Shumao Xu | Neurotechnology | Best Researcher Award

Published on by Neuroscientists

Assoc. Prof. Dr. Shumao Xu | Neurotechnology | Best Researcher Award

Assoc. Prof. Dr.  Shumao Xu, Fudan University, China.

Shumao Xu’s career embodies a fusion of material science, biomedical engineering, and neurotechnology, leading to remarkable advancements in neural interfaces and brain-computer interaction. His extensive research, industry collaborations, and prestigious funding awards highlight his influence in the field. With over 60 high-impact publications and thousands of citations, his work has significantly contributed to neuroengineering, setting the foundation for future innovations.

Profile

Orcid

✨ Early Academic Pursuits

Shumao Xu’s journey in academia began with a passion for innovation and exploration in neural interfaces and biomedical engineering. He pursued his Ph.D. at Shanghai Jiao Tong University (SJTU), where he laid the foundation for his research in neural engineering. His early academic years were marked by rigorous studies in material science, bioelectronics, and neurotechnology, setting the stage for his groundbreaking work in neural interfaces. His commitment to excellence led him to postdoctoral training at the prestigious Max Planck Institute for Solid-State Research as an Alexander von Humboldt scholar, followed by further research at Pennsylvania State University and UCLA.

👨‍🎓 Professional Endeavors

Currently an Associate Professor and Principal Investigator at Fudan University’s Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Shumao Xu is recognized as a National Overseas Young Talent (2024). His professional trajectory has been defined by his commitment to advancing brain-computer interfaces and neurotechnology. Securing funding from prestigious organizations such as the National Natural Science Foundation of China (NSFC), China Postdoctoral Science Foundation (Innovative Program), and the Shanghai Super Postdoctoral Program, he has spearheaded research that pushes the boundaries of neural engineering.

🧠 Contributions and Research Focus

Shumao Xu has dedicated his research to developing state-of-the-art neural interfaces that revolutionize neurostimulation and brain-computer interactions. His pioneering work includes implantable neural electrodes, non-invasive deep brain stimulation, calcium imaging, and non-genetic optoelectronic neural interfaces. His research extends to the development of soft magnetoelastic energy harvesters, injectable fluorescent neural probes, and triboelectric neurostimulators for self-powered neural systems. His work is crucial in creating biocompatible and energy-efficient neurotechnologies that have the potential to treat neurodegenerative diseases and enhance brain function.

🏆 Accolades and Recognition

With over 60 high-impact publications in renowned journals such as Advanced Materials, Nature Communications, Nano Letters, Matter, and Chem, Shumao Xu has established himself as a leading researcher in neurotechnology. His impressive h-index of 28 and more than 3,300 citations stand as a testament to the significance of his contributions. He has been honored with funding from the NSFC Oversea Young Talent program for his work on injectable fluorescent neural probes and received the Humboldt Foundation’s support for optoelectronic neural modulation. His research has gained international recognition, earning him industry collaborations and consultancy projects.

⚛️ Impact and Influence

Beyond academia, Shumao Xu’s work has practical applications in the medical and technological sectors. His collaborations with leading industry giants, such as Showa Denko and Teijin in Tokyo, Japan, have translated his academic innovations into real-world applications. His research in neural interfaces and brain-computer technologies has the potential to revolutionize treatments for neurological disorders, offering new hope to patients with neurodegenerative diseases. His advancements in self-powered neural stimulation systems have paved the way for sustainable and long-lasting neurotechnologies.

💡 Legacy and Future Contributions

As a visionary in neuroengineering, Shumao Xu continues to shape the future of brain-computer interfaces and neural modulation. His work is not only contributing to academic advancements but also influencing the next generation of researchers and engineers in neurotechnology. His ongoing research projects, including biocompatible neural electrodes and optoelectronic neural modulation, promise to drive innovation in the field. Through his relentless pursuit of scientific breakthroughs, he aims to bridge the gap between neuroscience and technology, ultimately transforming the landscape of brain-computer interaction and neurotherapy.

Publication

  • Artificial intelligence assisted nanogenerator applications

    • Authors: Shumao Xu, Farid Manshaii, Xiao Xiao, Jun Chen

    • Year: 2025

 

  • Advances in 2D materials for wearable biomonitoring

    • Authors: Songyue Chen, Shumao Xu, Xiujun Fan, Xiao Xiao, Zhaoqi Duan, Xun Zhao, Guorui Chen, Yihao Zhou, Jun Chen

    • Year: 2025

 

  • A comprehensive review on the mechanism of contact electrification

    • Authors: J Tian, Y He, F Li, W Peng, Y He, Shumao Xu, F Manshaii, X Xiao, Jun Chen

    • Year: 2025

 

  • Advances in Brain Computer Interface for Amyotrophic Lateral Sclerosis Communication

    • Authors: Yuchun Wang, Yurui Tang, Qianfeng Wang, Minyan Ge, Jinling Wang, Xinyi Cui, Nianhong Wang, Zhijun Bao, Shugeng Chen, Jing Wang et al.

