Assoc. Prof. Dr Mumtaz Karatas – Healthcare 4.0 – Best Researcher Award

Assoc. Prof. Dr Mumtaz Karatas - Healthcare 4.0 - Best Researcher Award

Wright State University - United States

AUTHOR PROFILE 

SCOPUS 

ORCID 

EARLY ACADEMIC PURSUITS 🎓

Mumtaz Karatas began his academic journey with a BSc in Industrial Engineering from the Turkish Naval Academy in Istanbul, Turkey, where he laid the foundation for his passion in operations research and optimization. His drive to understand complex systems led him to pursue an MSc in Industrial and Operations Engineering at the University of Michigan, Ann Arbor. Afterward, he continued his academic pursuit by earning a Ph.D. in Industrial Engineering from Kocaeli University in Turkey. During his doctoral studies, he developed a solid understanding of operations research and optimization techniques, which would later shape his career.

PROFESSIONAL ENDEAVORS 💼

Mumtaz’s professional career spans over two decades, beginning as an officer in the Turkish Naval Forces before moving into academia. He has held several key roles, including Assistant Professor and Associate Professor at the Naval Academy’s Department of Industrial Engineering, and as Director of the Modeling & Simulation Department at the Navy Research Center in Istanbul. His current position as Associate Professor at Wright State University in Dayton, OH, USA, reflects his growing influence in the field. His role in multiple universities worldwide, including teaching at Sabanci University, Piri Reis University, and others, highlights his versatility and dedication to advancing knowledge.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Mumtaz’s research is centered around operations research, optimization, and machine learning, with a particular focus on integer programming, multi-objective optimization, robust optimization, and heuristic algorithms. He is also a leading figure in integrating machine learning techniques with optimization methods. His work in predictive modeling, decision support Healthcare 4.0 systems, and big data analytics has profound implications across various sectors, including supply chain logistics, transportation planning, and energy storage. His contributions also extend to emergency and disaster response optimization, where he has made significant strides in real-time decision-making models.

ACCOLADES AND RECOGNITION 🏆

Mumtaz’s expertise in operations research has earned him widespread recognition, including being featured in the Top 2% Researchers List. His work has been acknowledged through various Healthcare 4.0 awards and prestigious fellowships, including his time as a PhD fellow at the US Naval Postgraduate School, where he collaborated on critical operations research projects. His contributions to academia and research have been recognized by multiple institutions, which has made him a respected figure in the industrial engineering community.

IMPACT AND INFLUENCE 🌍

Mumtaz’s impact is not confined to the classroom. His research directly influences operations research, logistics, transportation, and supply chain optimization practices globally. As a Healthcare 4.0 consultant for military and industrial organizations, his work on multi-objective optimization and routing problems has helped shape real-world solutions. His academic leadership, as Director of various divisions at the Naval Academy and currently at Wright State University, continues to shape future generations of engineers. Mumtaz’s work has had a lasting influence on optimizing large-scale systems, helping companies and governments improve their decision-making processes in crisis situations.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Mumtaz Karatas’s career is a testament to the enduring relevance of operations research in solving modern-day challenges. His future contributions promise to extend his groundbreaking work in data-driven optimization and multi-objective decision-making. As the Program Director for the Industrial Engineering Division at Wright State University, he is poised to continue influencing the next wave of researchers and practitioners. His legacy will undoubtedly include advancing optimization techniques in global logistics, supply chains, and disaster response, leaving a lasting mark on both academia and industry.

NOTABLE PUBLICATIONS 

  • Title: Location and routing of armed Unmanned Aerial Vehicles and carrier platforms against mobile targets
    Authors: Ertan Yakıcı, Mumtaz Karatas, Levent Eriskin, Engin Cicek
    Journal: Computers & Operations Research, 2024-09
  • Title: A robust multi-objective model for healthcare resource management and location planning during pandemics
    Authors: Levent Eriskin, Mumtaz Karatas, Yu-Jun Zheng
    Journal: Annals of Operations Research, 2024-04
  • Title: A collaborative decision support framework for sustainable cargo composition in container shipping services
    Authors: Mevlut Savas Bilican, Çağatay Iris, Mumtaz Karatas
    Journal: Annals of Operations Research, 2024-02-03
  • Title: Optimization of Air Defense System Deployment Against Reconnaissance Drone Swarms
    Authors: Li, N.; Su, Z.; Ling, H.; Karatas, M.; Zheng, Y.
    Journal: Complex System Modeling and Simulation, 2023
  • Title: Data analytics during pandemics: a transportation and location planning perspective
    Authors: Elif Bozkaya, Levent Eriskin, Mumtaz Karatas
    Journal: Annals of Operations Research, 2023-09

Dr. Amina Benabid – Medical image analysis – Best Researcher Award

Dr. Amina Benabid - Medical image analysis - Best Researcher Award

Zhejiang Normal University - China

Professional Profile

SCOPUS

Early Academic Pursuits

Amina Benabid embarked on her academic journey with a Bachelor's degree in Mathematics from Université Frères Mentouri - Constantine 1, Algeria, which she completed in July 2016. She continued her education with a Master's degree in Mathematics from the same university, focusing on Statistical Tests, and graduated in July 2018. Her academic pursuits culminated in a Doctor of Natural Science in Mathematics from Zhejiang Normal University, China, in June 2022. Her doctoral thesis, supervised by Prof. Dao-Hong Xiang, explored the Convergence Theory of Large Margin Learning.

Professional Endeavors

Dr. Amina Benabid has gained diverse professional experience in both research and academic roles. She served as a Research Assistant at the School of Data Science, City University of Hong Kong, under the supervision of Prof. Ding-Xuan Zhou in July 2019. Subsequently, she held a Medical image analysis Postdoctoral fellowship position at Zhejiang Normal University's College of Mathematical Medicine from August 2022 to August 2024, working under the guidance of Prof. Yuan Jing.

Contributions and Research Focus

Dr. Benabid's research interests are focused on Statistical Learning Theory, Medical Image Analysis, Deep Learning, and Semantic Segmentation. She has made significant contributions to these fields through several publications and ongoing research projects. Her work includes papers Medical image analysis such as "Comparison theorems on large-margin learning" and "CFNet: Cross-scale Fusion Network for Brain Tumor Segmentation on 3D MRI Scans." Her research emphasizes integrating contextual information for enhanced brain tumor classification and developing real-time semantic segmentation models.

Accolades and Recognition

Throughout her career, Dr. Benabid has been recognized for her academic achievements and contributions. She received the Outstanding Award for academic innovation in 2021 and was honored as an Excellent Student in 2022. Her work has been acknowledged at various international conferences, including the 4th International Symposium on Artificial Intelligence for Medical Sciences and the 6th International Symposium on Medical image analysis Image Computing and Digital Medicine.

Impact and Influence

Dr. Amina Benabid's research has had a profound impact on advancing the understanding and application of deep learning techniques in medical image analysis, particularly in the context of brain tumor segmentation. Her contributions to the development of real-time semantic segmentation models using innovative approaches like CFNet and P2AT have set benchmarks in the field.

Legacy and Future Contributions

Looking ahead, Dr. Benabid aims to continue her research endeavors, focusing on further advancements in medical image analysis and deep learning. Her commitment to leveraging artificial intelligence for improving healthcare outcomes underscores her dedication to making significant contributions to the field. Through ongoing research and mentorship, she seeks to inspire future generations of researchers and contribute to transformative innovations in medical imaging technologies.

NOTABLE PUBLICATIONS