Haike Lei | Health Statistics | Best Researcher Award

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Prof. Haike Lei | Health Statistics | Best Researcher Award

Offices director, Chongqing university cancer hospital, China.

Professor Haike Lei is a distinguished academic and researcher, currently serving as Deputy Chief Physician, Director of the Big Data Center, and Master’s Program Supervisor. His expertise spans data mining, statistical modeling, and big data management, evidenced by his nearly 40 published papers and over 10 patents and software copyrights. Professor Lei has played a pivotal role in establishing a comprehensive oncology big data research platform, which aggregates extensive patient data for in-depth medical research. His leadership is further demonstrated through his involvement in more than 10 national and municipal scientific research projects and his contributions as co-editor of a statistics textbook. His innovative approach and practical experience have significantly advanced the field, showcasing his profound impact and influence in both domestic and international research communities.

Profile
Education

Professor Haike Lei holds a distinguished educational background that has significantly contributed to his expertise in statistics, data mining, and big data management. He earned his Bachelor’s degree in Statistics from a prestigious institution, where he developed a strong foundation in statistical theories and methodologies. Building on this, he pursued a Master’s degree in the same field, deepening his knowledge in advanced statistical modeling and data analysis techniques. His academic journey culminated in a Doctorate, where he specialized in big data and its applications in healthcare. During his doctoral studies, Professor Lei conducted pioneering research that laid the groundwork for his later contributions to the establishment of oncology big data platforms and innovative statistical methods. This robust educational background has equipped him with the skills and insights necessary to excel in his current roles as Deputy Chief Physician and Director of the Big Data Center.

Professional Experience

Prof. Haike Lei is a distinguished academic and leader in the field of statistics and big data management. Currently serving as the Deputy Chief Physician and Director of the Big Data Center, he has spearheaded the development of a comprehensive oncology big data research platform, integrating nearly ten million pieces of patient data for advanced medical analysis. As a Master’s Program Supervisor, Prof. Lei is also dedicated to shaping the next generation of statisticians and data scientists. Over the past five years, he has significantly impacted the field through the publication of nearly 40 academic papers in prestigious journals and the acquisition of more than 10 invention patents and software copyrights. His leadership extends to presiding over numerous national and municipal scientific research projects and co-editing a professional textbook on statistics. Prof. Lei’s career exemplifies exceptional academic achievement, innovation, and a commitment to advancing research in data science and statistics.

Research Interest

Professor Haike Lei’s research interests lie at the intersection of data science and healthcare, with a particular focus on big data analytics, statistical modeling, and data mining. His work is centered on leveraging advanced statistical techniques to extract meaningful insights from large datasets, particularly in the context of oncology and medical research. Professor Lei is renowned for his innovative approach to managing and analyzing extensive patient data, having spearheaded the development of a comprehensive big data research platform for oncology. His research aims to improve diagnostic accuracy, treatment efficacy, and patient outcomes through sophisticated data-driven methods. Additionally, Professor Lei is deeply involved in exploring the latest technological advancements in data science, continuously integrating new methodologies to enhance the quality and impact of his research. His contributions significantly advance both theoretical and applied aspects of statistical science and big data management in the medical field.

Research Skills

Prof. Haike Lei demonstrates exceptional research skills in the domains of data mining, statistical modeling, and big data management. His expertise is reflected in his ability to innovate and apply cutting-edge statistical techniques to real-world problems. Prof. Lei has successfully led the development of a comprehensive oncology big data research platform, effectively managing and analyzing extensive patient data to drive forward medical research. His proficiency in statistical modeling and data analysis is further evidenced by his prolific publication record, with nearly 40 papers in esteemed journals. Additionally, his leadership in national and municipal scientific research projects highlights his capacity to coordinate complex studies and contribute to significant advancements in the field. Prof. Lei’s practical experience is complemented by his achievements in securing over 10 patents and software copyrights, showcasing his ability to translate theoretical research into tangible technological innovations.

Awards and Recognition

Yibo Wang possesses a robust set of research skills, particularly in the field of electrical engineering and energy systems. His expertise in stability analysis of distributed generation in cyber-energy systems is evidenced by his contributions to high-impact publications. Yibo is proficient in advanced analytical techniques, such as the Guardian Map Method, which he has applied to optimize parameter selection in complex energy systems. His ability to collaborate effectively with leading researchers and contribute to significant studies on virtual energy storage and multi-inverter systems demonstrates his strong teamwork and communication skills. Additionally, Yibo’s research is grounded in a deep understanding of both theoretical principles and practical applications, allowing him to develop innovative solutions for contemporary challenges in energy infrastructure. His technical proficiency, coupled with a commitment to advancing knowledge in his field, makes him a valuable asset in any research setting.

Conclusion

Yibo Wang is a promising candidate for the Best Researcher Award, particularly in the context of early-career researchers. His contributions to the field of electrical engineering, particularly in stability analysis and cyber-energy systems, are commendable. However, to strengthen his case for such an award, focusing on broadening his research impact, pursuing further professional development, and demonstrating independent research leadership would be beneficial. Overall, he is a strong contender with significant potential for future recognition.

Publications Top Notes

  1. Development and validation of a nomogram model for predicting venous thromboembolism risk in lung cancer patients treated with immune checkpoint inhibitors: A cohort study in China
    • Authors: Liang, G., Hu, Z., Xu, Q., Zhang, W., Lei, H.
    • Year: 2024
  2. The development of a prediction model based on random survival forest for the prognosis of non-Hodgkin lymphoma: A prospective cohort study in China
    • Authors: Li, X., Yang, Z., Li, J., Liu, Y., Lei, H.
    • Year: 2024
  3. A nomogram to predict the risk of venous thromboembolism in patients with colon cancer in China
    • Authors: Yang, Y., Zhan, J., Li, X., Lei, H., Chen, X.
    • Year: 2024
    • Citations: 1
  4. Development and validation of a multi-parameter nomogram for venous thromboembolism in gastric cancer patients: a retrospective analysis
    • Authors: Zhou, H., Lei, H., Zhao, H., Luo, L., Li, F.
    • Year: 2024
  5. Treatment-Related Lymphopenia is Possibly a Marker of Good Prognosis in Nasopharyngeal Carcinoma: a Propensity-Score Matching Analysis
    • Authors: Weng, K.-G., Lei, H.-K., Shen, D.-S., Wang, Y., Zhu, X.-D.
    • Year: 2024
  6. Antibody responses to SARS-CoV-2 Omicron infection in patients with hematological malignancies: A multicenter, prospective cohort study
    • Authors: Li, J., Liu, Y., Wei, X., Wu, Y., Liu, Y.
    • Year: 2023
    • Citations: 1
  7. Comparison of survival outcomes between clinical trial participants and non-participants of patients with advanced non-small cell lung cancer: A retrospective cohort study
    • Authors: Jiang, Q., Yue, X., Lei, H., Li, Y., Chen, X.
    • Year: 2023
  8. Development and validation of nomogram prognostic model for predicting OS in patients with diffuse large B-cell lymphoma: a cohort study in China
    • Authors: Li, X., Xu, Q., Gao, C., Wang, Y., Lei, H.
    • Year: 2023
    • Citations: 1
  9. Development and validation of prediction model for overall survival in patients with lymphoma: a prospective cohort study in China
    • Authors: Li, X., Chen, Y., Sun, A., Liu, Y., Lei, H.
    • Year: 2023
    • Citations: 2
  10. Nomogram prediction for the risk of venous thromboembolism in patients with lung cancer
    • Authors: Lei, H., Tao, D., Zhang, N., Xie, Y., Wang, Y.
    • Year: 2023
    • Citations: 6