About Me
👋 Welcome to My Academic Homepage
Exploring the Frontiers of Artificial Intelligence
🎯 Personal Introduction
Hello! I'm Mingyang Gao, a passionate student and researcher in the field of artificial intelligence and computer science. I am a 2022 undergraduate student majoring in Artificial Intelligence at the School of Intelligence Science and Technology, University of Science and Technology Beijing (USTB), supervised by Prof. Wei He. Since September 2024, I have been conducting research internship at the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, under the guidance of Associate Researcher Xiaomei Zhang.
🎓 Education
University of Science and Technology Beijing
- Bachelor of Artificial Intelligence
- School of Intelligence Science and Technology
- Expected Graduation: 2026
🔬 Research Interests
My research interests span across several exciting areas in artificial intelligence:
👁️ Computer Vision
Image processing, object detection, visual understanding systems, and computer vision applications
🔄 Multimodal Learning
Integrating and processing information from multiple modalities (vision, language) for comprehensive understanding
🤖 Large Language Models
Research on foundation models, prompt engineering, and large-scale language model applications
🧠 Artificial Intelligence
Machine learning algorithms, neural networks, deep learning architectures, and AI system development
💻 Technical Skills
🖥️ Programming Languages
C, C++, Python, Markdown
🧠 Machine Learning
PyTorch, Scikit-learn
📊 Data Analysis
Pandas, NumPy, Matplotlib
🛠️ Tools & Platforms
Git, Linux, Latex
🎯 Current Focus
I am currently focused on preparing for graduate school applications while conducting research on multimodal facial age estimation. My research builds upon MaPLe (a follow-up work of CLIP) to leverage the rich semantic information in Visual-Language Models (VLMs) for downstream tasks like facial age estimation. I introduce cross-modal information fusion mechanisms and external knowledge (LLMs) guided reasoning to explore the applications of VLMs in facial age estimation.
🤝 Feel Free to Connect Me!
I'm always interested in collaborating on interesting projects and research opportunities. Feel free to reach out if you'd like to discuss potential collaborations or have any questions about my work!