Dan Uchimura | Engineering | Best Researcher Award

Mr. Dan Uchimura | Engineering | Best Researcher Award

Mr. Dan Uchimura|Kajima Corporation | Japan

Dan Uchimura is an emerging professional in nuclear power plant structural design, currently serving as a designer in the Kajima Corporation Nuclear Power Department. With a Master’s Degree in Architecture from Waseda University, he has swiftly transitioned from academia to industry, applying his expertise in structural systems, safety analysis, and computational modeling. During his graduate studies in Tokyo, he focused on enhancing the resilience and sustainability of energy facilities, developing technical skills in MATLAB, Python, and Excel to simulate structural integrity under extreme conditions. Since joining Kajima, Dan has contributed to the planning and design of nuclear power facilities while spearheading research on integrating non-destructive inspection techniques—especially infrared thermography—into plant systems to detect structural anomalies without operational interruptions. Known for his analytical thinking, precision, and interdisciplinary approach, he collaborates with engineers, material scientists, and safety analysts to deliver reliable, innovative design solutions aligned with stringent safety regulations. His research interests center on advancing inspection technologies, modeling structural behavior under thermal and seismic loads, and exploring AI-driven predictive maintenance systems to enhance safety and efficiency in nuclear infrastructure. Though early in his career, Dan has already earned recognition for his innovative contributions, including commendations for his thesis on resilient energy infrastructure and praise from senior engineers for merging theoretical concepts with practical design solutions.

Profile : ORCID

Featured Publication 

Uchimura, D. (2024). Application of infrared thermography for non-destructive structural inspection in nuclear power facilities. Journal of Structural Engineering and Technology.

Uchimura, D. (2023). Resilient architectural design framework for nuclear power plants. International Journal of Sustainable Energy Infrastructure.

Uchimura, D. (2023). Computational modeling of seismic loads in nuclear plant structures. Journal of Advanced Structural Engineering.

 

Chen Chen | Engineering | Best Researcher Award

Assist. Prof. Dr. Chen Chen | Engineering | Best Researcher Award 

Assistent professor, at Xidian University, China.

Dr. Chen Chen is an Assistant Professor at Xidian University, specializing in the intersection of photonics and biosensing. She earned her Ph.D. from Xi’an Jiaotong University, following a B.Sc. from the same institution and an M.Sc. from Uppsala University. Her multidisciplinary expertise spans pharmacy, molecular biology, and photonics, unified by her focus on developing advanced biosensing platforms. Dr. Chen’s research integrates high-Q-factor metasurfaces, dual-wavelength and polarization techniques, and lab-on-chip technologies. She’s held past appointments at Dalian Maritime University and Peihua University and completed a postdoctoral fellowship at ICN2 in Spain. With 13 SCI‑indexed publications (Q1) and one ESI highly cited article, plus over 800 citations and an H‑index of 6, she is recognized as an emerging leader in analytical photonics. Dr. Chen also holds a published patent (CN202210581990.7), serves on editorial review boards, and collaborates internationally with institutions in Europe and China.

Professional Profile

Scopus

Google Scholar 

🎓 Education

Dr. Chen’s academic foundation is built upon rigorous training across multiple prestigious institutions. She initiated her studies at Xi’an Jiaotong University, obtaining a Bachelor of Science degree with a strong emphasis on molecular biology and pharmaceutical sciences. She then pursued further specialization at Uppsala University, Sweden, where she earned her Master of Science, focusing on advanced methodologies in biosensor design. Her academic journey culminated in a Ph.D. from Xi’an Jiaotong University, where her doctoral research explored the application of photonic technologies to biological systems. Throughout her education, Dr. Chen gained valuable research experience in optical biosensing and label-free detection techniques. Her educational path demonstrates a deliberate progression from foundational life sciences to cutting-edge photonics, equipping her with the interdisciplinary expertise essential for pioneering translational research at the interface of optics and biomedicine.

💼 Experience

Dr. Chen’s academic career features a trajectory of progressive responsibility and research impact. She began with a postdoctoral fellowship at ICN2 in Spain, contributing to EU‑funded projects on hybrid plasmonic sensors. She later joined Dalian Maritime University and Peihua University as a researcher and faculty member, where she led biosensing initiatives and supervised graduate student projects. Currently at Xidian University, she holds the title of Assistant Professor, leading multiple grant‑funded projects—seven as Principal Investigator and three as co-investigator. Her roles have included teaching, mentoring, coordinating industry‑sponsored consultancy efforts, and serving as peer reviewer for top-tier journals. Dr. Chen has also actively contributed to SPIE, IEEE, and OSA conferences, fostering collaborations with international universities. Through these appointments, she has successfully translated lab‑scale photonic biosensor prototypes into potential industry applications, bridging academic innovation and real‑world deployment.

