Zhiwei Zhong | Medicine and Health Sciences | Best Researcher Award

Published on by Forensic Scientist

Dr. Zhiwei Zhong | Medicine and Health Sciences | Best Researcher Award

The Second Affiliated Hospital of Nanchang University | China

Dr. Zhiwei Zhong’s research focuses on molecular oncology, nanomedicine, and biomarker discovery in complex diseases such as pancreatic cancer, hepatocellular carcinoma, thyroid eye disease, and venous thromboembolism. His studies integrate bioinformatics, molecular biology, and nanotechnology to uncover therapeutic targets and diagnostic biomarkers. Zhong has contributed to several high-impact publications in PLOS One, Cancer Cell International, Oncology Reports, Digestive Diseases and Sciences, and SN Applied Sciences. His notable works include identifying key extracellular proteins (EGFR, CD44, and CXCL8) as potential biomarkers in thyroid eye disease, elucidating the regulatory role of lncRNA FTX in suppressing NAFLD progression to hepatocellular carcinoma via Kupffer cell polarization, and exploring nanoparticle-based drug delivery systems for targeted thrombolysis and cancer therapy. He has also investigated tumor suppressor mechanisms involving KLF9 and CHD1L in pancreatic cancer, providing insights into tumor proliferation, invasion, and survival pathways. His research contributions advance the understanding of molecular pathogenesis, precision diagnostics, and targeted nanotherapeutic strategies in human diseases.

Profile: ORCID

Featured Publications

  1. He, S., Nie, H., Yin, X., & Zhong, Z. (2025, April). Identification of key extracellular proteins as the potential biomarkers in thyroid eye disease. PLOS ONE, 20(4), e0322415. https://doi.org/10.1371/journal.pone.0322415

Naila Camila da Rocha | Medicine and Health Sciences | Best Researcher Award

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Dr. Naila Camila da Rocha | Medicine and Health Sciences | Best Researcher Award

University of Wisconsin-Madison | United States

Dr. Naila Camila da Rocha is a distinguished researcher specializing in biostatistics, artificial intelligence in healthcare, and predictive analytics, with a strong focus on advancing precision medicine and healthcare delivery. She is completing her Ph.D. in Biometrics at São Paulo State University (UNESP) in collaboration with the University of Wisconsin–Madison, following a Master’s in Biometrics, a Professional Master’s in Applied Statistics, and a Bachelor’s in Administration. With over 14 years of experience in strategic planning, business intelligence, and applied statistics, she has held leadership roles including Head of Growth Strategy and Revenue at iFood, Data Science Manager at BRF, and currently works as a Data Scientist at Statbit, while also contributing as a volunteer researcher at the Clinics Hospital of Botucatu (LabData). Her research applies machine learning, natural language processing, and advanced statistical modeling to nephrology, transplantation, and chronic disease management, with impactful results such as predictive models for graft rejection, delayed graft function, and inequities in hemodialysis access. She has published more than 20 peer-reviewed papers in high-impact journals and received multiple prestigious awards, including the Massola Award (2025), AACD Summit Award (2025), Magaldi Award (2023), and Nestor Schor Award (2023). By successfully bridging data science with clinical applications, she has established herself as an influential voice in developing innovative tools for early diagnosis, risk stratification, and health system optimization, demonstrating excellence as a researcher whose work is shaping both academic knowledge and practical healthcare solutions.

Profile: Google Scholar | ORCID

Featured Publications

  • Beltramino, L., Bedacarratx, V., Roldán, P., González, N. A. M., … (2020). Aprendizajes y prácticas educativas en las actuales condiciones de época: COVID-19. Universidad Nacional de Córdoba, Facultad de Filosofía y Humanidades. Cited by: 33

  • Da Rocha, N. C., Barbosa, A. M. P., Schnr, Y. O., Machado-Rugolo, J., … (2022). Natural language processing to extract information from Portuguese-language medical records. Data, 8(1), 11. Cited by: 13

  • De Andrade, L. G. M., Barbosa, A. M. P., Da Rocha, N. C., Cardoso, M. M. de A., … (2022). Impact of the COVID-19 pandemic on solid organ transplant and rejection episodes in Brazil’s Unified Healthcare System. Journal of Clinical Medicine, 11(21), 6581. Cited by: 11

