Mr. Mengqi Lei | Medical Image Analysis | Best Researcher Award
Mr. Mengqi Lei | Medical Image Analysis – PhD Student at Tsinghua Univeristy, China
Mengqi Lei is a forward-looking and exceptionally talented early-career researcher whose contributions to artificial intelligence and computer vision are already drawing attention at an international level. Despite being at a formative stage of his academic journey, his work exhibits both depth and interdisciplinary impact, especially in fields like medical image analysis and hypergraph neural networks. His evolving academic record and consistent research output mark him as a standout figure among his peers and a fitting nominee for the Best Researcher Award.
🧾Academic Profile
ORCID | Google Scholar
🎓 Education
Mengqi Lei began his undergraduate education at the China University of Geosciences in Wuhan in 2021, where he focused on computer science foundations, machine learning, and applied algorithms. His academic rigor and innovative research led to his acceptance into the highly competitive Ph.D. program at Tsinghua University, Beijing, commencing in 2025. This transition to one of Asia’s most prestigious academic institutions is not only a testament to his intellectual capability but also reflects his commitment to pushing the frontiers of artificial intelligence and its applications in complex domains.
💼 Research Experience
Though still at an early stage in his career, Mengqi has amassed a considerable portfolio of research contributions. His experience involves collaboration with multi-disciplinary teams tackling challenges in medical image segmentation, crowd counting, brain disease diagnostics, and remote-sensing object detection. He has actively contributed to projects leveraging deep learning, contrastive learning, self-supervision, and graph neural networks. These experiences have not only honed his technical skills in algorithm development and model evaluation but also enriched his perspective on real-world applications of AI technologies.
🔬 Research Interests
Mengqi Lei’s research interests lie at the intersection of artificial intelligence, computer vision, and medical imaging. His work aims to enhance visual recognition systems by developing frameworks that are both computationally efficient and semantically powerful. Specifically, he has explored contrast-driven feature enhancement for medical segmentation, soft hypergraph structures for general visual tasks, and advanced neural architectures for density-aware crowd counting. With a strong focus on healthcare technology, he aims to bridge the gap between AI innovation and clinical utility, especially in diagnostics and public health.
🏆 Awards and Recognitions
While still early in his academic progression, Mengqi’s work has been recognized through publication in top-tier international conferences and journals, a strong indicator of peer validation and scientific merit. His upcoming enrollment in the doctoral program at Tsinghua University is itself a form of academic distinction. Additionally, his ability to publish in competitive venues such as AAAI and ICLR illustrates his potential to become a leading researcher in artificial intelligence in the years to come.
📚 Selected Publications
🧠 “CondSeg: A General Medical Image Segmentation Framework via Contrast-Driven Feature Enhancement” – AAAI Conference on Artificial Intelligence, 2025. [Cited by 3 articles]
🧩 “Hypergraph-Based Semantic and Topological Self-Supervised Learning for Brain Disease Diagnosis” – Pattern Recognition, 2025. [Cited by 2 articles]
🔄 “Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs” – ICLR, 2024. [Cited by 5 articles]
👥 “DDRANet: A Dynamic Density-Region-Aware Network for Crowd Counting” – IEEE Signal Processing Letters, 2024. [Cited by 4 articles]
🛰️ “SOLO-Net: A Sparser but Wiser Method for Small Object Detection in Remote-Sensing Images” – IEEE Geoscience and Remote Sensing Letters, 2023. [Cited by 3 articles]
🧬 “SoftHGNN: Soft Hypergraph Neural Networks for General Visual Recognition” – arXiv preprint, 2025. [Cited by 1 article]
💉 “EPPS: Advanced Polyp Segmentation via Edge Information Injection and Selective Feature Decoupling” – arXiv preprint, 2024. [Cited by 2 articles]
🧾 Conclusion
Mengqi Lei represents a rare blend of technical sophistication, academic maturity, and visionary thinking. His early achievements in computer vision and medical image analysis not only display his potential for groundbreaking discoveries but also his dedication to research that can make a tangible impact on society. As he steps into his doctoral studies at one of the world’s top research institutions, Mengqi stands out as a future leader in artificial intelligence. Honoring him with the Best Researcher Award at this stage would not only recognize his current excellence but also empower a trajectory destined for meaningful scientific contribution.
