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Applications are now open from November 1, 2024, to December 31, 2024. We welcome your submission.
Application
- Click the Registration Link (opens in new tab) to submit your registration information.
- Download the StarTrack Scholars Program Application Form.docx, along with the Letter of Recommendation.docx and Letter of Institutional Endorsement.docx templates. Utilize the form and templates to provide formal application details, then forward them via email to Yanxuan Wu at v-yanxuanwu@microsoft.com.
If you have any questions, please email Ms. Yanxuan Wu, program manager of the Microsoft Research Asia StarTrack Scholars, at v-yanxuanwu@microsoft.com.
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We are delighted to unveil the results of the esteemed MSR Asia StarTrack Scholars 2024 program.
Foremost, we express our sincere appreciation to all applicants who showcased remarkable dedication and passion in advancing research within their respective fields. Your contributions have significantly enriched our selection process, highlighting the depth of talent and innovation present within our global research community.
From a wealth of highly valuable proposals, we meticulously identified those that closely align with the focal collaborative research themes of this year’s program, encompassing Societal AI, Media Foundation, and Sustainability. Additionally, we selected projects that resonate with key research areas within our labs, including AI-Driven Advancement in System and Infrastructure, Embodied AI, Large Language Models, and Healthcare.
Following thorough review and evaluation, we are delighted to announce the selection of 17 exceptional scholars, listed below:
Name University Project Xu Chen Renmin University of China Social Simulation with Humanoid Large Language Models Weiran Huang Shanghai Jiao Tong University LLM Evaluation Based on Matrix Entropy Linus Huang Hong Kong University of Science and Technology Dynamic Value Alignment: Enhancing Ethical AI through User-Centric Adaptability Qi Mao Communication University of China Neural Codecs-Generative and Cross-modal Compression Xixin Wu The Chinese University of Hong Kong Multimodal Large Language Model based on Shared Space Renhe Jiang The University of Tokyo Uncertainty-Aware Machine Learning Models for Spatiotemporal Forecasting Cheng Tan Northeastern University Ensuring Correctness and Reliability of Large-scale Distributed Training and Inference in the LLM Era Luo Mai University of Edinburgh Exploring Next-Generation AI Accelerator System Stack Xiangyu Xu Xi’an Jiao Tong University Large Foundation Model for 3D Human Pose Estimation Ye Pan Shanghai Jiao Tong University Stylized 3D avater generation and real time animation Xiaohong Liu Shanghai Jiao Tong University Multi-Modal Reconstruction and Quality Assessment for Neuroimaging Hao Wu Nanjing University Synergistic Edge Intelligence Based on Retrieval-Enhanced Large Language Models Yujiang Wang Oxford Suzhou Centre for Advanced Research ICU-LLM: A Multi-modal Large Language Model for Understanding Structured and Unstructured Medical Records in Intensive Care Units Xie Chen Shanghai Jiao Tong University Multitask-oriented Speech Large Model Research Danfeng Shan Xi’an Jiaotong University Efficient network buffer management scheme for large-scale AI clusters Xingyu Gao Chinese Academy of Sciences Multimodal Perception and Embodied Intelligence Jian Li Institute of Information Engineering, Chinese Academy of Sciences Lightweight Large Language Models for Complex Reasoning Tasks