Yuhe Shen | Biochemistry, Genetics and Molecular Biology | Young Scientist Award

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Young Scientist Award: Yuhe Shen

Yuhe Shen
Tianjin University, China

Yuhe Shen
Affiliation Tianjin University
Country China
Scopus ID 57220027058
Documents 29
Citations 470
h-index 14
Subject Area Biochemistry, Genetics and Molecular Biology
Event Global Innovation Technologist Awards
ORCID 0009-0009-0535-5998

The Young Scientist Award article presents the reported academic profile and selected research publications of Yuhe Shen, affiliated with Tianjin University, China. The supplied profile records 29 documents, 470 citations and an h-index of 14. The selected 2026 publications address peptide-based nanozymes, nucleic acid delivery and enzyme-mimetic hydrogels, illustrating research themes at the intersection of molecular science, nanomaterials and potential biomedical applications. These details provide context for considering research contributions and award suitability, while formal recognition remains subject to the award programme’s assessment procedures.

Abstract

Yuhe Shen’s supplied publication record highlights three research directions reported in 2026: colorimetric glutathione detection using a peptide-based iron nanozyme, nucleic acid delivery through peptide dendrimer-liposome nanocomplexes, and enzyme-mimetic peptide hydrogels for infected inflammatory wounds. The publications appear in journals covering applied materials, nanomaterials and colloid and interface science. Together, these topics connect material design with analytical sensing and prospective biomedical applications. Bibliographic details and researcher metrics are presented as supplied and should be verified against the linked scholarly records. [1] [2] [3]

Keywords

Yuhe Shen; Young Scientist Award; Tianjin University; peptide nanozymes; glutathione detection; peptide dendrimers; liposome nanocomplexes; nucleic acid delivery; enzyme-mimetic hydrogels; biochemistry; molecular biology; nanomaterials; biomedical research.

Introduction

Research spanning biochemistry and nanomaterials investigates how molecular structures can be engineered for sensing, delivery and therapeutic applications. Peptides are of interest because their sequences and assembly behaviour can be tailored to create functional materials. The three supplied publications provide a focused view of these approaches and their potential relevance to interdisciplinary research. [1]–[3]

Research Profile

The supplied profile identifies Tianjin University as Shen’s institutional affiliation and Biochemistry, Genetics and Molecular Biology as the principal subject area. The reported Scopus indicators are 29 documents, 470 citations and an h-index of 14. These measures describe aspects of indexed publication output and citation activity; they do not independently establish the quality, originality or practical impact of each contribution. [4]

Research Contributions

The selected publications indicate three complementary directions:

  • Peptide-based iron nanozymes designed for sensitive colorimetric detection of glutathione, an important molecule in cellular redox biology. [1]
  • Peptide dendrimer-liposome nanocomplexes developed for nucleic acid delivery, a research area relevant to molecular and biomedical technologies. [2]
  • Dynamic enzyme-mimetic peptide hydrogels investigated for applications involving bacterial-infected inflammatory wounds. [3]

Publications

  1. “A Peptide-Based Iron Nanozyme with Multienzyme-Mimetic Activity for Sensitive Colorimetric Detection of Glutathione.” ACS Applied Materials & Interfaces (2026). [1]
  2. “Design of Peptide Dendrimer-Liposome Nanocomplexes for Efficient Nucleic Acid Delivery.” ACS Applied Nano Materials (2026). [2]
  3. “Dynamic enzyme-mimetic peptide hydrogel for the treatment of bacterial-infected inflammatory wounds.” Journal of Colloid and Interface Science (2026). [3]

Research Impact

The reported citation count and h-index suggest an established indexed research record, although citation metrics vary with database coverage, publication age and disciplinary practices. The listed topics have potential relevance to analytical detection, nucleic acid delivery and biomaterial-based wound research. Assessing their scientific impact more fully would require examining experimental results, methodological limitations, independent replication and subsequent use by other researchers. [4]

Award Suitability

The combination of interdisciplinary publication topics and the supplied bibliometric indicators provides a basis for consideration under a young researcher recognition category. A comprehensive assessment should also examine Shen’s specific authorship contributions, research independence, methodological rigour, publication verification and relevance to the award criteria. This profile does not constitute confirmation of nomination, selection or receipt of an award.

