Noemi Cardenas Rodriguez | Biochemistry and Molecular Biology | Women Researcher Award

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Dr. Noemi Cardenas Rodriguez | Biochemistry and Molecular Biology | Women Researcher Award

 Reserarcher | Instituto Nacional de Pediatría | Mexico

Dr. Noemí Cárdenas Rodríguez is a distinguished researcher in medical sciences with a strong specialization in neuroscience, molecular biology, and biochemical research. Her work has significantly advanced the understanding of neuronal toxicity, oxidative stress, and neuroprotective mechanisms, with applications in both experimental and clinical contexts. She has an impressive record of mentorship, guiding students across undergraduate, master’s, and doctoral programs, and actively participates in national and international scientific evaluation committees. Dr. Cárdenas Rodríguez has contributed extensively to high-impact journals, reflecting her commitment to rigorous, innovative research. Her multidisciplinary expertise bridges basic science with potential clinical applications, making her a prominent figure in translational neuroscience. Her research is recognized globally for its relevance and quality, contributing to scientific knowledge and healthcare advancements. According to Scopus, her research impact is measurable with 2,155 citations, 80 documents, and an h-index of 22.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

1. Integrated approach for biochemical and functional characterization of six clinical variants of glucose-6-phosphate dehydrogenase. International Journal of Molecular Sciences, 2025.

2. Post-COVID condition and neuroinflammation: Possible management with antioxidants. International Journal of Molecular Sciences, 2025.

3. Association of vitamin D supplementation with glutathione peroxidase (GPx) activity, interleukine-6 (IL-6) levels, and anxiety and depression scores in patients with post-COVID-19 condition. International Journal of Molecular Sciences, 2025.

4. Nitazoxanide analogs: Synthesis, in vitro giardicidal activity, and effects on Giardia lamblia metabolic gene expression. International Journal of Molecular Sciences, 2025.

5. Effects of digital neurohabilitation on attention and memory in patients with a diagnosis of pediatric obesity: Case series. Brain Sciences, 2025.

Qian Qiao | Materials Science | Best Researcher Award 

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Dr. Qian Qiao | Materials Science | Best Researcher Award 

R&D Manager | IDQ Science and Technology (Hengqin Guangdong) Co | China

Dr. Qian Qiao is a dedicated researcher specializing in electromechanical and mechanical engineering, with extensive experience in materials science, surface technology, and smart manufacturing. She has authored numerous papers in reputable international journals and holds multiple patents that highlight her innovative approach to engineering challenges. Her academic achievements, including several prestigious scholarships and awards, reflect consistent excellence and commitment to research advancement. Dr. Qian has actively participated in global academic conferences, contributing to the dissemination and exchange of cutting-edge knowledge. Her current research focuses on the structural and performance analysis of advanced manufacturing components, integrating intelligent systems and automation to enhance efficiency and reliability. With a strong foundation in both theoretical and applied research, she demonstrates outstanding potential for leading future developments in material innovation, corrosion science, and intelligent engineering solutions, contributing meaningfully to technological progress and industrial transformation.

Profiles: Google Scholar | Scopus | ORCID 

Featured Publications

1. Qiao, Q., Qian, H., Li, Z., Guo, D., Kwok, C. T., Jiang, S., Zhang, D., & Tam, L. M. (2025). Microstructure evolution and mechanical performance of AA6061-7075 heterogeneous composite fabricated via additive friction stir deposition. Alloys, 4(4), 21.

2. Lam, W. I., Leong, K. K., Tam, C. W., Qiao, Q., Lin, Y., Yang, G., Guo, D., & Kwok, C. T. (2025). A high performance mechanically alloyed stainless steel composite coating via friction surfacing. Surface and Coatings Technology, 132685.

3. Qiao, Q., Gong, X., Guo, D., Qian, H., Li, Z., Zhang, D., Kwok, C., & Tam, L. M. (2025). Influence of tool head geometry on in situ monitoring of temperature, force, and torque during additive friction deposition of aluminum alloy 2219. Materials Science in Additive Manufacturing, 4(4), 025280060.

