Jingyi Gao | Engineering | Best Researcher Award

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Ms. Jingyi Gao | University of Virginia | United States

Ms. Jingyi Gao | University of Virginia | United States

Jingyi Gao is a Ph.D. candidate in Systems and Information Engineering at the University of Virginia with a 3.75 GPA, focusing on time series prediction, Bayesian probabilistic modeling, and federated learning. She holds an M.S. in Applied Mathematics and Statistics from the Johns Hopkins University (GPA 3.9) and dual bachelor’s degrees in Mathematics–Computer Science and Economics from the University of California, San Diego. Jingyi has extensive teaching experience, serving as a teaching assistant at UVA where she has instructed over 1,000 students across multiple courses in statistical modeling, data mining, AI, and big data systems, and previously supported courses at Johns Hopkins and UC San Diego. She has mentored underrepresented students through the Data Justice Academy and completed research internships at the University of Pittsburgh and Tencent, developing machine learning models for stress detection, healthcare data analysis, and cloud resource forecasting. Jingyi has authored several publications, including work accepted by Pattern Recognition and under review at AAAI and IISE Transactions. Her recent projects involve designing deep latent variable models for ergonomic risk assessment, developing real-time adaptive prediction frameworks for occupational health monitoring, creating federated learning approaches for multi-output Gaussian processes, and modeling behavioral regularity and predictability from multidimensional sensing signals. Combining expertise in machine learning, statistical modeling, and data-driven decision systems, Jingyi aims to advance human-centered intelligent systems through interpretable and privacy-preserving predictive modeling.

Profile: Scopus | Google Scholar

Featured Publications 

Gao, J., Rahman, A., Lim, S., & Chung, S. TimeSets: A real-time adaptive prediction framework for multivariate time series (Manuscript under review at the Association for the Advancement of Artificial Intelligence).

Gao, J., Lim, S., & Chung, S. Gait-based hand load estimation via deep latent variable models with auxiliary information (Manuscript under review at IISE Transactions).

Gao, J., & Chung, S. Federated automatic latent variable selection in multi-output Gaussian processes (Accepted for publication in Pattern Recognition)*.

Gao, J., Yan, R., & Doryab, A. Modeling regularity and predictability in human behavior from multidimensional sensing signals and personal characteristics. Proceedings of the International Conference on Machine Learning and Applications (ICMLA). Institute of Electrical and Electronics Engineers.

Chen, T., Chen, Y., Gao, J., Gao, P., Moon, J. H., Ren, J., … & Woolf, T. B. Machine learning to summarize and provide context for sleep and eating schedules. bioRxiv.

Chen Chen | Engineering | Best Researcher Award

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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

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🎓 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.

Nan Li | Engineering | Best Researcher Award

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Dr. Nan Li | Engineering | Best Researcher Award

Associate researcher at erospace Information Research Institute, Chinese Academy of Sciences, China

Dr. Nan Li is an accomplished Associate Researcher at the State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences. With a strong interdisciplinary foundation in biomedical engineering and automation, she specializes in developing microfluidic-based nucleic acid and immunoassay detection systems. Dr. Li has contributed significantly to the advancement of rapid, portable, and sensitive diagnostic technologies, many of which are aimed at point-of-care and field diagnostics for infectious diseases. Her work is deeply rooted in translational research, seamlessly integrating microengineering, biotechnology, and clinical diagnostics.

Profile

Scopus

🎓 Education

Dr. Nan Li received her Ph.D. in Biomedical Engineering from the prestigious Tsinghua University in 2022, after completing her undergraduate degree in Automation from the Beijing Institute of Technology in 2016. During her doctoral studies, she focused on the development of centrifugal microfluidic platforms and integrated biosensing systems, gaining critical experience in both academic research and real-world biomedical applications. Her academic journey laid the groundwork for a career dedicated to creating impactful diagnostic tools for global healthcare needs.

💼 Experience

Dr. Li currently serves as an Associate Researcher at the Chinese Academy of Sciences, where she leads projects under the State Key Laboratory of Transducer Technology. She has also been actively involved in collaborative efforts with academic and industrial partners to translate laboratory innovations into commercial and clinical applications. In addition to her research responsibilities, Dr. Li contributes to scholarly activities as a journal reviewer for Microsystems & Nanoengineering and Current Analytical Chemistry. She has also delivered oral presentations at prominent international conferences such as Transducers 2025 and IEEE Sensors 2024, further reflecting her stature in the field.

🔬 Research Interests

Dr. Li’s core research interest lies in microfluidic technology for nucleic acid amplification, multiplex detection, and point-of-care diagnostics. She is particularly focused on developing integrated fluidic systems that are capable of rapid, accurate, and simultaneous detection of multiple pathogens or biomarkers. Her work often involves combining engineering principles such as centrifugal force and Euler force with advanced biochemical assays like LAMP and CRISPR. This interdisciplinary approach enables her to create portable diagnostic tools with immense potential in epidemic control, food safety, and personalized medicine.

🏆 Awards

Dr. Nan Li’s exceptional work has earned her several prestigious honors, including the Outstanding Reviewer Award from Microsystems & Nanoengineering in 2024. She was recognized as one of the Outstanding Graduates in Beijing in both 2016 and 2022. She also received the First Prize of Tsinghua University Comprehensive Scholarship in 2020 and the Gold Star Distinguished Research Award from the Biochip (Beijing) National Engineering Research Center in 2018 and 2020. Earlier in her academic journey, she was a recipient of the Tsinghua Future Scholar Scholarship, an award conferred upon top-performing doctoral candidates.

📚 Publications

Among Dr. Li’s numerous scientific publications, the following seven represent high-impact research in her field:

  1. Tianping Zhou, Nan Li* (2025). Sensors and Actuators B: Chemical. “Shockproof magnetofluidic multiplex nucleic acid system” – DOI: 10.1016/j.snb.2025.138139.

  2. Nan Li# et al. (2025). Biosensors & Bioelectronics, “Chip-based universal strategy for multiplex PCR”, Vol. 269, 116921.

  3. Bin Xiao# et al., Nan Li* (2024). Food Chemistry, “Toothpick DNA extraction with LAMP platform”, Vol. 460, 140659.

  4. Jiajia Liu# et al., Nan Li# (2024). Small Methods, “One-pot multiplex virus detection”, Vol. 8, 2400030. (Cover Article).

  5. Nan Li# et al. (2022). Sensors and Actuators B: Chemical, “Euler force-assisted sequential liquid release”, Vol. 359, 131642.

  6. Nan Li et al. (2022). Lab on a Chip, “Fully integrated SNP genotyping for hearing loss”, Vol. 22(4): 697–708. (Cover Article).

  7. Nan Li# et al. (2021). Microsystems & Nanoengineering, “Raw-sample-in multiplexed detection system”, Vol. 7(1): 94.

These works are widely cited and demonstrate her contributions to practical innovations in diagnostic technologies.

✅ Conclusion

Dr. Nan Li’s trajectory exemplifies a dedicated and forward-thinking researcher whose work merges engineering innovation with biomedical applications. Through her trailblazing research in microfluidic systems and portable diagnostics, she has not only addressed pressing needs in healthcare but also helped shape the future of rapid disease detection. Her consistent output of high-impact publications, international recognition, and impressive list of awards collectively make her a deserving candidate for a Best Paper Award. Dr. Li’s blend of creativity, precision, and practical implementation reflects the qualities that such an award seeks to honor.