Maame Yaa Yiadom | Data collection | Women Researcher Award

Dr. Maame Yaa Yiadom | Data collection | Women Researcher Award

Stanford University, United States

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Early Academic Pursuits ๐ŸŽ“

Dr. Maame Yaa Yiadomโ€™s academic journey began at Princeton University, where she earned her undergraduate degree in Public Health Policy and International Affairs, with a certificate in African Studies. This laid a strong foundation for her later research and clinical work in global health. Her commitment to expanding her expertise led her to advanced studies at Johns Hopkins School of Public Health and Harvard School of Public Health, where she obtained her Master of Public Health degree and further honed her focus on health systems and population health. Dr. Yiadomโ€™s academic progression continued with a Doctor of Medicine degree from Robert Wood Johnson Medical School, solidifying her clinical expertise in emergency medicine.

Professional Endeavors & Contributions ๐Ÿ”ฌ

Dr. Yiadomโ€™s career spans over two decades and has seen her contribute in both administrative and clinical roles across multiple health systems. As a physician-scientist, she has focused on translating research into clinical practice through program development, health system optimization, and change management. Her research efforts are centered on improving clinical care delivery, with a particular emphasis on emergency medicine and health equity. She has led pivotal projects involving digital health integration, clinical practice epidemiology, and healthcare innovation, with significant contributions to artificial intelligence and algorithmic equity in health systems.

Throughout her career, she has applied a mix of analytical strategies and leadership to tackle issues like healthcare efficiency, financial sustainability, and clinical effectiveness, particularly in emergency departments across the U.S. and internationally. Her leadership roles in organizations like the Emergency Department Benchmarking Alliance (EDBA) and the Health Equity Action Leadership (HEAL) Network highlight her commitment to advancing healthcare innovation and equity. Additionally, her involvement in research grants and mentorship has further fueled the development of the next generation of health leaders.

Research Focus & Impact ๐Ÿ“Š

Dr. Yiadomโ€™s research efforts are particularly focused on healthcare delivery operations, clinical workflows, and health equity, with ongoing projects spanning North America, Europe, and Africa. She leads a highly impactful lab, the Emergency Care Health Service Research Data Coordinating Center (HSR-DCC), which aims to improve clinical practice and workflow integration through cutting-edge digital health technologies. Through collaborations with multiple international institutions, Dr. Yiadom has made substantial contributions to improving emergency care systems and advancing equitable healthcare access across diverse populations. Notably, her projects tackle key issues such as algorithmic fairness and clinical decision support using artificial intelligence, particularly in heart attack screening.

Academic Citations & Recognition ๐Ÿ“š

As a physician-scientist, Dr. Yiadom has gained recognition in the field for her contributions to research, evidenced by her leadership roles in numerous initiatives and her consistent engagement with funding bodies. Her work has earned citations in major academic journals, cementing her as a key figure in emergency medicine and health system research. Through her collaborations, both national and international, Dr. Yiadom has been integral in publishing impactful work on topics such as clinical data analytics, health policy reform, and healthcare access for underserved populations.

Technical Skills & Teaching Experience ๐Ÿ’ป

Dr. Yiadomโ€™s technical skills are vast and varied, including expertise in clinical informatics, data analytics, and the integration of digital health tools into clinical environments. Her work in developing data-driven solutions to healthcare challenges has placed her at the forefront of innovative healthcare technologies. In her teaching roles, she has mentored numerous advanced trainees and faculty, providing guidance in research, clinical practice, and leadership development. Her educational impact extends beyond the classroom, as she also actively engages in mentorship programs, ensuring that the next generation of physicians and researchers is equipped to handle the evolving landscape of healthcare.

