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.

๐ŸŒย Professional Profileย 

Google Scholar

๐Ÿ† Suitability for Best Researcher Awardย 

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 1โ€“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.

๐ŸŽ“ Educationย 

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 Bachelorโ€™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.

๐Ÿ’ผ Experience

Prof. Shile Qi is currently an Artificial Intelligence Professor at Nanjing University of Aeronautics and Astronautics (2021โ€“present), focusing on brain image analysis, computational psychiatry, and AI-driven mental health research. From 2019โ€“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 (2018โ€“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.

๐Ÿ… Awards & Honorsย 

Prof. Shile Qiโ€™s research excellence has earned multiple prestigious awards and presentations. These include:

โœจ 2020 OHBM Merit Abstract Award (Top 1%)
โœจ 2020 & 2021 OHBM Oral Presentations (Top 3%)
โœจ 2017 OHBM Merit Abstract Award (Top 1%)
๐ŸŽค 2025 IEEE ICASSP & ISBI Oral Presentations
๐ŸŽค 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.

๐Ÿ”ฌ Research Focusย 

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.

๐Ÿ“Šย Publication Top Notesย ย 

  • 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

 

 

Mr. Feng Wang | Computational Analysis | Best Researcher Award

Mr. Feng Wang | Computational Analysis | Best Researcher Award

Mr. Feng Wang, China Three Gorges University, China

Mr. Feng Wang is an Associate Professor at China Three Gorges University, specializing in bridge and tunnel engineering. With a Ph.D. from Wuhan University of Technology, he has conducted groundbreaking research on nonlinear dynamic responses of long-span cable structures. His work has been applied in major engineering projects, contributing significantly to seismic design and wind/ice resistance of overhead transmission lines. As a visiting scholar at The University of Queensland, he collaborated with leading experts to enhance computational analysis methods. With over 50 academic publications and 60 patents, Mr. Wangโ€™s contributions have had a lasting impact on structural engineering. His interdisciplinary approach integrates AI-driven assessment models, vibration suppression techniques, and disaster protection strategies, making him a leader in modern civil engineering. Recognized with multiple teaching awards, he continues to mentor young engineers while advancing critical infrastructure development. ๐Ÿš€๐Ÿ—๏ธ

๐ŸŒ Professional Profile

Orcid

๐Ÿ† Suitability for Best Researcher Awardย 

Mr. Feng Wang is a highly accomplished researcher whose work in structural engineering has led to significant advancements in bridge safety, vibration control, and AI-driven assessment models. His contributions address critical engineering challenges, including dynamic catastrophe protection and seismic resistance for large-scale structures. Having led and participated in over 30 research projects funded by prestigious organizations, he has demonstrated exceptional expertise and innovation. His 50+ publications in high-impact journals, 60 patents, and multiple software copyrights reflect his leadership in applied research. His work aligns with global infrastructure development strategies, including the Belt and Road Initiative. Additionally, his recognition as an “Excellent Instructor” underscores his dedication to academia. Mr. Wang’s research not only pushes theoretical boundaries but also translates into real-world applications, making him an outstanding candidate for the Best Researcher Award. ๐Ÿ…๐Ÿ”ฌ

๐Ÿ“š Education

  • Ph.D. in Bridge and Tunnel Engineering (2007โ€“2010) โ€“ Wuhan University of Technology ๐ŸŽ“

    • Dissertation: “Geometric Nonlinear Analysis of Long-Span Three-Tower Composite Girder Cable-Stayed Bridges”
    • Awarded Outstanding PhD Dissertation Award
    • Supervised by Prof. Liu Muyu, Director of the Hubei Provincial Key Laboratory of Road and Bridge Engineering
  • Visiting Scholar (2019โ€“2020) โ€“ The University of Queensland, Australia ๐ŸŒ

    • Fully funded by the China Scholarship Council
    • Collaborated with Prof. Chien Ming Wang on nonlinear dynamics of long-span cable structures

His education provided a strong foundation in computational mechanics, structural stability, and interdisciplinary engineering applications, enabling his impactful research in bridge safety and AI-driven assessment methods. ๐ŸŽ“๐Ÿ“–

๐Ÿ‘จโ€๐Ÿ”ฌ Experienceย 

  • Associate Professor, China Three Gorges University (2015โ€“Present) ๐Ÿ—๏ธ

    • Conducts research in bridge engineering, computational analysis, and AI-driven infrastructure assessment
    • Supervises Master’s students in civil and electrical engineering
  • Lecturer, China Three Gorges University (2011โ€“2015) ๐Ÿ“š

    • Promoted to Associate Professor in 2015
  • Assistant Engineer, China Communications Construction Company (2002โ€“2004) ๐Ÿšง

    • Worked on highway base and surface construction
  • Visiting Researcher, The University of Queensland (2019โ€“2020) ๐ŸŒ

    • Specialized in long-span cable structure dynamics

With over two decades of experience in academia and industry, Mr. Wang has contributed to major engineering projects and advanced computational methods in structural analysis. ๐Ÿ”๐Ÿ—๏ธ

๐Ÿ… Awards and Honors

  • Outstanding PhD Dissertation Award (2010) โ€“ Wuhan University of Technology ๐ŸŽ“๐Ÿ†
  • Excellent Instructor Award (2014, 2017, 2018) โ€“ “Gaojiao Cup” National College Students’ Advanced Drawing Technology Competition ๐Ÿ…๐Ÿ‘จโ€๐Ÿซ
  • National Natural Science Foundation of China (NSFC) Grant Recipient โ€“ Led multiple funded research projects ๐Ÿ’ฐ๐Ÿ”ฌ
  • China Scholarship Council Award (2019โ€“2020) โ€“ Fully funded visiting scholar at The University of Queensland ๐Ÿ‡จ๐Ÿ‡ณ๐ŸŒ
  • 60+ Patents & 5 Software Copyrights โ€“ Innovations in bridge engineering, AI models, and disaster protection ๐Ÿ—๏ธ๐Ÿ’ก

Mr. Wangโ€™s recognitions highlight his research excellence, innovation, and contributions to structural engineering and education. ๐ŸŒŸ๐ŸŽ–๏ธ

๐Ÿ”ฌ Research Focusย 

Mr. Feng Wangโ€™s research revolves around computational structural analysis, AI-driven assessment models, and disaster protection technologies for large-scale infrastructure. His work in geometric nonlinear analysis enhances bridge safety and longevity, while his vibration suppression techniques improve the stability of ultra-long stay cables. He has pioneered AI-based models to assess bridge components, ensuring optimal maintenance and damage prevention. His research extends to dynamic catastrophe protection, helping safeguard overhead transmission lines from extreme environmental conditions. ๐ŸŒ‰๐Ÿ’ก

By integrating Big Data Analytics, AI, and engineering mechanics, he develops predictive models that optimize bridge resilience. His interdisciplinary approach aligns with Chinaโ€™s Belt and Road Initiative, focusing on sustainable infrastructure. His contributions advance both fundamental research and practical applications, making a lasting impact on structural engineering. ๐Ÿ—๏ธ๐Ÿ”

Publication Top Notes:

Title : Coupled Parametric Vibration Model and Response Analysis of Single Beam and Double Cable Under Deterministic Harmonic and Random Excitation
Published Year : 2024