Chuxu Zhang photo

Chuxu Zhang / 张初旭

Associate Professor
Director, MINDS Lab
School of Computing, College of Engineering
University of Connecticut (UConn)
chuxu.zhang@uconn.edu

News
Pin: Looking for PhD students and research interns at UConn SoC. Please read THIS for detailed student recruitment information.
Sep 2026: DIAL, MAGIC-Video, and RAG-GD were accepted to NeurIPS 2026.
Event: Resource-Efficient Learning workshop at KDD'26 on August 2026.
Invited Talk: AI for Societal Impacts: Foundation Model, Resource Efficiency, and Safety
Nov 2025: Best Paper Candidate at ICDM'25    
Invited Talk: On the Intersection of Graph and Language Models
Aug 2025: New NSF Core Grant on AI for Tackling the Food Insecurity                            
July 2025: Early Career Spotlight at IJCAI'25    
Event: Resource-Efficient Learning workshop, Graph Foundation Models and Graph Prompt Learning tutorials at KDD'25 on August 2025.
May 2025: MASS, GPM, and GIT were accepted to ICML 2025.
Event: Resource-Efficient Learning workshop/tutorial at WWW'25 on April 2025.
Aug 2024: Resource-Efficient Learning workshop at KDD'24 on Aug 25.
Aug 2024: NSF grant on promoting community resilience for teenagers and young adults.       
Jul 2024: The Frontiers of Science Award. Thanks to ICBS 2024
:)
Invited Talk: Graph Machine Learning: Effectiveness, Efficiency, and Safety
Feb 2024: The NSF CAREER Award. Thanks to NSF, my excellent mentors, students, and collaborators :)
About
I am an Associate Professor wth tenure of Computer Science and Engineering at the University of Connecticut. My research broadly focuses on AI and AI+X. Recently, I have focused on developing foundational, efficient, and trustworthy AI models and techniques, particularly for language, graph, spatiotemporal, and multimodal data. I also translate these advances into real-world applications in healthcare and industrial systems. My work is primarily published in top AI conferences.

I have received several awards/honors, such as the NSF CAREER Award. Besides, my work has earned multiple Best Paper Awards or nominations at leading conferences.

I received my Ph.D. in Computer Science and Engineering from the University of Notre Dame in 2020.

Publications
Here are some of my recent papers. Please see my Google Scholar page for a complete list.

  • NeurIPS'26: Direction-Informed Adaptive Learning for LLM Agents
  • NeurIPS'26: Structured Memory for Ultra-Long Agentic Video Reasoning
  • NeurIPS'26: In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective
  • ICML'26: Graph is a Substrate Across Data Modalities
  • ICML'26: Non-Monotonic Autoregressive Sequence Model
  • KDD'26: Generalizing GNNs with Tokenized Mixture of Experts
  • ACL'26: AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answering
  • NeurIPS'25: AutoData: A Multi-Agent System for Open Web Data Collection
  • NeurIPS'25: Generative Graph Pattern Machine
  • ICML'25: MASS: MAthematical Data Selection via Skill Graphs for Pretraining Large Language Models
  • ICML'25: Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
  • ACL'25: NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning
    • Teaching & Service
    Teaching:
    • Big Data Analytics (Fall 2025, Fall 2026)
    • Deep Learning (Spring 2021, Spring 2022, Spring 2023, Fall 2024)
    • Graph Machine Learning (Fall 2020, Fall 2021, Fall 2022)
    • Artificial Intelligence (Fall 2023)
    Service:
    • Conference Area Chair: ICML, NeurIPS, ICLR, KDD, ARR
    • Journal Editor: Transactions on Machine Learning Research, ACM Transactions on Intelligent Systems and Technology, Data Mining and Knowledge Discovery