Legacy & Future Contributions ๐Ÿ”ฎ

Dr. Yiadomโ€™s legacy is rooted in her unwavering commitment to improving healthcare delivery, with a particular focus on emergency care, health equity, and digital health innovation. As she continues to advance research in algorithmic equity and healthcare policy, her work has the potential to significantly influence how emergency departments and other healthcare settings operate globally. Looking forward, Dr. Yiadom is poised to leave an indelible mark on health system transformation, especially through her leadership roles at Stanford University and beyond. Her involvement in cutting-edge initiatives such as the Center for Digital Health and her guidance in the fogarty innovation program ensures that her contributions will continue to shape the future of healthcare.

Teaching & Mentorship ๐ŸŒฑ

Dr. Yiadom has demonstrated a strong commitment to mentorship and teaching, shaping future leaders in healthcare. She has mentored faculty members, trainees, and researchers, contributing significantly to academic and clinical environments. Her leadership in various academic programs has helped guide young professionals in their careers, particularly in emergency medicine and healthcare research. The knowledge and skills she imparts will undoubtedly have a long-lasting influence on the medical community.

 

 Top Noted Publications ๐Ÿ“–

Influence of timeโ€toโ€diagnosis on timeโ€toโ€percutaneous coronary intervention for emergency department STโ€elevation myocardial infarction patients: Timeโ€toโ€electrocardiogram matters

Authors: Maame Yaa A.B. Yiadom, Wu Gong, Brian W. Patterson, Christopher W. Baugh, Angela M. Mills, Nicholas Gavin, Seth R. Podolsky, Bryn E. Mumma, Mary Tanski, Gilberto Salazar et al.

Journal: JACEP Open

Year: 2024

Stanford Emergency Medicine Partnership Program: a novel approach to streamlining the evaluation and implementation of emerging health technologies through academic-industry partnerships

Authors: John Dayton, Maame Yaa A. B. Yiadom, Sam Shen, Matthew C. Strehlow, Christian Rose, Gabrielle Bunney, Ryan Ribeira

Journal: BMJ Innovations

Year: 2024

2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy-relevant, patient-centered research agenda

Authors: Matthew Strehlow, Michael A Gisondi, Holly Caretta-Weyer, Felix Ankel, Alexandria Brackett, Pawan Brar, Teresa M Chan, Adrene Garabedian, Bridget Gunn, Eric Isaacs et al.

Journal: Academic Emergency Medicine: Official Journal of the Society for Academic Emergency Medicine

Year: 2024

 Shorter Door-to-ECG Time Is Associated with Improved Mortality in STEMI Patients

Authors: Maame Yaa A. B. Yiadom, Wu Gong, Sean M. Bloos, Gabrielle Bunney, Rana Kabeer, Melissa A. Pasao, Fatima Rodriguez, Christopher W. Baugh, Angela M. Mills, Nicholas Gavin et al.

Journal: Journal of Clinical Medicine

Year: 2024

 Changes in low-acuity patient volume in an emergency department after launching a walk-in clinic

Authors: Divya Kurian, Vandana Sundaram, Anna Graber Naidich, Shreya A Shah, Daniel Ramberger, Saud Khan, Shashank Ravi, Sunny Patel, Ryan Ribeira, Ian Brown et al.

Journal: Journal of the American College of Emergency Physicians Open

Year: 2023

yunhao zhao | Data Analysis Innovation | Best Researcher Award

Assoc Prof Dr. yunhao zhao | Data Analysis Innovation | Best Researcher Award

Qingdao Huanghai University, China

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๐Ÿง‘โ€๐ŸŽ“ Early Academic Pursuits

Yunhao Zhao was Shandong, P.R. China. His academic journey began with a strong foundation in International Economics and Social Security studies, setting the stage for his future research. After completing his undergraduate education, he became an associate professor at Qingdao Huanghai University, where he also supervises undergraduate students. His quest for further knowledge continues as he pursues a Ph.D. at The Catholic University of Korea, focusing on the evolving fields of economics and social security.

๐Ÿ‘จโ€๐Ÿซ Professional Endeavors

Dr. Zhaoโ€™s academic career has been marked by significant contributions in the realms of data analysis and economic research. As an All-Media Operator and Associate Professor, he actively engages in both teaching and research at Qingdao Huanghai University. His dedication to advancing knowledge in the academic sphere extends to overseeing the academic progress of undergraduate students, ensuring they are equipped with the necessary skills and insights to excel in their respective fields.