Conclusion

Yuhe Shen’s supplied profile and selected 2026 publications describe research at the intersection of peptide engineering, functional nanomaterials and biomedical applications. The work provides a relevant foundation for scholarly evaluation in biochemistry and molecular science. Further assessment using verified publication records and evidence of individual research contributions would support a balanced award review.

References

  1. “A Peptide-Based Iron Nanozyme with Multienzyme-Mimetic Activity for Sensitive Colorimetric Detection of Glutathione.” (2026). ACS Applied Materials & Interfaces. DOI: 10.1021/ACSAMI.6C03146.
    https://doi.org/10.1021/ACSAMI.6C03146
  2. “Design of Peptide Dendrimer-Liposome Nanocomplexes for Efficient Nucleic Acid Delivery.” (2026). ACS Applied Nano Materials. DOI: 10.1021/ACSANM.6C01329.
    https://doi.org/10.1021/ACSANM.6C01329
  3. “Dynamic enzyme-mimetic peptide hydrogel for the treatment of bacterial-infected inflammatory wounds.” (2026). Journal of Colloid and Interface Science. DOI: 10.1016/J.JCIS.2026.140210.
    https://doi.org/10.1016/J.JCIS.2026.140210
  4. Elsevier. (n.d.). Scopus author details: Yuhe Shen, Author ID 57220027058. Scopus. Profile metrics should be checked against the current indexed record.
    https://www.scopus.com/authid/detail.uri?authorId=57220027058
  5. ORCID. (n.d.). Yuhe Shen researcher identifier. ORCID provides persistent researcher identifiers for distinguishing scholarly contributors.
    https://orcid.org/0009-0009-0535-5998

Isha Saini | Biology and Life Sciences | Best Researcher Award

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Best Researcher Award

Isha Saini
Panjab University, India

Isha Saini
Affiliation Panjab University
Country India
Scopus ID 57815138900
Documents 5
Citations 65
h-index 3
Subject area Biology and Life Sciences
Event Global Innovation Technologist Awards

Isha Saini is a researcher affiliated with Panjab University, India, whose reported research profile falls within biology and life sciences. Her listed publication, “Enhancing memory T cell responses through Soluble Leishmania antigen and natural adjuvants against Leishmania donovani in murine model,” addresses immune responses relevant to experimental research on leishmaniasis. This article presents her research profile and its relevance to the Best Researcher Award category associated with the Global Innovation Technologist Awards.

Abstract

This profile summarizes the available bibliographic information and research topic associated with Isha Saini. Her listed 2026 publication investigates memory T-cell responses following exposure to soluble Leishmania antigen and natural adjuvants in a murine model of Leishmania donovani infection. The research topic connects experimental immunology with the study of host responses to a parasitic disease. The profile records five documents, 65 citations and an h-index of three as supplied data; these metrics should be checked against the current indexed author record before formal evaluation. [1] [2]

Keywords

Isha Saini; immunology; memory T cells; Leishmania donovani; soluble Leishmania antigen; natural adjuvants; murine model; biology and life sciences; research impact.

Introduction

Leishmaniasis is a parasitic disease caused by organisms of the genus Leishmania. Research into host immunity can help clarify how immune cells respond to infection and how experimental approaches might inform future prevention or treatment strategies. Memory T cells are important to adaptive immunity because they can respond to previously encountered antigens. Studies examining these responses contribute to broader investigations of immune mechanisms and experimental immunology. [3]

Research Profile

The available profile identifies Panjab University as the researcher’s institutional affiliation and biology and life sciences as the relevant subject area. The reported Scopus author identifier is 57815138900. An ORCID identifier was not supplied and is therefore recorded as unavailable. Institutional affiliation, author identity and publication metadata should be confirmed using the relevant research databases. [1]

Research Contributions

The listed study focuses on soluble parasite antigen, natural adjuvants and memory T-cell responses in a mouse model. These themes are relevant to understanding immune responses under controlled experimental conditions. The study title alone does not establish the direction or magnitude of any observed effect, so detailed conclusions should be based on the published article’s methods, results and discussion rather than inferred from its title. [2]

Publications

The supplied publication record lists the following 2026 article in Microbial Pathogenesis:

  • Saini, Isha, and Kaur, Sukhbir. “Enhancing memory T cell responses through Soluble Leishmania antigen and natural adjuvants against Leishmania donovani in murine model.” Microbial Pathogenesis (2026). DOI and complete publication details were not provided in the supplied record.

