Prof. Shile Qi | Bioinformatics | Best Researcher Award

Prof. Shile Qi | Bioinformatics | Best Researcher Award

Prof. Shile Qi, Nanjing University of Aeronautics and Astronautics, China

Prof. Shile Qi is a distinguished expert in computational psychiatry, brain imaging, and data science, currently serving as a Professor of Artificial Intelligence at Nanjing University of Aeronautics and Astronautics. With postdoctoral experience at TReNDS (Georgia State, Georgia Tech, Emory) and The Mind Research Network (USA), Prof. Qi specializes in multimodal neuroimaging, machine learning, and individualized mental health prediction. His research has been recognized globally through prestigious presentations and awards at IEEE ISBI, ICASSP, and OHBM. His work bridges AI, neuroscience, and psychiatry, advancing early diagnosis and personalized treatment of disorders like schizophrenia and depression. Prof. Qi is a rising leader in neuroinformatics, integrating computational innovation with medical science for impactful mental health solutions.

šŸŒĀ Professional ProfileĀ 

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šŸ† Suitability for Best Researcher AwardĀ 

Prof. Shile Qi is an exceptional candidate for the Best Researcher Award due to his high-impact contributions in computational neuroscience and AI-powered psychiatry. His groundbreaking work in individualized mental health prediction, multimodal brain data fusion, and bioinformatics has earned him multiple international honors and oral presentations at top-tier conferences like IEEE ISBI, ICASSP, and OHBM (top 1–3%). With a proven record of excellence in brain imaging and mental health research, he offers innovative tools for diagnosing complex psychiatric disorders. His international training, interdisciplinary skills, and leadership in neuroimaging AI make him a transformative figure driving precision psychiatry forward. Prof. Qi exemplifies the ideal balance of academic rigor, innovation, and societal impact.

šŸŽ“ EducationĀ 

Prof. Shile Qi earned his Ph.D. in Pattern Recognition (2018) from the Institute of Automation, Chinese Academy of Sciences, focusing on computational neuroscience and AI algorithms. He holds a Master’s degree in Mathematics (2014) from Fuzhou University, and a Bachelor’s degree in Mathematics (2011) from Zhoukou Normal University. His solid mathematics background supports his innovations in neuroimaging data analysis, multimodal integration, and personalized prediction models. From 2018 to 2021, he completed prestigious postdoctoral fellowships in the U.S. at The Mind Research Network and the TReNDS Center, working alongside leading experts in neuroimaging, psychiatry, and AI. His education reflects a unique blend of mathematics, pattern recognition, and brain science, forming the foundation of his cutting-edge research.

šŸ’¼ Experience

Prof. Shile Qi is currently an Artificial Intelligence Professor at Nanjing University of Aeronautics and Astronautics (2021–present), focusing on brain image analysis, computational psychiatry, and AI-driven mental health research. From 2019–2021, he was a Postdoctoral Researcher at TReNDS (a collaborative center of Georgia State, Georgia Tech, and Emory University), where he worked on multimodal data fusion and individualized prediction of psychiatric disorders. Earlier, he completed a postdoc at The Mind Research Network (2018–2019), contributing to high-level brain imaging studies. With extensive experience in interdisciplinary collaboration, Prof. Qi has published and presented work at global platforms and continues to pioneer AI-based diagnostics in neuroscience, combining machine learning, data science, and clinical insights.

šŸ… Awards & HonorsĀ 

Prof. Shile Qi’s research excellence has earned multiple prestigious awards and presentations. These include:

✨ 2020 OHBM Merit Abstract Award (Top 1%)
✨ 2020 & 2021 OHBM Oral Presentations (Top 3%)
✨ 2017 OHBM Merit Abstract Award (Top 1%)
šŸŽ¤ 2025 IEEE ICASSP & ISBI Oral Presentations
šŸŽ¤ 2021 IEEE ISBI Oral Presentation

His work on multiple psychiatric disorders and ECT treatment studies was consistently ranked among the top abstracts internationally. These honors highlight his cutting-edge contributions to neuroimaging, AI-based psychiatry, and multimodal data fusion. Recognized for technical depth, innovation, and clinical relevance, Prof. Qi has emerged as a thought leader in computational neuroscience, driving AI-enhanced healthcare forward globally.

šŸ”¬ Research FocusĀ 

Prof. Shile Qi’s research lies at the intersection of AI, neuroscience, and psychiatry. He specializes in computational psychiatry, using brain imaging and bioinformatics to model mental disorders like schizophrenia and depression. His expertise spans multimodal data fusion, individualized prediction models, and deep learning techniques for detecting subtle brain abnormalities. Prof. Qi develops novel methods to integrate MRI, fMRI, EEG, and other neuroimaging data, providing personalized insights for early diagnosis and treatment planning. He also contributes to bioinformatics and mental health AI, creating predictive models that are both clinically relevant and technically robust. His work aims to transform how psychiatric conditions are understood, detected, and managed through neuroinformatics innovation.