๐Ÿ“Š Contributions and Research Focus

Dr. Zhaoโ€™s primary research areas are data analysis, internet of things (IoT), and auction theory. His most notable work focuses on congestion control in IoT systems, where he applied auction theory to improve performance and efficiency. His research contributions are significant in their potential to drive forward the development of smarter and more efficient IoT networks. Furthermore, his work on energy consumption reduction demonstrates the real-world impact of his methods, achieving a remarkable 24.13% reduction in energy usage in experimental scenarios.

๐ŸŒ Impact and Influence

Dr. Zhaoโ€™s work has already made notable contributions to the global research community, evidenced by his publication in Scientific Reports (SCI) and recognition in high-impact journals. His research on IoT and auction theory has contributed to solving critical issues in technology and energy efficiency, impacting industries reliant on smart technology. His scholarly output has the potential to influence policy and innovation in areas such as network management and resource optimization.

๐Ÿ”ง Technical Skills

Dr. Zhao possesses advanced technical skills in data analysis, machine learning, and network optimization, particularly within the context of IoT systems. His expertise in auction theory and its applications in real-world scenarios is a testament to his depth of understanding and innovation in these areas. He is also adept at utilizing advanced analytical tools and methods to derive actionable insights from complex datasets.

๐Ÿ‘ฉโ€๐Ÿซ Teaching Experience

As an Associate Professor at Qingdao Huanghai University, Dr. Zhao has extensive experience in educating the next generation of scholars and professionals. His role as a supervisor for undergraduate students allows him to nurture young talent and help shape their academic journeys. His commitment to teaching is evident through his personalized mentorship approach, guiding students to succeed in both their academic and professional aspirations.

๐ŸŒŸ Legacy and Future Contributions

Looking ahead, Dr. Zhao aims to continue contributing to the field of International Economics and Social Security Studies, with a strong emphasis on data-driven solutions. His work has already proven impactful, and he intends to further refine his methodologies to solve pressing global issues such as economic inequality, social security systems, and technological advancements in IoT. His legacy will undoubtedly inspire future researchers and practitioners in these fields, and his work has the potential to pave the way for groundbreaking solutions in economic policy and technological development.

๐Ÿ† Recognition and Awards

Dr. Zhaoโ€™s academic achievements have garnered recognition within the research community. He is a strong candidate for the Best Researcher Award for his ongoing contributions to data analysis and IoT research. His ability to surpass existing methodologies, particularly in terms of energy efficiency, sets him apart as an innovator in his field. His commitment to advancing knowledge and solving real-world problems makes him a deserving nominee for such accolades.

 

๐Ÿ“– Top Noted Publications

Congestion control in internet of things (IoT) using auction theory
    • Authors: Zhenlong Li; Yunhao Zhao
    • Journal: Scientific Reports
    • Year: 2024
Enhancing Chinaโ€™s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling
    • Authors: Nasi Wang; Yunhao Zhao; Jun Li; Guanfeng Cai
    • Journal: Scientific Reports
    • Year: 2024
Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC)
    • Authors: Yunhao Zhao; Xiaoqing Shu
    • Journal: Scientific Reports
    • Year: 2023

Haixia Mao | Data Science | Best Researcher Award

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

๐Ÿ‘จโ€๐ŸŽ“Professional Profile

Scopus Profile

๐Ÿ‘ฉโ€๐Ÿซ Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

๐ŸŽ“ Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

๐Ÿ’ผ Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

๐Ÿ“š Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

๐Ÿ… Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

๐Ÿ’ป Technical Skills

Dr. Maoโ€™s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

๐Ÿ“š Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

๐Ÿ“–Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings โ€“ 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings โ€“ 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings โ€“ IEEE International Conference on Mobile Data Management
Year: 2016