    • Year: 2025

 

  • Tailored Terminal Groups in MXenes for Fast-Charging and Safe Energy Storage

    • Authors: Shumao Xu, Minyan Ge, Weiqiang Zhang, Yuchun Wang, Yurui Tang

    • Year: 2025

 

  • Heart-brain connection: How can heartbeats shape our minds?

    • Authors: Xu Shumao, Scott Kamryn, Manshaii Farid, Chen Jun

    • Year: 2024

  • Injectable Fluorescent Neural Interfaces for Cell-Specific Stimulating and Imaging

    • Authors: Xu Shumao, Xiao Xiao, Manshaii Farid, Chen Jun

    • Year: 2024

 

  • Multiphasic interfaces enabled aero-elastic capacitive pressure sensors

    • Authors: Xu Shumao, Manshaii Farid, Chen Jun

    • Year: 2024

 

  • Reversible metal-ligand coordination for photocontrolled metallopolymer adhesives

    • Authors: Xu Shumao, Manshaii Farid, Chen Guorui, Chen Jun

    • Year: 2024

 

  • Self-Thermal Management in Filtered Selenium-Terminated MXene Films for Flexible Safe Batteries

    • Authors: Pang Xin, Lee Hyunjin, Rong Jingzhi, Zhu Qiaoyu, Xu Shumao

    • Year: 2024

 

🌟 Conclusion

Shumao Xu’s pioneering research and dedication to neural engineering continue to push the boundaries of brain-inspired intelligence and medical advancements. His visionary contributions have paved the way for next-generation neurotechnologies that hold the potential to transform neurological treatments and human-computer interactions. As he continues his groundbreaking research, his legacy will inspire future scientists and engineers, driving forward the possibilities of neurotechnology for years to come.

Xiaobing Yan | Neurotechnology | Best Researcher Award

Published on by Neuroscientists

Prof. Xiaobing Yan | Neurotechnology | Best Researcher Award

Prof. Xiaobing Yan, Hebei University, China.

Professor Xiaobing Yan is a distinguished researcher specializing in novel memory devices and memristor-based brain-inspired chip technologies. As a Senior Member of IEEE and a reviewer for leading journals, he has made significant contributions to the field of neuromorphic engineering. His outstanding achievements include recognition as a Young Changjiang Scholar and a Young Top-notch Talent under China’s National Ten Thousand Talents Program. With over 120 high-impact publications, 5,600+ citations, and an H-index of 40, he is globally recognized among the top 2% of scientists. His research has been supported by several prestigious national and provincial funding programs.

Profile

Scopus

🎓 Early Academic Pursuits

Xiaobing Yan embarked on his academic journey with a deep passion for electronics and information engineering. His early years were marked by an unwavering dedication to understanding the complexities of memory devices and neuromorphic systems. As he progressed through his studies, his curiosity and drive led him to explore the intersection of artificial intelligence and hardware development. His rigorous academic training laid a solid foundation for his future contributions to next-generation computing technologies.

💪 Professional Endeavors

Currently serving as a Professor at the Institute of Life Science and Green Development, Hebei University, Xiaobing Yan has established himself as a distinguished leader in the field of electronic engineering. He is a Doctoral Supervisor and a Senior Member of IEEE, a testament to his vast expertise and influence in the scientific community. His role extends beyond academia, as he actively engages in national-level research programs and collaborates with top-tier research institutions. His professional journey is a testament to his commitment to pioneering advancements in neuromorphic computing and memristor-based brain-inspired chip technologies.

🤖 Contributions and Research Focus

Xiaobing Yan’s research primarily revolves around novel memory devices and brain-like computing systems. His work has been instrumental in the advancement of memristor-based chip technologies, which hold the potential to revolutionize artificial intelligence hardware. By bridging the gap between neuroscience and semiconductor innovation, he is contributing to the development of energy-efficient, high-performance computing architectures. His research projects, funded by prestigious national programs, aim to push the boundaries of nanoelectronics and intelligent systems.

🏆 Accolades and Recognition

Xiaobing Yan’s groundbreaking work has earned him widespread recognition. In 2019, he was honored as a Young Changjiang Scholar by the Ministry of Education and selected as a Young Top-notch Talent under the National Ten Thousand Talents Program. In 2024, he further cemented his legacy by winning the Excellence Award at the National Disruptive Innovation Technology Competition. His contributions are not only recognized in China but also on a global scale, as he has been listed among the top 2% of scientists worldwide by Stanford University.

