People / Students / Class of 2027
Xinyan (Amanda) Ge graduated from NYU Shanghai with a dual degree in Computer Science and Mathematics, where she built a strong foundation in machine learning, statistics, and mathematical modeling. She was recognized as an NYU Shanghai Honors Scholar for her academic excellence throughout her undergraduate studies. Her coursework and research experience equipped her with proficiency in Python, SQL, PyTorch, and modern machine learning frameworks, enabling her to conduct research in natural language processing, large language models, and graph-based machine learning.
Her research has focused on soft prompt tuning for large language models, exploring methods to improve controllable text generation for tasks such as question generation. During her research at HKUST, she developed an LLM-based text classification pipeline for large-scale datasets, gaining hands-on experience with model fine-tuning and data-centric AI workflows. In addition to her research, Amanda applied machine learning in industry through internships in AI and consulting, where she built NLP pipelines, explored AI agents and prompt engineering, and developed OCR- and text classification-based solutions for real-world business applications.
At Northwestern, Amanda looks forward to deepening her expertise in machine learning and AI systems while collaborating with peers from diverse backgrounds. She is particularly interested in building reliable and scalable AI solutions that bridge cutting-edge research with real-world impact. Outside of academics, Amanda enjoys photography, traveling, and staying active through sports.
