About Me
Hello! I am an Associate Professor in the School of Computing at Stevens Institute of Technology.
My research group develops machine learning and AI methods that reason over complex and evolving data with a focus on making predictions that are faithful, causal, and robust. Much of our work centers on graph-structured, text, and timeseries data, where we design models that capture how relationships and events change over time. We are especially motivated by high-stakes applications in healthcare and social informatics, where understanding why a prediction is made matters as much as accuracy.
Our research is supported by the National Science Foundation (including an NSF CAREER award and the NSF NAIRR Pilot), NIH AIM-AHEAD, Nvidia, and Stevens Institute of Technology.
I received my Ph.D. from the Department of Computer Science of Virginia Tech under Dr. Naren Ramakrishnan, a Fellow of IEEE, AAAS, and ACM.
I am also affiliated with Stevens Institute for Artificial Intelligence (SIAI),
Center for Research Toward Advancing Financial Technologies (CRAFT), and Semcer Center for Healthcare Innovation (CHI).
Join us: recruiting PhD students for Fall 2027.
I am looking for motivated students interested in LLM reasoning and agentic AI, causal and interpretable machine learning, graph and time-series learning, and AI for healthcare and science.
Read about openings and how to apply → | PhD ad (PDF) | Meet the lab
Read about openings and how to apply → | PhD ad (PDF) | Meet the lab
Research Interests
- Foundations of AI and Machine Learning: LLM reasoning and agentic AI, causal inference, graph neural networks, domain adaptation and generalization
- Trustworthy and Interpretable AI: concept-grounded and mechanistic interpretability, fairness, privacy-aware learning
- Use-Inspired AI: clinical prediction and diagnostic reasoning, societal event forecasting, hydrology and macroeconomic forecasting
See Research for current projects and Publications for papers.
News
| 08.2026 | Paper on LLM Intermediate-variable Reasoning is accepted by EMNLP 2026 Findings. |
| 08.2026 | Paper on Domain Generalization is accepted by CIKM 2026. |
| 05.2026 | Paper on Large Language Models for Socio-Political Event Interpolation and Extrapolation is accepted by ECML-PKDD 2026. |
| 04.2026 | Paper on Transparent Domain Adaptation is accepted by ICML 2026. |
| 04.2026 | Congratulations to Sandy Xiaoxue Han on successfully defending her PhD thesis! |
| 04.2026 | Paper on Conceptual Hierarchies within LLMs is accepted by ACL Findings 2026. |
| 01.2026 | I am invited to join the Faculty Futures AI studio at NJ AI Hub. |
| 09.2025 | Paper on Agentic Causal Discovery was accepted by EMNLP 2025 (Findings). |
| 08.2025 | Congratulations to Nan Cui and Jing Chen on successfully defending their PhD theses! |
| 05.2025 | Congratulations to Sandy Han and Pengfei Hu on their summer internships. Best wishes for a productive and rewarding experience! |
| 01.2025 | Paper on Graph OOD generalization was accepted by AISTATS 2025. |
| 10.2024 | Paper on Continual Graph Learning was accepted by NeurIPS 2024. |
| 10.2024 | We are grateful to receive an award from NSF NAIRR Pilot to support our research on domain-informed foundation models! |
| 10.2024 | I am excited to receive a research fellowship from the NIH-sponsored AIM-AHEAD program! This fellowship will support my work on developing AI methods to address and mitigate health outcome disparities. |
| 09.2024 | Invited talk at University of Delaware. |
| 08.2024 | Tutorial talk at KDD 2024. |
| 08.2024 | I will serve as Co-chair for AAAI Doctoral Consortium (2025). |
| 02.2024 | Congratulations to Chang on successfully defending his PhD thesis! |
| 11.2023 | Invited talk at Case Western Reserve University. |
| 09.2023 | Paper on contrastive learning for ICD coding was accepted by NeurIPS 2023. |
| 09.2023 | Paper on fair federated graph neural networks was accepted by ICDM 2023. |
| 08.2023 | Paper on time series generation was accepted by TKDE. |
| 05.2023 | Paper on graph unlearning was accepted by KDD 2023. |
| 05.2023 | Received Early Career Award for Research Excellence from Stevens. |
| 03.2023 | Stevens media published a nice article on my research. |
| 02.2023 | Invited talk at ADP Data Science and Machine Learning. |
| 12.2022 | Invited keynote talk at MLoG workshop at ICDM'22. |
| 10.2022 | Paper on news-enhanced pandemic forecasting was accepted by IEEE BigData 2022. |