Research Impact

The supplied bibliometric figures are five documents, 65 citations and an h-index of three. Citation counts can change as databases are updated, and author profiles may require disambiguation. These figures provide quantitative indicators of indexed research activity but do not independently measure methodological quality, originality or practical significance. [1]

Award Suitability

The research topic and reported bibliometric indicators provide information relevant to considering the profile for the Best Researcher Award category of the Global Innovation Technologist Awards. A balanced assessment should consider publication quality, individual contribution, research integrity, citation context and relevance to the subject area. The available information does not by itself establish an award decision or independent verification of the reported metrics.

Conclusion

Isha Saini’s listed research concerns experimental immunology and T-cell responses in a murine model of Leishmania donovani. The supplied profile provides a starting point for evaluating research activity and subject relevance. Verification of the publication record, author identity, citation metrics and full-text findings is recommended before making formal scholarly or award-related judgments.

References

  1. Elsevier. (n.d.). Scopus author details: Isha Saini, Author ID 57815138900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57815138900
  2. Saini, Isha, and Sukhbir Kaur. (2026). “Enhancing memory T cell responses through Soluble Leishmania antigen and natural adjuvants against Leishmania donovani in murine model.” Microbial Pathogenesis. Bibliographic details reproduced from the supplied publication record; DOI not provided.
  3. World Health Organization. Leishmaniasis. General background on the disease and its public-health significance.
  4. Global Innovation Technologist Awards. Official event website.
    innovationtechnologist.com

Xuechen Liang | Computer Science | Research Excellence Award

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Mr. Xuechen Liang | Computer Science | Research Excellence Award

Master | East China Jiaotong University | China

Mr. Xuechen Liang is a computer science researcher focused on large language models, multi-agent systems, and intelligent analysis in imperfect information settings. His research addresses commentary generation, strategic reasoning, and agent collaboration, with notable contributions to top-tier venues such as IJCAI, EACL, AAAI, and IEEE Access. His work spans personalized role-playing frameworks, self-evolving and memory-augmented agents, psycholinguistically inspired token reduction, and collaborative tuning methods to enhance model efficiency and performance. His scholarly output includes 7 research documents, receiving 8 citations, and reflects an h-index of 2, demonstrating growing academic impact in advanced AI and language model research.

Citation Metrics (Scopus)

10

8

6

4

2

0

Citations
8

Documents
7

h-index
2

Citations

Documents

h-index

Featured Publications

Self-Evolving Agents with Reflective Memory for Complex Decision Tasks

– arXiv Preprint, 2024

Mahir Sharif | Bioinformatics | Best Researcher Award

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Assist. Prof. Dr. Mahir Sharif | Bioinformatics | Best Researcher Award

Prince Sattam ibn Abdelaziz University | Saudi Arabia

Dr. Mahir M. Sharif is an accomplished academic and researcher in the field of Computer Science, specializing in Computational Intelligence and Bioinformatics. He has extensive experience in academia, research, and administration, complemented by leadership roles in multiple universities and colleges. His career reflects a strong commitment to innovation, digital transformation, and applied research in artificial intelligence, deep learning, and assistive technologies.

Publication Profile 

Scopus

Educational Background 

He holds a Ph.D. in Computer Science with a specialization in Computational Intelligence and Bioinformatics from Cairo University. He also earned an M.Sc. in Computer Science from Elneelain University and a B.Sc. in Computer Science from Omdurman Islamic University with distinction.

Professional Experience 

Dr. Sharif has served as an Associate Professor of Computer Science at Stars College for Medical Science and Technology and has held several academic positions, including Assistant Professor at Omdurman Islamic University, Prince Sattam ibn Abdel Aziz University, and other institutions. He has extensive teaching experience in computer science and has contributed as a professional trainer in computer skills and applications. Additionally, he has significant administrative experience, serving as Dean, Deputy Dean, and Head of Departments in various faculties, where he demonstrated strong leadership in academic governance and program development.

