Xiaobin Li | Geometry | Best Researcher Award

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Assoc. Prof. Dr. Xiaobin Li | Geometry | Best Researcher Award

Researcher at Southwest Jiaotong University, China

Dr. Xiaobin Li, a faculty-researcher at the School of Mathematics, Southwest Jiaotong University, specializes in symplectic geometry and mathematical physics. He earned his Ph.D. from Sichuan University and has served as a visiting scholar at Beijing Normal University and the University of Utah. With six research projects and nine international collaborations, he has published extensively in leading journals such as Acta Mathematica Sinica, Science China Mathematics, and the Journal of High Energy Physics. His notable achievements include proving Ruan’s conjecture on singular symplectic flops, advancing the understanding of Nekrasov conjectures, and introducing new topological vertex algorithms. A member of the Chinese and American Mathematical Societies, Dr. Li also mentors students and contributes editorially, reflecting his dedication to advancing mathematical knowledge and fostering international academic exchange.

Professional Profile

Google Scholar | ORCID Profile 

Education

Dr. Xiaobin Li earned his Ph.D. in Mathematics from Sichuan University, where he developed a strong foundation in advanced mathematical theory and research methodology. His academic journey includes prestigious visiting scholar appointments at Beijing Normal University and the University of Utah, experiences that expanded his global academic perspective and collaborative network. These opportunities exposed him to diverse research environments, enabling him to engage with leading experts in symplectic geometry and mathematical physics. His education has been marked by a commitment to deep theoretical inquiry, a capacity for innovative problem-solving, and an openness to interdisciplinary perspectives. Through rigorous academic training and international exposure, Dr. Li has built the scholarly expertise and vision necessary to contribute groundbreaking results to contemporary mathematics and to lead in high-level research collaborations worldwide.

Experience

Dr. Xiaobin Li serves as a faculty-researcher at the School of Mathematics, Southwest Jiaotong University, where he actively combines teaching, mentorship, and high-impact research. His career includes participation in six significant research projects, several of which involve nine international collaborations with renowned institutions. He has authored numerous papers in respected journals, including Acta Mathematica Sinica, Science China Mathematics, and the Journal of High Energy Physics, earning him recognition in both the Chinese and global mathematics communities. In addition to his scholarly output, Dr. Li has contributed as an editorial board member, helping shape the academic discourse in his field. His role extends beyond academia through active engagement with professional societies, creating platforms for knowledge exchange and collaborative innovation. His diverse experience reflects both research excellence and community-oriented leadership.

Research Interest

Dr. Xiaobin Li’s research interests lie at the intersection of symplectic geometry and mathematical physics, focusing on deep and complex problems with far-reaching implications in modern theoretical mathematics. He has made notable progress in nonlinear sigma models, developing a new recursive relation from localization analysis and proving Ruan’s conjecture on singular symplectic flops. Recently, his collaborative work proved the Nekrasov conjecture for 5-brane webs with O5-planes and revealed a novel jumping phenomenon under freezing, along with introducing a new topological vertex algorithm. His research approach blends analytical precision with creative exploration, aiming to resolve longstanding conjectures and inspire new frameworks in geometry and physics. Dr. Li’s work continues to bridge mathematical theory with physical applications, pushing the boundaries of both disciplines and contributing to global scientific advancement.

Award and Honor

Throughout his academic career, Dr. Xiaobin Li has been recognized for his impactful contributions to mathematics, especially within the realms of symplectic geometry and mathematical physics. His research breakthroughs—such as proving Ruan’s conjecture and the Nekrasov conjecture—have earned him respect among peers and positioned him as a leading voice in his field. His role as an editorial board member for a reputed journal and his membership in both the Chinese Mathematical Society and the American Mathematical Society reflect his professional standing and commitment to excellence. His achievements, though primarily scholarly, represent a form of honor that extends beyond formal awards, as his work influences academic discourse globally. The nomination for the Best Researcher Award further acknowledges his sustained dedication, leadership, and contributions to the mathematical sciences.