4. Qiao, Q., Tam, C. W., Lam, W. I., Wang, K., Guo, D., Kwok, C. T., Lin, Y., Yang, G., & Zhang, D. (2025). Hybrid heat-source solid-state additive manufacturing: A method to fabricate high performance AA6061 deposition. Journal of Materials Science & Technology, 228, 107–124.

5. Wu, Z., Qian, H., Chang, W., Zhu, Z., Lin, Y., Qiao, Q., Guo, D., Zhang, D., & Kwok, C. T. (2025). Enhanced corrosion resistance by Pseudomonas aeruginosa on 2219 aluminum alloy manufactured through additive friction stir deposition. Acta Metallurgica Sinica (English Letters), 1–18.

Keira MacDonald | Computer Science | Women Researcher Award

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Ms. Keira MacDonald | Computer Science | Women Researcher Award

Researcher at University of Western Ontario, Canada

Keira MacDonald is an accomplished early-career researcher and entrepreneur currently pursuing an Honours Bachelor of Science in Computer Science & Engineering at the University of Western Ontario, where she has earned multiple academic distinctions including the Dean’s List and the Governor General’s Medal. She is actively engaged in cutting-edge research as a Visiting Student Researcher at RWTH Aachen University, focusing on advanced simulations and metallurgy related to laser welding. Keira has also published work on optimizing fusion reactors using quantum computing, highlighting her interdisciplinary expertise. Beyond academia, she co-founded The Dashello Company, a startup leveraging AI to improve financial management, demonstrating strong leadership and innovation skills. Additionally, her role as UI/UX Executive for Canada’s largest student-led hackathon showcases her commitment to community engagement and advancing women in technology. With a robust combination of research, entrepreneurship, and leadership, Keira exemplifies the qualities of a rising star in STEM.

Professional Profile 

Google Scholar

Education

Keira MacDonald is pursuing an Honours Bachelor of Science in Computer Science & Engineering at the University of Western Ontario, with an expected graduation date of May 2027. Throughout her academic career, she has demonstrated exceptional academic performance, consistently earning a place on the Dean’s List. She has also been awarded prestigious scholarships, including the Principal’s Regis Scholarship and the Mathematics Excellence Scholarship, recognizing both her scholastic aptitude and dedication to STEM fields. Prior to university, Keira graduated from Eastwood Collegiate Institute with an OSSD Honours Endorsement in Science and Arts, earning the Governor General’s Medal for outstanding academic achievement. She was also nominated for the Schulich Leader Scholarship, a competitive award for top STEM students, and received the National Plaque of Music Excellence, showcasing her well-rounded talents. Keira’s education reflects a strong foundation in both science and technology, positioning her well for future research and innovation in engineering and computing disciplines.

Professional Experience

Keira MacDonald has gained diverse professional experience that blends research, entrepreneurship, and leadership. Currently, she serves as a Visiting Student Researcher at RWTH Aachen University in Germany, where she focuses on laser welding simulations and metallurgy, contributing to high-level engineering research. In addition to her research role, Keira is the UI/UX Executive for Ignition Hacks, Canada’s largest student-led hackathon, where she develops graphics and collaborates with major sponsors such as Microsoft and Best Buy. Her ability to secure significant funding demonstrates strong organizational skills. Keira is also the Co-Founder and Full-Stack Developer at The Dashello Company, a startup focused on financial management optimization through AI-powered solutions. Her role involves conducting user interviews, leading development, and implementing multimodal AI APIs. This blend of technical, entrepreneurial, and leadership roles highlights her ability to translate research into practical applications and thrive in multidisciplinary environments.

Research Interest

Keira MacDonald’s research interests lie at the intersection of computational science, engineering, and advanced technology. Her work as a Visiting Student Researcher at RWTH Aachen University centers on the simulation of laser welding processes, specifically investigating spatial and temporal energy input and heat transfer mechanisms in metallurgy. This applied research demonstrates her focus on practical engineering challenges involving materials science and manufacturing technology. Additionally, Keira explores cutting-edge topics like fusion reactor optimization through quantum computing, indicating a passion for interdisciplinary research that combines quantum algorithms with energy systems. Her research aims to leverage computational methods to solve complex physical problems, driving innovation in both theoretical and applied sciences. Keira’s interests reflect a commitment to advancing technologies that have real-world industrial and scientific impact, particularly in areas related to materials engineering, quantum computing, and AI-driven solutions.