Research Interests 

His research focuses on artificial intelligence, deep learning, computational intelligence, bioinformatics, assistive technologies, and smart systems. His recent work includes developing advanced object detection models for visually impaired individuals, enhancing cybersecurity threat detection, and exploring AI-driven applications in IoT and smart cities.

Awards and Honors 

Dr. Sharif has received recognition for his contributions to academia and research through leadership roles, membership in scientific councils, and participation in international conferences and research forums. He has also led and contributed to several funded research projects, notably in AI-driven accessibility technologies and digital platforms for data management.

Research Skills 

He possesses strong expertise in artificial intelligence, machine learning, deep learning algorithms, object detection systems, computational modeling, bioinformatics, and the design of smart solutions. His skills also extend to managing research projects, supervising postgraduate research, and implementing innovative technology-driven approaches to real-world problems.

Publications 

  1. Leveraging Assistive Technology for Visually Impaired People Through Optimal Deep Transfer Learning Based Object Detection Model
    Year: 2025

  2. Advanced object detection for smart accessibility: a Yolov10 with marine predator algorithm to aid visually challenged people
    Year: 2025

  3. Feature enhancement model with up sampling based cyber threat attack detection and classification on imbalanced dataset in Industrial Internet of Things
    Year: 2025

  4. IoT in urban development: insight into smart city applications, case studies, challenges, and future prospects
    Year: 2025

  5. Artificial intelligence with greater cane rat algorithm driven robust speech emotion recognition approach
    Year: 2025

Conclusion 

Dr. Mahir M. Sharif exemplifies a dedicated researcher and academic leader with a strong track record in teaching, research, and administration. His contributions to artificial intelligence applications, assistive technologies, and digital innovation demonstrate his capability to bridge academic research with societal impact. His leadership in funded projects and involvement in international collaborations further highlights his commitment to advancing knowledge and technology for the betterment of education and community development.

Tianyi Yan | Computational Neuroscience | Best Researcher Award

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Prof. Dr. Tianyi Yan | Computational Neuroscience | Best Researcher Award

Vice Dean at School of Medical Technology, Beijing Institute of Technology, China

Tianyi Yan is a prominent researcher and educator in biomedical engineering, dedicated to exploring innovative solutions for brain health and cognitive enhancement. With numerous accolades and a rich publication record, he is shaping the future of neuroscience and technology integration. 🧠✨

Publication Profile : 

Scopus

 

🎓 Educational Background :

Tianyi Yan obtained a PhD in Biomedical Engineering from Okayama University, Japan, in 2004. He also holds an MSc in Biomedical Engineering from Kagawa University (2003) and a BSc in Electronic Engineering from Changchun University of Science and Technology, China (2001).

💼 Professional Experience :

Currently, he serves as the Vice Dean of the School of Medical Technology and the School of Life Sciences at the Beijing Institute of Technology (BIT) since March 2020. He has been a Professor at BIT since 2016 and the Director of the Department of Biomedical Engineering since July 2018. His academic journey began as a Lecturer at BIT in 2011, followed by a post-doctoral position at Okayama University.

📚 Research Interests : 

His research spans several areas, including Brain Science and Neuronal Engineering, Cognitive Neuroscience, Brain-Computer Interfaces, and non-invasive neuromodulation for brain disease diagnosis. He focuses on developing algorithms to study neural degenerative diseases, designing wearable devices for neural feedback, and advancing brain-controlled technologies.

📝 Publication Top Notes :