🌟 Impact and Influence

With over 120 high-impact publications and more than 5,600 citations, Xiaobing Yan’s research has significantly shaped the field of electronics and artificial intelligence. His H-index of 40 reflects the depth and relevance of his contributions. As a reviewer for prestigious journals such as Nature Electronics, Advanced Materials, and ACS Nano, he plays a crucial role in shaping the direction of cutting-edge research. His influence extends beyond his publications, as he mentors young researchers and fosters collaborations that drive innovation in neuromorphic computing.

🚀 Legacy and Future Contributions

As a leader in disruptive technology and nanoelectronics, Xiaobing Yan is poised to continue pushing the boundaries of scientific discovery. His ongoing research projects, including multiple National Key R&D initiatives and collaborations with leading institutions, demonstrate his commitment to pioneering breakthroughs in brain-inspired computing. With his vision and expertise, he is set to leave a lasting legacy in the development of next-generation intelligent systems, shaping the future of artificial intelligence and semiconductor technology.

Publication

  1. In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

    • Authors: H. Lin, Haipeng; J. Ou, Jiali; Z. Fan, Zhen; X. Gao, Xingsen; J. Liu, Junming
    • Year: 2025

 

  1. Ultra robust negative differential resistance memristor for hardware neuron circuit implementation

    • Authors: Y. Pei, Yifei; B. Yang, Biao; X. Zhang, Xumeng; S. Li, Shushen; X. Yan, Xiaobing
    • Year: 2025

 

  1. Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models

    • Authors: W. Yue, Wenshuo; K. Wu, Kai; Z. Li, Zhiyuan; R. Huang, Ru; Y. Yang, Yuchao
    • Year: 2025

 

  1. Memristor-based feature learning for pattern classification

    • Authors: T. Shi, Tuo; L. Gao, Lili; Y. Tian, Yang; X. Yan, Xiaobing; Q. Liu, Qi
    • Year: 2025

 

  1. Harnessing spatiotemporal transformation in magnetic domains for nonvolatile physical reservoir computing

    • Authors: J. Zhou, Jing; J. Xu, Jikang; L. Huang, Lisen; X. Yan, Xiaobing; S.T. Lim, Sze Ter
    • Year: 2025

 

  1. Flexoelectric Effect in Thin Films: Theory and Applications

    • Authors: X. Jia, Xiaotong; R. Guo, Rui; J. Chen, Jingsheng; X. Yan, Xiaobing
    • Year: 2025

 

  1. Deoxyribonucleic acid brick crystals-based memristor as an artificial synapse for neuromorphic computing

    • Authors: Z. Wang, Zhongrong; X. Liu, Xinran; J. Li, Jiahang; J. Lou, Jianzhong; X. Yan, Xiaobing
    • Year: 2025

 

  1. Weighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors

    • Authors: Z. Guo, Zhenqiang; G. Duan, Guojun; Y. Zhang, Yinxing; Y. Faraj, Yousef; X. Yan, Xiaobing
    • Year: 2025

 

  1. Achieving over 10 % efficiency in kesterite solar cells via selenium-free annealing

    • Authors: Q. Zhou, Qing; Y. Cong, Yijia; H. Li, Hao; Y. Sun, Yali; W. Yu, Wei
    • Year: 2024

 

  1. Hardware implementation of memristor-based artificial neural networks

  • Authors: F.L. Aguirre, Fernando L.; A. Sebastian, Abu; M. Le Gallo, Manuel; S. Matias Pazos, Sebastian; M. Lanza, Mario
  • Year: 2024

 

Conclusion

Professor Yan’s work plays a pivotal role in advancing memory technology and brain-inspired computing. His extensive research contributions and leadership in high-impact projects underscore his expertise in developing next-generation computing technologies. His global recognition and numerous accolades highlight his influence in the field, positioning him as a key figure in neuromorphic engineering and memory device innovation.

 

 

Saba Hesaraki | Neurotechnology | Best Researcher Award

Published on by Neuroscientists

Ms. Saba Hesaraki | Neurotechnology | Best Researcher Award

Ms. Saba Hesaraki,  Islamic Azad University science and research branch, Iran.

Saba Hesaraki is a computer engineer specializing in artificial intelligence (AI), particularly in medical imaging and generative AI. She holds a Master’s degree in Computer Engineering from Islamic Azad University, Science and Research Branch, Tehran, where her thesis focused on breast cancer image segmentation using an improved 3D U-Net++ model. She has a strong academic background with high GPAs in both her bachelor’s and master’s programs.

