt: A taxonomy of existing chatgpt research, current challenges, and possible future directions

A low-cost texture-based pipeline for predicting myocardial tissue remodeling and fibrosis using cardiac ultrasound

Identification of Novel Abiotic Stress Proteins in Triticum aestivum Through Functional Annotation of Hypothetical Proteins

Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis

His work is highly cited, demonstrating a significant impact on the field of AI and medical imaging, especially in the context of liver disease. 📖📈