Research Skill

Dr. Xiaobin Li possesses a diverse set of advanced research skills that underpin his success in tackling complex mathematical challenges. He is adept in geometric analysis, topological methods, and algebraic geometry techniques, allowing him to work across theoretical and applied mathematical physics domains. His ability to design and execute high-level proofs, such as those for Ruan’s and Nekrasov conjectures, demonstrates precision, creativity, and resilience in problem-solving. He is experienced in collaborative research, having successfully engaged in nine international partnerships, and is skilled in guiding students through intricate research problems. His editorial experience adds critical evaluation and peer-review expertise, further enhancing his contribution to the academic community. These combined skills enable him to not only generate original results but also to mentor, lead, and inspire future mathematicians.

Publication Top Notes

  • Title: Multiple Hybrid Phase Transition: Bootstrap Percolation on Complex Networks with Communities
    Authors: C. Wu, S. Ji, R. Zhang, L. Chen, J. Chen, X. Li, Y. Hu
    Year: 2014
    Citations: 25

  • Title: Thermodynamic Limit of Nekrasov Partition Function for 5-Brane Web with O5-Plane
    Authors: X. Li, F. Yagi
    Year: 2021
    Citations: 12

  • Title: Freezing and BPS Jumping
    Authors: SSK Xiaobin Li, Satoshi Nawata, Futoshi Yagi
    Year: 2024
    Citations: 7

  • Title: Ruan’s Conjecture on Singular Symplectic Flops of Mixed Type
    Authors: B. Chen, A. Li, X. Li, G. Zhao
    Year: 2014
    Citations: 6

  • Title: O-Vertex, O7⁺-Plane, and Topological Vertex
    Authors: SSK Xiaobin Li, Futoshi Yagi, Rui-Dong Zhu
    Year: 2024

  • Title: Ruan Cohomologies of the Compactifications of Resolved Orbifold Conifolds
    Authors: S. Du, B. Chen, C.Y. Du, X. Li
    Year: 2016

  • Title: Bootstrap Percolation on Complex Networks with Community Structure
    Authors: W. Chong, L. Xiaobin, Z. Rui, H. Yanqing, J. Shenggong, C. Jiawei, C. Liujun
    Year: 2014

  • Title: A New Gluing Recursive Relation for Linear Sigma Model of ℙ¹-Orbifold
    Authors: X.B. Li, B.H. Chen, C.Y. Du
    Year: 2013

  • Title: An Application of Symplectic Virtual Localization
    Authors: L. Xiaobin
    Year: 2010

Conclusion

Dr. Xiaobin Li stands as an accomplished mathematician whose research, leadership, and international collaborations have advanced the frontiers of symplectic geometry and mathematical physics. His proven ability to resolve complex conjectures, combined with a consistent record of publishing in high-impact journals, demonstrates both depth and influence in his scholarly work. Through his mentoring of students and editorial contributions, he fosters an environment of academic growth and innovation. His memberships in prestigious mathematical societies affirm his global engagement and professional credibility. With a vision for continued exploration and a foundation of rigorous research skills, Dr. Li is poised to make even greater contributions to mathematics, making him a truly deserving nominee for honors such as the Best Researcher Award.

Mojtaba Lashgari | Geometry | Best Researcher Award

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Dr. Mojtaba Lashgari | Geometry | Best Researcher Award