Award and Honor

Keira MacDonald’s academic and extracurricular achievements have been recognized through multiple awards and honors. She is a consistent member of the Dean’s List at the University of Western Ontario, reflecting her sustained academic excellence. She has received the Principal’s Regis Scholarship and the Mathematics Excellence Scholarship, which acknowledge both her academic merit and aptitude in quantitative disciplines. During high school at Eastwood Collegiate Institute, Keira was awarded the prestigious Governor General’s Medal, reserved for top-ranking students nationwide. She was also nominated for the Schulich Leader Scholarship, a highly competitive STEM award for promising Canadian students. Beyond academics, she earned the National Plaque of Music Excellence, illustrating her versatile talents. These awards collectively highlight Keira’s strong intellectual capabilities, leadership potential, and well-rounded profile, positioning her as an outstanding candidate for research and innovation awards focused on women in STEM.

Conclusion

Keira MacDonald is a highly accomplished young researcher and leader poised to make significant contributions in STEM. Her academic record, including scholarships and prestigious awards, reflects a dedication to excellence and strong foundational knowledge in computer science and engineering. Her research on laser welding simulations and fusion reactor optimization demonstrates both technical depth and innovative interdisciplinary thinking. As a co-founder of a startup and UI/UX executive at a major hackathon, Keira shows exceptional leadership, entrepreneurial spirit, and community engagement. While she continues to build her portfolio of peer-reviewed publications and mentorship roles, her blend of research expertise, real-world impact, and academic achievements makes her a compelling candidate for women-focused research awards. Keira exemplifies the next generation of women innovators who combine rigorous science with practical application and leadership, promising a bright future in both academia and industry.

Publications Top Notes

Title: Advancing Fusion: Optimizing Fusion Reactors with Quantum Computing
Author: K.S. MacDonald
Year: 2025

Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

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Assist Prof Dr. Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Biomedical, University of Texas at San Antonio, United States

Profile

Google Scholar

Short Bio

Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio, specializing in artificial intelligence models for disease phenotype predictions, biomarker identification, and explainable mechanisms. His innovative research integrates various AI techniques to enhance our understanding of disease progression, particularly in oncology.

Education

Dr. Flores holds a Bachelor’s degree in Electronics Engineering from the Metropolitan Autonomous University, a Master’s in Applied Mathematics, and a PhD in Electrical Engineering (Computational Biology) from the University of Texas at San Antonio. He completed his postdoctoral fellowship at the National Center for Biotechnology Information (NCBI), NIH.

Experience

Since 2020, Dr. Flores has served as an Assistant Professor with joint appointments in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME) at UTSA. His prior roles include NIH Postdoctoral Fellow at NCBI and Research Associate at the Greehey Children’s Cancer Research Institute, showcasing his extensive experience in computational biology and bioinformatics.

Research Interests

Dr. Flores’s research focuses on developing AI tools for disease gene dependence prediction, utilizing spatially resolved transcriptomics, single-cell RNA sequencing, and Electronic Health Records (EHRs) to analyze tumor microenvironments. His work aims to bridge gaps in understanding disease mechanisms and improve patient outcomes through precision medicine.

Awards

Dr. Flores has received numerous awards for his research, including funding from the NIH for projects on neural circuits inhibiting pain, and recognition from the AIM-AHEAD Fellowship program, supporting his efforts to address health disparities in minority populations.

Publications Top Notes

Dr. Flores has authored several impactful publications, including:

New tools for spatial biology transcriptomics & proteomics in immuno-oncology, Immuno-Oncology Insights, 2023.

Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis, Brief in Bioinformatics, 2022.

Transformer for Gene Expression Modeling (T-GEM): An Interpretable Deep Learning Model for Gene Expression-Based Phenotype Predictions, Cancers, 2022.