šŸ“ŠĀ Publication Top NotesĀ Ā 

  • Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

    • Citations: 159
    • Year: 2018

  • Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships

    • Citations: 151
    • Year: 2020

  • Aberrant dynamic functional network connectivity and graph properties in major depressive disorder

    • Citations: 148
    • Year: 2018

  • Gender differences in connectome-based predictions of individualized intelligence quotient and sub-domain scores

    • Citations: 137
    • Year: 2020

  • Connectome-based individualized prediction of temperament trait scores

    • Citations: 87
    • Year: 2018

 

 

Ms. Jing Jing | Bioinformatics Awards | Best Researcher Award

Ms. Jing Jing | Bioinformatics Awards | Best Researcher Award

Ms. Jing Jing, Qufu Normal University, China

Ms. Jing Jing is a dedicated graduate student in Computer Science at Qufu Normal University, China, where she also earned her B.S. in Computer Science. Her research focuses on pattern recognition, spatial transcriptomics, and bioinformatics, where she applies computational tools to manage and analyze complex biological data. Through her work, Ms. Jing is contributing to the emerging intersection of spatial information and gene expression, advancing the field of bioinformatics with innovative research.

Professional Profile:

Scopus

Suitability for the Award

Ms. Jing Jing is at an early stage in her research career but has already made notable contributions to the fields of pattern recognition, spatial transcriptomics, and bioinformatics. Here’s an assessment of her suitability for the Best Researcher Award:

  1. Research Focus on Emerging Fields:

    • Her work in spatial transcriptomics and bioinformatics positions her at the forefront of an emerging and highly specialized field. Spatial transcriptomics, which integrates spatial and genetic information, represents a promising area with significant potential for advancing our understanding of complex biological processes.
  2. Contributions to Scientific Knowledge:

    • Despite being in the early stages of her academic career, Ms. Jing Jing has already contributed to the scientific community through her publications. Her work on a multi-view contrastive fusion method demonstrates her ability to develop innovative solutions in bioinformatics.
  3. Academic Potential:

    • While her current citation count may be low, this is not unusual for a researcher at her stage. The importance and relevance of her research, particularly in spatial transcriptomics, suggest that her work is likely to gain recognition as the field continues to develop.
  4. Promise as a Future Leader in Research:

    • Ms. Jing Jing’s involvement in cutting-edge research areas such as spatial transcriptomics indicates strong potential for future contributions to the scientific community. Her current work lays a solid foundation for a promising research career.

Summary of Qualifications

  1. Education:

    • B.S. in Computer Science (2022), Qufu Normal University, Rizhao, China.
    • Currently pursuing a Master’s degree at the same institution, focusing on Computer Science.
  2. Research Focus:

    • Pattern Recognition.
    • Spatial Transcriptomics: An emerging field that combines spatial information with gene expression data.
    • Bioinformatics: The application of computational tools to manage, analyze, and interpret biological data.
  3. Publications:

    • “A review of recent advances in spatially resolved transcriptomics data analysis” (2024, Neurocomputing):
      • Co-authored a review article focusing on advances in spatially resolved transcriptomics, a cutting-edge area in bioinformatics.
    • “stMCFN: A Multi-view Contrastive Fusion Method for Spatial Domain Identification in Spatial Transcriptomics” (2024, Lecture Notes in Computer Science):
      • Contributed to the development of a novel multi-view contrastive fusion method aimed at improving spatial domain identification in spatial transcriptomics.
  4. Research Contributions:

    • Ms. Jing Jing has co-authored two significant publications, one of which reviews recent advancements in spatial transcriptomics data analysis, while the other proposes a new method for spatial domain identification in spatial transcriptomics.

Conclusion

While Ms. Jing Jing is still in the early stages of her research career, her focus on emerging and impactful fields such as spatial transcriptomics and bioinformatics makes her a promising candidate for future recognition. However, given the typically high standards of the Best Researcher Award, which often rewards more established researchers with significant citations and broader impact, Ms. Jing Jing might be better suited for awards or recognitions targeting early-career researchers or rising stars in the field. Her current trajectory suggests strong potential for future accomplishments that could make her a contender for more prestigious awards as she continues to develop her research portfolio.

 

 

 

Dr. Liangrui Pan | Bioinformatics | Best Researcher Award

Dr. Liangrui Pan | Bioinformatics | Best Researcher Award

Dr. Liangrui Pan, Hunan university, China

Dr. Liangrui Pan is an emerging scholar in the field of computer science, currently pursuing a Ph.D. at Hunan University, China. With a Master’s Degree in Computer Science from Prince of Songkla University, Thailand, his research interests encompass machine learning, deep learning, and pattern recognition. As a dedicated professional, Dr. Pan is actively involved in various professional organizations, holding memberships in the Chinese Society of Electrical Engineering, the IEEE Power and Energy Society, and the China Computer Federation. His engagement with these communities highlights his commitment to advancing the field and contributing to the broader scientific discourse.

🌐 Professional Profile:

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Orcid

Education

  • Ph.D. in Computer Science (Ongoing)
    • Hunan University, Changsha, China
  • Master’s Degree in Computer Science (2021)
    • Prince of Songkla University, Thailand

Research Interests

  • Machine Learning
  • Deep Learning
  • Pattern Recognition

Professional Memberships

  • Member of the Chinese Society of Electrical Engineering
  • Member of the IEEE Power and Energy Society
  • Member of the China Computer Federation

Professional Activities

  • IEEE Power and Energy Society: Beijing, China
    • Membership
  • China Computer Federation: Beijing, China
    • Membership

Publication Top Notes: