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Email: huangyiyan@gbu.edu.cn Location: Great Bay University, Songshan Lake, Dongguan, China Welcome to my homepage! I am Yiyan Huang, a tenure-track Assistant Professor in the School of Computing and Information Technology at Great Bay University, Guangdong, China. My main research focus is Causal Inference and Data Science, at the intersection of Stats&Econ, Operations Research, and Machine Learning. |
📣 Prospective opportunities 📣:
I am looking for self-motivated Visiting students (访问学生), RAs (研究助理), Masters (湾大-南科大联培硕士生、湾大-深圳大学联培硕士生), and PhDs (湾大-哈工深联培博士生) to join my research team. I also have several openings for Postdoctoral (博士后) positions, with the postdoctoral certificate awarded by THU or USTC(博后出站颁发清华大学/中国科学技术大学博后联合培养证书). The salary of a postdoc ranges from 350k-400k CNY/year, and details can be found via GBU Recruitment Page.
Please email me your CV if you are interested in research topics related to Causal Inference and Machine Learning.
My primary research focuses on Causal Inference and Data Science, with a multidisciplinary approach integrating Statistics, Econometrics, Operations Research, and Machine Learning. I'm also interested in applying causal inference and data science methods for solving real-world problems in fields such as Management Science, Digital Marketing, Healthcare, etc. Currently, our group is focusing on three research lines (Collaborations are always welcome!):
⭐ 1. [Theoretical] Data-driven causal decision making: Studying the contextual and non-contextual bandit problem in different settings, in order to solve the resource allocation problem in Management Science and Operations Research.
⭐ 2. [Theoretical and Experimental] Causal4ML and ML4causal: Bridging the gap between causal inference and machine learning, aiming to address trustworthiness challenges such as robust learning, distribution shifts, and uncertainty.
⭐ 3. [Experimental] Reliable/Trustworthy LLM: Using causal inference and machine learning methods to build more reliable/trustworthy Large Language Models.
Internship at JD Digital Technology-Risk Management Center-Intelligent Model Department.
Reviewers for COLT、Neurips、ICML、ICLR、AISTATS、JMLR、TPAMI、Neural Networks、Journal of Biomedical Informatics, etc.