| 09.2022 | Two papers were accepted by ICDM 2022. |
| 07.2022 | Congratulations to Dr. Deng who successfully defended her PhD thesis! |
| 05.2022 | Songgaojun Deng received the Excellence in Graduate Research Award from Stevens! |
| 05.2022 | Chang Lu started summer internship at NEC Labs America. |
| 05.2022 | Paper on causal event analysis was accepted by KDD 2022. |
| 12.2021 | Paper on health event prediction using dynamic disease graphs was accepted by AAAI 2022. |
| 11.2021 | Invited talk at the Computer Science department, NJIT. |
| 11.2021 | Paper on anti-Asian hate speech detection was accepted by ICWSM 2022. |
| 09.2021 | I am serving as student travel award co-chair for KDD 2022. |
| 08.2021 | Paper on interpretable event prediction was accepted by CIKM 2021. |
| 06.2021 | I am honored to receive an NSF CAREER award to explore deep interpretable methods for temporal event modeling. Thanks NSF! |
| 05.2021 | PhD student Songgaojun Deng received Excellence Doctoral Fellowship. Congratulations Songgaojun! |
| 04.2021 | Paper on collaborative graph learning for health event prediction was accepted by IJCAI 2021. |
| 02.2021 | Check out our toturial on Explainable AI for Societal Event Predictions in AAAI 2021. |
| 02.2021 | Paper on fake news detection was accepted by PAKDD 2021. |
| 01.2021 | I will serve on the Bergen County Academies ATCS advisory board. |
| 11.2020 | I will serve as a senior PC for IJCAI-2021. |
| 10.2020 | Paper on asynchronous online federated learning was accepted by IEEE BigData 2020. |
| 07.2020 | Paper on predicting long-term influenza-like illness cases was accepted by CIKM 2020. |
| 07.2020 | Invited to serve on the PC of ICLR 2021, IJCAI 2021, TheWebConf 2021. |
| 05.2020 | Paper on dynamic knowledge graph based multi-event forecasting was accepted by KDD 2020. |
| 05.2020 | Received an NSF CRII award to explore and create deep learning models for learning dynamic graph-based event precursors. Thanks NSF! |
| 03.2020 | Paper on reducing identity bias in detecting toxic comment detection was accepted by ICWSM 2020. |
| 09.2019 | Received an Nvidia GPU grant. Thanks Nvidia! |
| 08.2019 | I will be teaching a new course: Natural Language Processing in the fall semester. |
| 08.2019 | Invited to serve on the PC of AAAI 2020. |
| 04.2019 | Paper on modeling dynamic event context graphs was accepted by KDD 2019. |
| 04.2019 | Check out our tutorial on Spatio-Temporal Event Forecasting and Precursor Identification in KDD 2019. |
| 01.2019 | Invited to serve on the PC of KDD 2019, ASONAM 2019, SDM 2019. |
Professional Service
Service highlights: Area Chair, ICLR 2027 and KDD 2024 to 2026; Doctoral Consortium Co-chair, AAAI 2025; Senior PC, AAAI 2027 and IJCAI 2021; Student Travel Award Co-chair, KDD 2022.
- Organizing Committee
- Doctoral Consortium Co-chair: AAAI 2025
- Local Arrangement Chair: IEEE INFOCOM 2023
- Student Travel Award Co-chair: KDD 2022
- Area Chair: ICLR 2027; KDD 2024 - 2026
- Session Chair
- SDM 2021
- KDD 2020
- Senior PC: AAAI 2027; IJCAI 2021
- Program Committee: KDD 2019-2023
- Program Committee: AAAI 2020-2026
- Program Committee: ICLR 2021, 2023 - 2026
- Program Committee: ICML 2020-2026
- Program Committee: NeurIPS 2021-2026
- Program Committee: IJCAI 2021-2026
- Program Committee: CVPR 2023
- Program Committee: The Web Conf (previously WWW) 2021-2023
- Program Committee: CIKM short paper track 2022
- Program Committee: PAKDD 2020-2022
- Program Committee: SDM 2019-2026
- Program Committee: IEEE BigData 2020-2026
- Program Committee: ICMLA 2019
- Program Committee: ASONAM 2018-2022
- Reviewer: Transactions on Machine Learning Research (TMLR)
- Reviewer: Sensors, published by MDPI
- Reviewer: Nature Communications
- Reviewer: Pattern Recognition
- Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE)
- Reviewer: ACM Transactions on Knowledge Discovery from Data (TKDD)
- Reviewer: IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Reviewer: Social Network Analysis and Mining (SNAM)
- Reviewer: IEEE Transactions on Intelligent Transportation Systems (T-ITS)
- Reviewer: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
- Reviewer: IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- Guest Editor: Frontiers in Big Data
Contact
Mailing Address
1 Castle Point Terrace,
Hoboken, NJ 07030,
USA
Office
Gateway South 448
yue.ning AT stevens.edu