Publications
Published, submitted, and planned research outputs in machine learning, NLP, retrieval, and model evaluation.
Parameter-Efficient Neural Machine Translation for Low-Resource Language Pairs: English-Norwegian in the Oil & Gas Domain
Xiaojing Yang, Zhihan Li, Gege Sun, Mengyue Li, Meriem Beloucif
Investigates parameter-efficient adaptation of neural machine translation for the Norwegian oil and gas domain, covering LoRA fine-tuning, hyperparameter optimisation, data-quality assessment, and model-scale evaluation.
EAMT
First author; lead experimental contributor
Beyond Routing: Diagnosing Modular LoRA Experts for Low-Resource Multilingual Petroleum-Domain Translation
Xiaojing Yang, Zhihan Li, Meriem Beloucif
Studies modular expert architectures for low-resource, domain-specific NMT, including language-specific LoRA adapters, learned routing, target-anchored synthetic data, terminology-aware evaluation, and routing analysis.
EMNLP 2026
First author; framework design and experimental lead
Structure-Aware Graph Retrieval for Evidence Grounding over Long Annual Reports
Xiaojing Yang, Zhihan Li, Meriem Beloucif
Evaluates how document structure, graph-based candidate expansion, and deterministic routing can improve evidence grounding over long financial reports, with robustness testing and held-out-year validation.
EMNLP 2026
First author; retrieval framework and evaluation lead
Projects
Selected research and technical projects in machine learning, NLP, retrieval, evaluation, and applied AI systems.
Experience
Research, work, and teaching experience across AI, NLP, data analysis, and machine learning.
Research Projects in Language Technology
Designed and led research projects across multilingual NLP, machine translation, retrieval, data attribution, and bias evaluation.
Data Analyst
Completed various data analytics projects spanning customer intelligence, sales optimization, and predictive modeling across e-commerce, retail, and marketing domains.
Teaching Assistant, Machine Translation
Supported 25 students across assignment marking, lab sessions, and project supervision in a machine translation course.
Skills
Methods, tools, and technical strengths supporting my research and applied AI work.
Python
The core programming language for AI and data science, supporting machine learning and deep learning development.
PyTorch
Facebook's deep learning framework providing dynamic computation graphs and flexible model building.
Pandas
Powerful data analysis and manipulation library, the go-to tool for handling structured data.
NumPy
Fundamental package for scientific computing, providing high-performance multidimensional array operations.
Git/GitHub
Version control system and collaborative development platform for managing code repositories.
OpenCV
Computer vision library for image processing, object detection, and multimodal AI applications.