Mrs. Rong Wang is a postdoctoral researcher at the Eberhard Karls University of Tübingen, Germany, specializing in computational linguistics and the evaluation and optimization of large language models (LLMs). She holds an M.Sc. in Computational Linguistics (NLP) from the University of Stuttgart (Grade: 1.7, 2024) and a Ph.D. in Digital Humanities from Zhejiang University, China (2016). Her interdisciplinary academic background bridges computer science, linguistics, and AI-driven humanities research, reflecting her ability to apply quantitative and symbolic methods to linguistic and cognitive studies. Professionally, she has served as a Postdoctoral Fellow at the University of Tübingen, AI Engineer at Telus International Digital AI, AGI Engineer Intern at Deepseek AI, Data Scientist at DEKRA GmbH, and Assistant Professor of Linguistics at Hangzhou Dianzi University. Her research focuses on language model evaluation metrics, neural-symbolic reasoning, multimodal semantics, and automated linguistic assessment. She has contributed to projects on enhancing spatial reasoning in LLMs, multi-agent AI systems, and personality recognition models, alongside authoring several publications on machine learning applications in cognitive linguistics and NLP evaluation. Technically proficient in Python, R, JavaScript, and SQL, she is experienced with frameworks such as LangChain, Autogen, Hugging Face, and PyTorch, and cloud platforms including Azure ML and AWS SageMaker. Her certifications include Azure Certified Data Scientist Associate and AWS Certified AI Practitioner. Mrs. Wang is fluent in English, German, and Chinese, with working knowledge of Japanese, and is recognized for her strong teamwork, communication, and leadership abilities. Her recent works have appeared in Data Intelligence, Psychology Methods, and TMLR, demonstrating her innovative contributions to the AI and NLP research community. (0 Citations ; 2 Documents ; 0 h-index.)
Profiles: Scopus | ResearchGate
Featured Publications
Wang, R., Sun, K., & Kuhn, J. (2024, Dec). Dspy-based neural-symbolic pipeline to enhance spatial reasoning in LLMs [Preprint]. arXiv. https://arxiv.org/abs/2411.18564
Wang, R., Sun, K., & Kuhn, J. (2024, Nov). A pipeline of neural-symbolic integration to enhance spatial reasoning in large language models [Preprint]. arXiv. https://arxiv.org/abs/2411.18564
Sun, K., & Wang, R. (2024, Oct). The roles of contextual semantic relevance metrics in human visual processing [Preprint]. arXiv. https://arxiv.org/abs/2410.09921
Wang, R., & Sun, K. (2024, Jul). A novel dependency framework for enhancing discourse data analysis [Preprint]. arXiv. https://arxiv.org/abs/2407.12473
Wang, R., & Sun, K. (2024, Jun). Continuous output personality detection models via mixed strategy training [Article]. arXiv. https://arxiv.org/abs/2406.16223