Ruijiang Gaoمشاهده پروفایل
استادیار
Ruijiang Gao is an Assistant Professor in Information Systems at the Naveen Jindal School of Management, University of Texas at Dallas. He earned his PhD in Information, Risk, and Operations Management from UT Austin (2024), MA in Statistics from the University of Michigan (2018), and BS in Statistics from the School of the Gifted Young at University of Science and Technology of China (2016). His research focuses on human-centered machine learning , emphasizing robustness , interpretability , adaptability , and fairness in ML/AI models, including foundational models. Key contributions include: Human-AI collaboration frameworks with bandit feedback Counterfactual self-training techniques Contextual recourse bandit algorithms Uncertainty-aware domain adaptation Nonparametric discrete choice experiments for product design His work has been accepted at top ML/AI conferences (AISTATS, AAAI, NeurIPS, ICML, IJCAI, ICCV) and journals (Machine Learning, Management Science). Notable achievements include Best Student Paper at CIST 2022 and Best Paper Runner-Up at WITS 2024. Research grants and fellowships include the UT Austin Continuing Fellowship and INFORMS Data Science Workshop Scholarships. Current research trends include: Human-AI collaborative decision-making under confounding Counterfactual-aware model training Adaptive survey design for consumer preferences Uncertainty calibration in regression and domain adaptation Algorithmic fairness in contextual bandits He has previously collaborated with institutions including Netflix Research, Harvard University, IBM Research, Tencent, and Amazon.
