The brain is one of the most complex objects in the world. Although our research on the brain has been ongoing for thousands of years, there are still many mysteries about the human brain.
The team hopes to conduct interdisciplinary research and use artificial intelligence technology to help neuroscientists better understand the brain. This understanding may not only aid in exploring the mechanisms of brain diseases and promoting brain health but also provide inspiration from the brain to design smarter artificial intelligence.
To create a synergistic relationship between AI and the brain, Dongsheng Li and his colleagues at Microsoft Research Asia – Shanghai emphasize the need to integrate expertise in both AI and neuroscience. This integration is essential for bridging the gap and uncovering new opportunities. Their research focuses on brain-inspired AI, brain signal decoding brain-computer interfaces, and AI for brain health, all of which hold significant importance for society and humanity.
If you are passionate about the intersection of AI and neuroscience, and eager to use AI to advance brain science while improving AI systems and brain health, we warmly invite you to join the Microsoft Research Asia StarTrack Scholars Program. Applications are now open for the 2025 program. For more details and to submit your registration, visit our official website: Microsoft Research Asia StarTrack Scholars Program – Microsoft Research.
Synergy between AI and the Brain
Brain-inspired AI: Applying the efficient mechanisms of the brain to AI
As AI research and technology continue to advance, it is crucial to consider the energy and infrastructure resources needed to manage large datasets, perform complex computations, and handle open-ended tasks. The human brain serves as an exemplary model of efficiency, adeptly managing intricate tasks with minimal resources. Inspired by this, the team aims to understand the brain’s efficient processes and replicate them in AI.
In collaboration, the team is exploring three research directions to foster more sustainable AI. First, leveraging the energy-efficient spiking neurons in the brain could make computational mechanisms in artificial neural networks up to three orders of magnitude more efficient. Second, designing new neural network architectures that mimic the brain’s learning and computational methods could enhance learning efficiency. Third, embodied AI, when interacting with the real world, can draw from the human brain’s strategies to operate efficiently and effectively in open-ended environments and goals.
Brain signal decoding Brain-computer interface: Promote EEG decoding of brain signals
Understanding how the brain works is crucial for addressing the fundamental scientific question of the origin of intelligence, as well as developing next-generation brain-computer interfaces (BCI). Electroencephalogram (EEG) signals are among the most popular tools for studying the brain with non-invasive electrodes because of its convenience and reasonable quality for decoding brain states including both what people sense (perception) and what people want (control).
However, decoding brain signals with non-invasive EEG is a challenging task because of the lack of data and neuroscience guarantees. To address these challenges, the first promising research direction is to build the foundation models for understanding EEG signals, e.g., self-supervised learning on EEG signals or multi-modal learning between EEG and human language, by leveraging large-scale unlabeled EEG data. The other promising direction is to combine neuroscience knowledge in machine learning algorithm design, e.g., designing more bio-plausible decoding algorithms or BCI decoding paradigms.
AI for brain health: Advancing the understanding of brain diseases
AI can help conquer brain disorders in several ways, including diagnostics and mechanism understanding.
In diagnostics, machine learning algorithms can analyze complex medical data, such as EEG signals, genetic information, and MRI scans, with remarkable accuracy and speed, enabling earlier and more precise identification of brain disorders.
For mechanism understanding, AI can sift through vast amounts of research data to uncover patterns and insights that may not be immediately apparent to human researchers, thereby advancing our knowledge of the underlying causes and progression of neurological diseases.
Cross-disciplinary Collaboration: Partnering with StarTrack Scholars to Unlock Infinite Possibilities
Collaborations between AI researchers and neuroscience experts offer tremendous potential, yet they also pose significant challenges.
Data quality and availability are major hurdles. High-quality, standardized, and sufficiently large datasets are essential for training AI models, but such datasets are often difficult to obtain in neuroscience.
Brain data is highly complex and variable. AI models need to be able to handle the intricacies of neural data, such as high dimensionality, noise, and non-linear relationships. Also, neuroscience often involves multimodal data, including imaging, electrophysiological recordings, and behavioral data. Integrating these diverse data types into a coherent AI model is challenging.
AI models, especially deep learning models, are often seen as “black boxes.” Ensuring that these models provide interpretable and actionable insights for neuroscientists and clinicians is a significant challenge.
To tackle these challenges, Microsoft Research Asia launched the StarTrack Program, championing cross-disciplinary dialogue and joint experimentation to drive breakthroughs in scientific frontiers.
Jiangchao Yao: Revolutionizing Non-Invasive Treatment for Alzheimer’s Disease
In 2025, Dr. Jiangchao Yao, Assistant professor from Shanghai Jiao Tong University, joined the StarTrack Program and embarked on an in-depth collaboration with Principal Researcher Dongsheng Li’s team at Microsoft Research Asia. Their work focused on the intersection of AI and brain science—medical AI, with a particular emphasis on non-invasive treatment for Alzheimer’s disease.