  • Ordones, F. V., Kawano, P. R., Vermeulen, L., Hooshyari, A., Scholtz, D., … (2025). A novel machine learning-based predictive model of clinically significant prostate cancer and online risk calculator. Urology, 196, 20–26. Cited by: 5

  • Addad, V. V., Palma, L. M. P., Vaisbich, M. H., Barbosa, A. M. P., … (2023). A comprehensive model for assessing and classifying patients with thrombotic microangiopathy: The TMA-INSIGHT score. Thrombosis Journal, 21(1), 119. Cited by: 5

  • Santos, G. P. A., Sesso, R., Lugon, J. R., Neves, P. D. M. de M., Barbosa, A. M. P., … (2024). Geographic inequities in hemodialysis access: A call to reassess dialysis facility locations in Brazil. Journal of Nephrology, 37(9), 2601–2608. Cited by: 4

Xuanlong Chen | Medicine and Health Sciences | Best Researcher Award

Published on by Forensic Scientist

Mr. Xuanlong Chen | Medicine and Health Sciences | Best Researcher Award

Fudan University | China

Mr. Xuanlong Chen is a promising researcher in forensic pathology with a strong academic foundation and a growing record of impactful contributions. Known for his dedication and meticulous approach to scientific inquiry, he has already demonstrated significant potential in advancing forensic research. His work combines cutting-edge molecular techniques with practical forensic applications, reflecting both innovation and a commitment to improving diagnostic accuracy in complex medico-legal cases. He has been recognized for academic excellence through multiple scholarships and awards, positioning him as a notable candidate for the Best Researcher Award.

Professional Profile

Scopus

Education

Mr. Xuanlong Chen completed his Bachelor’s degree at Nanjing Medical University, China, where he developed a strong background in medical sciences and research methodology. Currently, he is pursuing a Master’s degree at Fudan University, focusing on forensic pathology and molecular forensic research. During his academic journey, he has received several university-level scholarships, been honored as an Outstanding Student, and awarded the prestigious National Scholarship, reflecting his consistent dedication to academic and research excellence.

Experience

As a graduate researcher, Mr. Xuanlong Chen has undertaken advanced projects that combine single-nucleus RNA sequencing and machine learning to identify potential biomarkers in sudden unexplained deaths among psychiatric patients. He has contributed to developing predictive identification models for sudden death cases, addressing critical challenges in forensic pathology. In addition, he has conducted comprehensive reviews on rare toxicological phenomena, such as bongkrekic acid poisoning, demonstrating both breadth and depth in his research. Although early in his career, his proactive approach and innovative methods reflect significant research maturity.

Research Interests

His primary research focus is forensic pathology, particularly investigating molecular and cellular mechanisms underlying sudden unexplained deaths. He also explores toxicological studies and the identification of biomarkers for psychiatric-related mortalities. By integrating molecular biology, bioinformatics, and forensic analysis, he aims to develop practical diagnostic tools and predictive models that enhance forensic accuracy and provide valuable insights for medico-legal investigations.

Awards

Throughout his academic career, Mr. Xuanlong Chen has been recognized for excellence through multiple scholarships and university awards, including the highly competitive National Scholarship and several “Outstanding Student” honors. These accolades reflect his consistent academic performance, innovative research approach, and commitment to advancing knowledge in forensic pathology.

Publications

Mr. Xuanlong Chen has published several peer-reviewed articles in internationally recognized journals, reflecting his research contribution and growing scientific impact. His work includes studies on single-nucleus RNA sequencing and machine learning in forensic pathology and comprehensive reviews of toxicological phenomena. Selected publications include:

  • Title: Single-nucleus RNA sequencing and machine learning identify CACNA1A as a myocyte-specific biomarker for sudden unexplained death in schizophrenia
    Journal: Forensic Science International

  • Title: A comprehensive review on bongkrekic acid poisoning
    Journal: Journal of Forensic Medicine

Conclusion

Mr. Xuanlong Chen is a dedicated and innovative researcher whose academic accomplishments, publications, and contributions to forensic pathology exemplify excellence. His work in biomarker identification and toxicological studies demonstrates both scientific creativity and practical relevance, making him a highly deserving candidate for the Best Researcher Award. His dedication, forward-thinking approach, and growing influence in forensic research underscore his potential to make significant contributions to the scientific community.