Research fellow at University of Oxford, United Kingdom

Dr. Mojtaba Lashgari is an accomplished researcher in biomedical engineering and computer science, currently serving as a postdoctoral researcher at the University of Oxford. With a PhD from the University of Leeds and a Marie Curie Early-Stage Research Scholarship, his work bridges artificial intelligence, medical image analysis, and computational modeling. Dr. Lashgari has published extensively in top-tier journals such as Medical Image Analysis and IEEE Transactions on Image Processing, focusing on virtual imaging trials, cardiac MRI, and coronary vessel segmentation. He has presented his research at international conferences and played active roles in scientific committees and conference organization. His interdisciplinary expertise, from MRI physics to deep learning, underpins innovative solutions in healthcare technology. Through academic service, teaching, and high-impact collaborations, Dr. Lashgari exemplifies scientific excellence and leadership. His work is contributing to the future of personalized medicine and diagnostic imaging, making him a highly deserving candidate for the Best Researcher Award.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Mojtaba Lashgari’s educational background reflects a strong interdisciplinary foundation in engineering, biomedical sciences, and computational research. He earned his PhD in Computer Science from the University of Leeds in 2023, where he specialized in advanced medical image analysis and virtual imaging trials. Prior to this, he completed a Master of Science in Biomedical Engineering from Isfahan University of Medical Sciences in 2016, graduating as the top-ranked student in his cohort. His academic journey began with a Bachelor of Science in Electrical Engineering from Malek-Ashtar University of Technology in 2013, where he developed a solid base in electronics and signal processing. This unique blend of electrical, biomedical, and computer science education has equipped Dr. Lashgari with the analytical, technical, and problem-solving skills required for high-level research in medical technology and artificial intelligence. His academic achievements have been consistently marked by excellence, innovation, and a clear focus on impactful, real-world applications.

Professional Experience

Dr. Mojtaba Lashgari has accumulated rich and diverse professional experience across leading academic institutions and interdisciplinary research domains. Currently, he serves as a Postdoctoral Researcher in the Department of Engineering Science at the University of Oxford (2023–2026), where he is engaged in pioneering research in medical imaging and AI-driven healthcare solutions. Prior to this, he worked as a part-time Technical Engineer at the Institute of Transport Studies, University of Leeds, contributing to computational modeling projects. His research journey also includes a tenure as a Graduate Researcher at the Medical Image and Signal Processing Research Centre in Isfahan, Iran, where he deepened his expertise in biomedical image analysis. Throughout his career, Dr. Lashgari has been actively involved in teaching, academic service, and organizing scientific events. His roles have consistently demonstrated his capabilities in bridging engineering, medicine, and computational sciences, establishing him as a well-rounded researcher with both technical depth and collaborative breadth.

Research Interest

Dr. Mojtaba Lashgari’s research interests lie at the dynamic intersection of medical imaging, computational modeling, and artificial intelligence. He is particularly passionate about developing innovative solutions for medical image analysis, with a focus on MRI physics, diffusion-weighted imaging, and virtual imaging trials. His work encompasses both model-based and image-based methodologies, integrating techniques such as finite element analysis, inverse problems, and machine and deep learning algorithms to simulate and interpret complex biological systems. A key area of his research involves the creation of patient-specific in-silico models to improve diagnostic accuracy and procedural planning in cardiovascular medicine. Dr. Lashgari is also deeply involved in advancing domain generalization methods for coronary vessel segmentation, aiming to enhance clinical applicability and robustness across diverse imaging environments. His interdisciplinary approach strives to bridge engineering, biomedical science, and data science, contributing significantly to the future of precision medicine and computational healthcare.

Award and Honor

Dr. Mojtaba Lashgari has been recognized with several prestigious awards and honors that underscore his academic excellence and impactful research contributions. He was awarded the esteemed Marie Sklodowska-Curie Early-Stage Research Doctoral Scholarship in 2018, a testament to his potential in cutting-edge scientific innovation at the European level. In 2024, he received a partial scholarship to attend the Virtual Imaging Trial in Medicine (VITM) Summit at Duke University, USA, further highlighting his growing international recognition. His academic brilliance was also evident early in his career when he ranked first in his M.Sc. Biomedical Engineering class at Isfahan University of Medical Sciences in 2016. These honors reflect Dr. Lashgari’s dedication to advancing medical imaging technologies and his leadership within the global research community. His active involvement in scientific committees and organization of high-impact academic events also reinforces his role as an emerging thought leader in biomedical engineering and computational imaging science.