Dr. Yao’s expertise in machine learning complemented perfectly with Dongsheng Li’s extensive experience in brain science and medical AI. Supported by MSRA researchers Dr. Xinyang Jiang, Dr. Zilong Wang, and interns, the team shared experimental code and datasets, propelling the project forward with remarkable efficiency.
Dr. Yao reflects: “Our bi-weekly discussions were true brainstorming marathons, igniting countless sparks of inspiration. Their professional insights were invaluable to someone like me, newly venturing into medical AI. Every team member was incredibly kind, and the collaborative atmosphere was simply outstanding!”
The partnership centered on optimizing Temporal Interference (TI) technology—a non-invasive treatment that stimulates the cerebral cortex using high-frequency electromagnetic waves, dramatically lowering both cost and risk in Alzheimer’s therapy. Yet TI struggles with precise target localization. To overcome this, the team proposed dynamically optimizing stimulation targets by analyzing inter-regional cortical correlations. Validated by medical experts, this innovative approach demonstrates immense potential and is poised to mark a pivotal advancement in TI applications—underscoring the transformative power of interdisciplinary collaboration.
Through the StarTrack Program, Dr. Yao leveraged MSRA’s global platform to connect with leading researchers and international scholars. Actively engaging in events such as the StarTrack Scholar Seminar and invited talks, he deepened his expertise in AI system optimization and medical applications. On MSRA’s research environment, he remarks: “MSRA’s global vision truly broadened my horizons. With frequent lectures by world-class scholars, the international atmosphere reinforced my commitment to global collaboration.”
To young scholars applying for the 2026 StarTrack Program, Dr. Yao advises:
“Seize this opportunity without hesitation. MSRA is a world-class platform where professional, supportive researchers will amplify your work on the global stage.”
He emphasizes that StarTrack is more than an academic springboard—it is a gateway for emerging scholars to achieve international impact and drive cross-disciplinary innovation.
Weilong Zheng: Breakthrough Progress in EEG Signal Decoding
Associate Professor Weilong Zheng from Shanghai Jiao Tong University has long pursued interdisciplinary research bridging computer science, brain science, and clinical medicine. A question that has lingered in his mind: “When someone admires an oil painting, can we reconstruct the image they see from their brain electrical signals?” Deeply concerned for the nearly 50 million depression patients in China, he wonders: “Can brain-computer interfaces transform depression diagnosis and treatment? By quantifying visual cognitive differences between patients and healthy individuals, can we gain deeper insight into this community?”
Seeking answers, Prof. Zheng joined the StarTrack Program upon its 2022 application launch, visiting Microsoft Research Asia as a StarTrack Scholar to collaborate with the Shanghai lab team.
In this partnership, Prof. Zheng contributed specialized knowledge in EEG signal processing, while the team excelled in machine learning algorithm design and optimization—forming a synergy of complementary strengths to conquer complex challenges.
This cross-disciplinary collaboration yielded groundbreaking results: In 2023, the team introduced NeuroImagen, outperforming state-of-the-art methods in EEG-driven visual image reconstruction across semantic accuracy, image quality, and structural consistency. In 2024, they unveiled EEG2Video, achieving a world-first in decoding dynamic human visual input from EEG signals—pushing the frontiers of EEG decoding research.
These advancements continue to propel breakthroughs in reconstructing visual information from EEG signals, vividly illustrating the transformative potential of AI-brain science synergy.
For Prof. Zheng, the StarTrack experience at Microsoft Research Asia opened a vibrant platform for open collaboration and exchange. It not only expanded his research vision but also connected him with scholars from diverse backgrounds and regions, enabling him to collaborate with like-minded peers in service of society.
The interdisciplinary frontier between AI and brain science is vast and brimming with promise. Deeper exploration in this domain is poised to deliver disruptive breakthroughs, fundamentally reshaping industries. The fusion of these fields will unlock new horizons in human cognition and capability while accelerating progress in AI, healthcare, and beyond.
The 2026 Microsoft Research Asia StarTrack Program extends its most open invitation to outstanding scholars worldwide: Join us in forging collaborations, co-exploring synergistic innovation between AI and brain science, and become a shining star in this journey of transformation!
Microsoft Research Asia StarTrack Scholars advocates an open attitude, encouraging dialogue and joint experimentation with researchers from various disciplines to discover viable solutions. Now visit our official website to know more: Microsoft Research Asia StarTrack Scholars Program – Microsoft Research
Theam Team
- Dongsheng Li, Principal Research Manager, Microsoft Research Asia
- Yansen Wang, Senior Researcher, Microsoft Research Asia
- Dongqi Han, Senior Researcher, Microsoft Research Asia
- Mingqing Xiao, Senior Researcher, Microsoft Research Asia
If you have any questions, please email Ms. Yanxuan Wu, program manager of the Microsoft Research Asia StarTrack Scholars Program, at v-yanxuanwu@microsoft.com
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