Jiong Zhu is a final-year Ph.D. candidate in Computer Science & Engineering at University of Michigan, advised by Prof. Danai Koutra. His doctoral research focuses on Graph Representation Learning and Graph Neural Networks (GNNs), and his works on improving GNN designs for graph datasets beyond homophily have been published at NeurIPS, AAAI and KDD with over 1000 citations. He also has 2 years of applied machine learning research experience at Amazon, where he worked closely with the product team and led the development of a semantic query recommendation system utilizing pre-trained Large Language Models (LLMs) and contrastive fine-tuning. He also served as reviewers for AI and Data Mining journals and conferences, and organizers of Workshop on Graph Learning Benchmark (GLB).