Hi! 👋🏻 I’m Yuxuan (Leo) Lu, a Ph.D. student at Northeastern University. Before that, I got my B.E. in Computer Science and Technology and Graduated with honor at Beijing University of Technology. I’m advised by Prof. Dakuo Wang. My research interest includes Human Computer Interaction and Natural Language Processing , especially in training, running and utilizing Large Language Models (LLMs) effiently and effectively. In the past, I’ve worked as Machine Learning Researcher at a joint program between LinkedIn and Microsoft Research Asia. I’ve also worked as an intern research assistant at THUNLP lab, supervised by Prof. Zhiyuan Liu(刘知远).
I’m currently persuing my Ph.D. in Computer Science at Khoury College of Computer Sciences, Northeastern University, advised by Prof. Dakuo Wang.
I got my B.E. in Computer Science and Technology and Graduated with honor at Beijing University of Technology. Before that, I’ve finished my junior and senior high at Beijing National Day School （北京市十一学校）.
- Professional Network Matters: Connections Empower Person-Job FitIn Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024
- In SubmissionExploring Parent’s Needs for Children-Centered AI to Support Preschoolers’ Storytelling and Reading ActivitiesIn , 2024
- CHI 2024Rethinking human-ai collaboration in complex medical decision making: A case study in sepsis diagnosis2024
- More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt EngineeringarXiv preprint arXiv:2311.09782, 2023
- Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation TasksarXiv preprint arXiv:2311.09825, 2023
- FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children’s Storybook NarrativesarXiv preprint arXiv:2311.09756, 2023
- Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureIn Findings of the Association for Computational Linguistics: EMNLP 2023, Dec 2023
- TCBB 2023Improving Biomedical Question Answering by Data Augmentation and Model WeightingIEEE/ACM Transactions on Computational Biology and Bioinformatics, Dec 2023
- Contextual Embedding and Model Weighting by Fusing Domain Knowledge on Biomedical Question AnsweringIn Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Dec 2022
- BIBM 2021Dual Model Weighting Strategy and Data Augmentation in Biomedical Question AnsweringIn 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Dec 2021
My current research fields includes data annotation and optimizing LLMs.
Before that, I’ve worked as Machine Learning Researcher at a joint program between LinkedIn and Microsoft Research Asia where I do study about LinkedIn’s social network data. I’ve also worked as an intern research assistant at THUNLP lab, supervised by Prof. Zhiyuan Liu(刘知远). My research area there includes Knowledge Embedding.
Open source communities
I’ve participated in many open-source communities. I’m the maintainer of the VSCode extension LaTeX-Utilities, and I’m the founder and maintainer of the EduOJ project. Furthermore, I’ve contributed to many open-source projects, like GitLab, UniversalOJ, OI-Wiki, nix and others.
I’ve participated as mentor and community leader in the Open Source Promotion Plan 2021. All my 3 students successfully finished their projects. I’ve participated as a student in the OSPP 2020 in the UniversalOJ community, and successfully finished my project.
Learn more about my open-source experience at here.