🔬 Research Interests

Dr. Chen focuses on advancing optical biosensing platforms by leveraging hybrid plasmonics and metasurface photonics. She is particularly interested in developing dual‑wavelength and dual‑polarization sensing systems to analyze conformational changes in amyloid‑β (Aβ) proteins, facilitating early detection of neurodegenerative diseases. Her broader interests include high‑Q‑factor metasurfaces and label‑free detection modalities that enable multiplexed analysis within compact lab‑on‑chip formats. To enhance analytical performance, she integrates AI‑based data interpretation algorithms for real‑time biosignal processing. Additionally, Dr. Chen explores scalable translation pathways for these systems, collaborating with industry partners to transition innovations toward commercialization. Her multidisciplinary ambitions bridge photonics, molecular diagnostics, and biomedical engineering, striving to develop rapid, sensitive, and affordable tools for disease diagnosis and environmental monitoring.

🏆 Awards

Dr. Chen has been recognized as a rising talent in analytical chemistry and photonics. She has secured national and provincial‑level research grants in China, affirming her leadership as a young scholar. Notably, she received a prestigious early‑career award from her institution for groundbreaking work in amyloid protein detection. She holds a published Chinese invention patent (CN202210581990.7) for a dual‑polarization biosensor design. In addition, she is an active reviewer for high‑impact journals such as Sensors & Actuators B, Applied Optics, and MST, underscoring her scientific credibility. Her achievements have led to invitations to SPIE, IEEE, and OSA events. She is also a member of the China Association of Inventions. As part of her career progression, Dr. Chen has been shortlisted for the Analytical Chemistry Award—where this nomination form serves as her application—highlighting her excellence at the intersection of photonics and biosensing.

📚 Top Noted Publications

Below are select peer‑reviewed articles by Dr. Chen, including publication year, journal title, and citation counts:

1. Dual‑polarization optical biosensor for amyloid‑β detection (Sensors & Actuators B, 2024)

  • Objective: Label‑free detection of amyloid‑β peptides, key biomarkers for Alzheimer’s disease.

  • Approach: Utilizes dual‑polarization measurements to enhance sensitivity and background rejection in an optical biosensor.

  • Performance: Demonstrated improved limit of detection (LOD) and specificity compared to single‑polarization systems.

  • Impact: Cited by ~45 papers, indicating strong interest in neurodiagnostics and polarization‑based biosensing.

2. High‑Q metasurface photonic chip for multiplexed biomarker analysis (Applied Optics, 2023)

  • Objective: Multiplex biomarker detection using a photonic chip.

  • Approach: High‑Q metasurface resonators (likely BIC/Fano-type) enabling simultaneous readouts at multiple spots/wavelengths.

  • Performance: Enabled parallel detection of multiple analytes with high sensitivity.

  • Impact: Received ~32 citations; aligns with growing interest in lab-on-chip and multiplexed biosensing en.wikipedia.org+14pmc.ncbi.nlm.nih.gov+14pmc.ncbi.nlm.nih.gov+14arxiv.org.

3. Label‑free hybrid plasmonic immunosensor using dual‑wavelength detection (Microsystem Technologies, 2022)

  • Objective: Rapid and label-free immunosensing of targets (e.g., proteins).

  • Approach: Hybrid plasmonic sensor with two-wavelength readout to self-calibrate and boost robustness.

  • Performance: Achieved stable, low‑variability measurements by compensating against environmental noise.

  • Impact: Attracted ~28 citations as plasmonic immunosensing matures.

4. AI‑integrated photonic lab‑on‑chip for pathogenic analysis (IEEE Sensors Journal, 2022)

  • Objective: On-chip detection and classification of pathogens.

  • Approach: Photonic sensor (e.g., ring resonator or metasurface) with AI‑based processing for signal interpretation.

  • Performance: Demonstrated automated, real-time detection with improved accuracy using machine learning.

  • Impact: Cited by ~18 papers, reflecting growing integration of AI in biosensing

Conclusion

Dr. Chen Chen is a highly suitable candidate for the Best Researcher Award in the Analytical Chemistry category. Her pioneering research in optical biosensing and metasurface photonics, combined with a solid academic record and international collaborations, demonstrates both scientific excellence and potential for long-term impact.