Conclusion

Dr. Mojtaba Lashgari stands out as a highly accomplished and forward-thinking researcher at the intersection of biomedical engineering, computer science, and medical image analysis. With a PhD from the University of Leeds and a current postdoctoral position at the University of Oxford, his academic journey reflects a deep commitment to scientific excellence. His contributions span advanced MRI simulations, deep learning for image segmentation, and virtual imaging trials, underscoring his role in shaping the future of computational medical diagnostics. Recognized with prestigious awards such as the Marie Curie Fellowship and actively engaged in academic leadership, Dr. Lashgari has proven himself a driving force in interdisciplinary research. His impactful publications, teaching roles, and organizational contributions further highlight his versatility and dedication. With a visionary approach to science and a growing international presence, Dr. Lashgari is well-positioned to make lasting contributions to healthcare technology and deserves strong consideration for the Best Researcher Award.

Publications Top Notes

  1. Title: A comparative study of new and current methods for dental micro-CT image denoising
    Authors: M Shahmoradi, M Lashgari, H Rabbani, J Qin, M Swain
    Year: 2016
    Citations: 29
    Source: Dentomaxillofacial Radiology, 45(3), 20150302

  2. Title: Missing surface estimation based on modified Tikhonov regularization: Application for destructed dental tissue
    Authors: M Lashgari, M Shahmoradi, H Rabbani, M Swain
    Year: 2018
    Citations: 16
    Source: IEEE Transactions on Image Processing, 27(5), 2433–2446

  3. Title: A fast and accurate dental micro-CT image denoising based on total variation modeling
    Authors: M Lashgari, H Rabbani, M Shahmorad, M Swain
    Year: 2015
    Citations: 7
    Source: 2015 IEEE Workshop on Signal Processing Systems (SiPS), pp. 1–5

  4. Title: Three-dimensional micro-structurally informed in silico myocardium—Towards virtual imaging trials in cardiac diffusion weighted MRI
    Authors: M Lashgari, N Ravikumar, I Teh, JR Li, DL Buckley, JE Schneider, …
    Year: 2022
    Citations: 4
    Source: Medical Image Analysis, 82, 102592

  5. Title: Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories
    Authors: M Lashgari, RP Choudhury, A Banerjee
    Year: 2024
    Citations: 2
    Source: Frontiers in Cardiovascular Medicine, 11, 1398290

  6. Title: SpinDoctor-IVIM: A virtual imaging framework for intravoxel incoherent motion MRI
    Authors: M Lashgari, Z Yang, MO Bernabeu, JR Li, AF Frangi
    Year: 2025
    Citations: 1
    Source: Medical Image Analysis, 99, 103369

  7. Title: Reconstruction of Connected Digital Lines Based on Constrained Regularization
    Authors: M Lashgari, H Rabbani, G Plonka, I Selesnick
    Year: 2022
    Citations: 1
    Source: IEEE Transactions on Image Processing, 31, 5613–5628

  8. Title: Splitting and Merging for Active Contours: Plug-and-Play
    Authors: M Lashgari, A Banerjee, H Rabbani
    Year: 2025
    Source: Mathematics, 13(6), 991

  9. Title: Virtual Imaging Trial can Unveil the Relationship Between Intravascular Diffusivity and Intravoxel Incoherent Motion in MRI
    Authors: M Lashgari, Z Yang, MO Bernabeu, JR Li, AF Frangi
    Year: 2024
    Source: Proceedings Virtual Imaging Trials in Medicine 2024, 1, 146

  10. Title: An in silico imaging framework for microstructure-sensitive myocardial diffusion-weighted MRI
    Author: M Lashgari
    Year: 2023
    Source: PhD Thesis, University of Leeds

  11. Title: Myocardium numerical phantom at micro-scale: application in MRI simulation
    Authors: M Lashgari, N Ravikumar, I Teh, J Schneider, A Frangi
    Year: 2021
    Source: Book of Abstracts, ESMRMB 2021 Online, 38th Annual Scientific Meeting