Profile

Google Scholar

🌱 Early Academic Pursuits

Saba Hesaraki embarked on her academic journey with a deep passion for computer engineering, earning her Bachelor of Science in Software Engineering from Islamic Azad University, West Tehran Branch. With an outstanding GPA of 17.22 out of 20.0, she demonstrated an early inclination toward problem-solving and artificial intelligence. Her intellectual curiosity and commitment to innovation led her to pursue a Master’s degree in the same domain at Islamic Azad University, Science and Research Branch, Tehran. Her thesis, titled “Segmentation of Breast Cancer Images Using Improved 3D U-Net++ Model,” under the supervision of Dr. Maryam Rastgarpour, showcases her dedication to advancing medical imaging technologies through AI-driven solutions. With an exceptional GPA of 18.12 out of 20.0, her academic excellence laid the foundation for a remarkable research career.

💼 Professional Endeavors

Saba’s professional journey reflects her deep expertise in artificial intelligence, particularly in the realms of generative AI and medical imaging. She has worked remotely in various esteemed organizations, contributing her skills to groundbreaking AI projects. Her role as a Generative AI Engineer at Care Vox in Mountain View, California, and Nexus in San Jose, California, enabled her to develop innovative AI-driven solutions. Prior to this, she made significant contributions as a Computer Vision Engineer at Koga Studio and the Quantitative MR Imaging and Spectroscopy Group in Tehran. Her engagement as an NLP Researcher at Asr Gooyesh Pardaz further showcases her versatility in the field of AI. Through these roles, she has gained profound experience in AI-based medical diagnostics, image segmentation, and sustainable AI development, paving the way for impactful innovations.

📚 Contributions and Research Focus

As a dedicated researcher, Saba’s work has revolved around the intersection of AI and healthcare, particularly medical image segmentation and generative AI applications. Her research interests extend to AI-driven personalized medicine and sustainable AI solutions. She has co-authored multiple research papers, including “Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter” and “UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation.” Her work reflects a keen interest in leveraging AI to solve complex medical challenges, from cancer detection to mental health analysis. Her research on classifying 3D point cloud objects using hybrid neural networks also highlights her multidisciplinary expertise.

🏆 Accolades and Recognition

Saba’s dedication to AI research has been recognized through her academic achievements and professional contributions. Her IELTS score of 7.5 and GRE score of 332 underscore her strong analytical and communication skills, essential for global collaboration in AI research. Her research papers have been under review and submission in reputable scientific journals, further solidifying her presence in the AI and medical imaging research community. The recognition she has garnered through collaborations and innovative contributions establishes her as an influential figure in AI-driven healthcare solutions.

🌍 Impact and Influence

Saba’s work extends beyond research, as she actively contributes to the global AI community by developing cutting-edge AI applications for real-world problems. Her role in AI for sustainable development and AI-driven personalized medicine signifies her commitment to leveraging technology for societal benefit. Her experience in deep learning frameworks like PyTorch and Keras, along with her expertise in machine learning algorithms, has allowed her to shape AI-driven healthcare innovations that have the potential to save lives and enhance medical diagnostics. Through collaborations and mentorship, she inspires the next generation of AI researchers to push the boundaries of technological advancements.

🚀 Legacy and Future Contributions

As an AI researcher and engineer, Saba continues to drive innovation in medical imaging and generative AI. Her aspirations include advancing AI methodologies for early disease detection, improving healthcare accessibility through AI-driven solutions, and fostering AI applications in sustainable development. Her ability to blend technical expertise with a deep understanding of healthcare challenges positions her as a leader in the field. With a promising future ahead, she remains dedicated to exploring new AI frontiers that will revolutionize medical imaging, AI ethics, and beyond.

Publication

Title: A Comprehensive Analysis on Machine Learning based Methods for Lung Cancer Level Classification
Authors: S. Farshchiha, S. Asoudeh, M.S. Kuhshuri, M. Eisaeid, M. Azadie, S. Hesaraki
Year: 2025

Title: Breast Cancer Ultrasound Image Segmentation Using Improved 3D Unet++
Authors: S. Hesaraki, A.S. Mohammed, M. Eisaei, R. Mousa
Year: 2025

Title: BERTCaps: BERT Capsule for Persian Multi-Domain Sentiment Analysis
Authors: M. Memari, S.M. Nejad, A.P. Rabiei, M. Eisaei, S. Hesaraki
Year: 2024

Title: UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation
Authors: S. Hesaraki, M. Akbari, R. Mousa
Year: 2024

Title: Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid Approach
Authors: R. Mousa, M. Khezli, M. Azadi, V. Nikoofard, S. Hesaraki
Year: 2024

Title: CapsF: Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter
Authors: M.A. Dadgostarnia, R. Mousa, S. Hesaraki
Year: 2024

Conclusion

Saba Hesaraki is a highly skilled and motivated AI engineer with a strong academic and research background in medical imaging and generative AI. Her experience across various AI-driven projects, coupled with technical expertise in deep learning and computer vision, positions her as a valuable contributor to the field. With multiple publications and collaborations in AI and machine learning, she continues to make significant advancements in healthcare applications using AI.