Shuaicheng Zhang

Virginia Tech - Computer Science.

Agentic AI / Graph Reasoning / Scientific Discovery

Designing AI systems that reason over structure, memory, and science.

Hi there, I recently completed my Ph.D. in Computer Science at Virginia Tech, advised by Dr. Dawei Zhou at the Sanghani Center for AI and Data Analytics. My research develops efficient and effective inference methods and data strategies for foundation models reasoning over structured knowledge.

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Shuaicheng Zhang
Degree Ph.D. Computer Science
Next AI Engineer at LinkedIn

Research Focus

01

Agentic AI Systems

Autonomous agents with planning, tool use, and structured reasoning capabilities.

02

Memory-Augmented LLMs

Long-term memory, retrieval-augmented generation, and scalable context management.

03

Graph-Grounded Reasoning

Knowledge graphs and structured context for GraphRAG and graph-LLM architectures.

04

Multimodal Foundations

Joint learning over text, graph structures, time-series, and other modalities.

05

Real-World Deployments

Applied systems for predictive maintenance, financial intelligence, databases, and discovery.

I am thrilled to announce that I will be joining LinkedIn as an AI Engineer. Beyond my role, I am always eager to collaborate on topics close to my research, especially agentic systems for scientific discovery and multimodal agent memory systems. Feel free to reach out.

Internship

Oak Ridge National Laboratory
2026 — Research Intern, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Microsoft
2025 — Research Intern, Microsoft Research, Redmond, WA, USA
MIT-IBM Lab
2023 — Research Intern, MIT-IBM Lab, Cambridge, MA, USA
Deloitte
2021 — NLP Research Intern, Natural Language Processing Team, Deloitte, NY, USA
Hundsun Technologies
2017 — Software Development Engineer Intern, Trust Team, Hundsun Technologies Inc., Hangzhou, China

News

05/2026 Passed my final defense and officially became Dr. Shuaicheng Zhang!
04/2026 Gave a talk at the Virginia Tech SNN Group on an agentic co-design system for hypothesis generation in spiking neural network (SNN) design.
01/2026 Gave an invited talk at Microsoft Research on Open World Graph Learning 😊!
01/2026 I will start my internship at Oakridge National Laboratory on GraphRAG for Scientific Discovery at Spring 2026 😊!
12/2025 Attending NeurIPS 2025 in San Diego, CA — see you at our poster session 😊!
09/2025 One paper accepted at NeurIPS 2025 — see you in San Diego 😊!
07/2025 Our paper "When Heterophily Meets Heterogeneity" received the KDD 2025 Best Paper Award in the Dataset and Benchmark track.
06/2025 Starting my internship at Microsoft on GNN for Database Foundation Model— see you in Redmond 😊!
05/2025 One paper accepted at KDD Benchmark 2025 — see you in Toronto 😊!
05/2025 Recognized as EXCELLENT Reviewer (Top 25%) by KDD 2025 February Track 😊!
12/2024 Recognized as OUTSTANDING Reviewer (Top 10%) by KDD 2025 August Track 😊!
10/2024 One paper accepted at IEEE BigData 2025 — see you in DC 😊!
07/2024 One paper accepted at KDD 2025 — see you in Toronto 😊!
09/2023 One paper accepted at ICAIF 2023 with oral — see you in New York 😊!
07/2023 Attending ICML 2023 in Honolulu, HI — see you at our poster session 😊!
05/2023 New preprint available!
05/2023 Joining IBM-MIT Lab this summer to work on deep graph generative models!
05/2023 One paper accepted at ICML 2023 — see you in Hawaii 😊!
04/2023 Thank you to ML Day-Amazon 2023 for the travel grant!
03/2023 Selected as a CCI Cyber Innovation Scholar!
10/2022 Attending CIKM 2022 in Atlanta, GA — see you at our workshop 😊!
10/2022 Thank you to CIKM 2022 NSF for the travel award!
06/2022 Serving as Publicity Chair of the 1st Trustlog workshop@CIKM22
05/2022 My website is alive! 🎉
04/2022 One paper accepted at Findings of NAACL 2022 — see you in Seattle 😊!

Publications

2025

  1. gpatcher.jpg
    HeroFilter: Adaptive Spectral Graph Filter for Varying Heterophilic Relations
    Shuaicheng Zhang, Haohui Wang, Junhong Lin, and 5 more authors
    2025
    to appear
  2. h2gb.png
    When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark
    Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, and 3 more authors
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
    DOI
  3. mentorpdm.png
    MentorPDM: Learning Data-Driven Curriculum for Multi-Modal Predictive Maintenance
    Shuaicheng Zhang, Tuo Wang, Stephen Adams, and 5 more authors
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 1, 2025
    DOI
  4. hg.jpg
    Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions
    A Kulkarni, F Alotaibi, X Zeng, and 6 more authors
    CoRR, 2025
    arXiv preprint

2024

  1. ugt.png
    UnifiedGT: Towards a Universal Framework of Transformers in Large‑Scale Graph Learning
    Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, and 3 more authors
    In IEEE International Conference on Big Data (BigData), 2024
    DOI

2023

  1. federated.png
    Personalized Federated Learning under Mixture of Distributions
    Shuaicheng Zhang, Yue Wu, Wenchao Yu, and 5 more authors
    In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023
    DOI
  2. tgeditor.png
    TGEditor: Task‑Guided Graph Editing for Augmenting Temporal Financial Transaction Networks
    Shuaicheng Zhang, Yada Zhu, and Dawei Zhou
    In Proceedings of the Fourth ACM International Conference on Artificial Intelligence and Finance (ICAIF), 2023
    DOI

2022

  1. graphtransformer.png
    Extracting Temporal Event Relation with Syntax‑guided Graph Transformer
    Shuaicheng Zhang, Qiang Ning, and Lifu Huang
    In Findings of the Association for Computational Linguistics: NAACL, 2022
    DOI

My Cats

Cats are connoisseurs of comfort.

– James Herriot

Here are some photos of my cats. Each one has their own unique personality and brings joy to my life in their own special way.

Jojo
Joy
From left to right: Jojo and Joy enjoying their favorite spots.
Cat 4
Cat 5
More of my cats being their adorable selves.

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