  1. Y. Yang, Q. Fan, T. Yan, J. Pei, and G. Li, “Network Group Partition and Core Placement Optimization for Neuromorphic Multi-Core and Multi-Chip Systems,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2024.
  2. Y. Huang, Y. Li, Y. Yuan, X. Zhang, W. Yan, T. Li, Y. Niu, M. Xu, T. Yan, X. Li, D. Li, J. Xiang, B. Wang, and T. Yan, “Beta-informativeness-diffusion multilayer graph embedding for brain network analysis,” Frontiers in Neuroscience, vol. 18, no. 1303741, 2024.
  3. S. Liu, M. Liu, D. Zhang, Z. Ming, Z. Liu, Q. Chen, L. Ma, J. Luo, J. Zhang, D. Suo, G. Pei, and T. Yan, “Brain-Controlled Hand Exoskeleton Based on Augmented Reality-Fused Stimulus Paradigm,” IEEE Journal of Biomedical and Health Informatics, 2024.
  4. S. Liu, Z. Ming, M. Liu, D. Zhang, Z. Liu, Q. Chen, L. Ma, J. Luo, D. Suo, J. Zhang, and T. Yan, “Remote-Oriented Brain-Controlled Unmanned Aerial Vehicle for IoT,” IEEE Internet of Things Journal, 2024.
  5. J. Wu, L. Ma, D. Luo, Z. Jin, L. Wang, L. Wang, T. Li, J. Zhang, T. Liu, D. Lv, T. Yan, and B. Fang, “Functional and structural gradients reveal atypical hierarchical organization of Parkinson’s disease,” Human Brain Mapping, vol. 45, no. 4, e26647, 2024.
  6. J. Lu, T. Yan, L. Yang, X. Zhang, J. Li, D. Li, J. Xiang, and B. Wang, “Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability,” NeuroImage, vol. 295, 2024, pp. 120651.
  7. M. Yao, O. Richter, G. Zhao, N. Qiao, Y. Xing, D. Wang, T. Hu, W. Fang, T. Demirci, M.D. Marchi, L. Deng, T. Yan, C. Nielsen, S. Sheik, C. Wu, Y. Tian, B. Xu, and G. Li, “Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip,” Nature Communications, vol. 15, no. 1, p. 4464, 2024.
  8. G. Wang, N. Jiang, Y. Ma, T. Liu, D. Chen, J. Wu, G. Li, D. Liang, and T. Yan, “Connectional-style-guided contextual representation learning for brain disease diagnosis,” Neural Networks, vol. 175, 2024, pp. 106296.
  9. G. Wang, N. Jiang, Y. Ma, D. Suo, T. Liu, S. Funahashi, and T. Yan, “Using a deep generation network reveals neuroanatomical specificity in hemispheres,” Patterns, vol. 5, no. 4, 2024.
  10. G. Wang, N. Jiang, T. Liu, L. Wang, D. Suo, D. Chen, S. Funahashi, and T. Yan, “Using unsupervised capsule neural network reveal spatial representations in the human brain,” Human Brain Mapping, vol. 45, no. 5, e26573, 2024.
  11. L. Wang, S. Li, L. Gong, Z. Zheng, Y. Chen, G. Chen, and T. Yan, “Right parietal repetitive transcranial magnetic stimulation in obsessive-compulsive disorder: A pilot study,” Asian Journal of Psychiatry, vol. 93, Mar. 2024, pp. 103902.
  12. T. Li, T. Liu, J. Zhang, Y. Ma, G. Wang, D. Suo, B. Yang, X. Wang, S. Funahashi, K. Zhang, B. Fang, and T. Yan, “Neurovascular coupling dysfunction of visual network organization in Parkinson’s disease,” Neurobiology of Disease, 2023, pp. 106323.
  13. J. Zhang, Y. Yang, T. Liu, Z. Shi, G. Pei, L. Wang, J. Wu, S. Funahashi, D. Suo, C. Wang, and T. Yan, “Functional connectivity in people at clinical and familial high risk for schizophrenia,” Psychiatry Research, vol. 328, 2023, pp. 115464.
  14. T. Yan, G. Wang, T. Liu, G. Li, C. Wang, and D. Suo, G. Pei, “Effects of Microstate Dynamic Brain Networks Disruption in Different Stages of Schizophrenia,” IEEE Transactions on Neural Systems & Rehabilitation Engineering, vol. 31, 2023, pp. 2688-2697.
  15. T. Li, L. Wang, Z. Piao, K. Chen, X. Yu, Q. Wen, D. Suo, C. Zhang, S. Funahashi, G. Pei, B. Fang, and T. Yan, “Altered Neurovascular Coupling for Multidisciplinary Intensive Rehabilitation in Parkinson’s Disease,” The Journal of Neuroscience, vol. 1, no. 1, 2023, pp. 1204-1222.