Dawei Zhou
Bio
Dr. Dawei Zhou is an Assistant Professor at the Computer Science Department of Virginia Tech and the director of the VirginiaTech Learning on Graphs (VLOG) Lab. Zhou’s prior research on open-world machine learning, trustworthy machine learning, and risk management, with applications in financial fraud detection, cyber security, financial forecasting, social media analysis, and healthcare. He obtained his Ph.D. degree from the Computer Science Department of the University of Illinois Urbana-Champaign (UIUC). He has authored more than 40 publications in premier academic venues across AI, data mining, and information retrieval (e.g., AAAI, IJCAI, KDD, ICDM, SDM, TKDD, DMKD, WWW, CIKM) and has served as Vice Program Chair/Proceeding Chair/Session Chairs/(Senior) Program Committee Members in various top ML and AI conferences (e.g., NeurIPS, ICML, KDD, WWW, SIGIR, ICLR, AAAI, IJCAI, BigData, etc.). His research is generously supported by Virginia Tech, NSF, DARPA, DHS, Commonwealth Cyber Initiative, 4VA, Deloitte, and Cisco. His work has been recognized by CNSF Capitol Hill Science Exhibition, Cisco Faculty Research Award, and AAAI New Faculty Highlights roster.
VLOG Lab
Lab Openings
I am actively looking for self-motivated Ph.D. students (2~3 GRAs + 2 GTAs) and one postdoc (Virginia Tech Presidential Fellowship) to join my group in the Fall 2024 semester.
My current research includes but is not limited to the following topics:
Long-tail category analysis (e.g., generalization, pre-trained model)
Transfer learning across graphs (e.g., evolving domain discrepancy, data augmentation)
Symbolic reasoning and learning on knowledge graphs (e.g., question answering, recommendation)
Trustworthy learning on graphs (e.g., fairness, calibration, robustness)
Deep graph generative model for scientific domains (e.g., PPI network, ARG prediction, 3D molecular conformation)
Machine learning for finance (e.g., financial forecasting, financial fraud detection)
Students with CS, math, biostatistics, and EE background are particularly encouraged to apply! Please drop me an email (zhoud[at]vt[dot]edu) with your CV and transcripts if you are interested.
News
[5/2024]: Honored to receive a new grant as PI from U.S. Department of Homeland Security (DHS) to support our research on Combating Dynamic and Networked Financial Crimes.
[5/2024]: Two papers have been accepted by ICML2024. Congrats to my student Haohui for her first leading-author paper on Dynmaic Non-iid Transfer Learning!
[4/2024]: One paper on Benchmarking 3D Molecule Learning with Functional Groups has been accepted by IJCAI2024. Congrats to my students Tingwei and Jianpeng!
[4/2024]: Congrats to my students Haohui and Shuaicheng, who have been selected as the CCI Cyber Innovation Scholar again!
[2/2024]: Honored to receive a new grant from DARPA to support our research on 3D Metamaterial Synthesis via Large Graph-Language Foundation Model.
[1/2024]: I am invited to serve as the Editor of Elsevier Big Data Research.
[1/2024]: I am invited to serve as the Proceedings Chair for ACM SIGKDD 2024, which will be held in Barcelona, Spain.
[12/2023]: I am honored to be selected as one of the AAAI-24 New Faculty Highlights and invited to give a talk on Open World Machine Learning!
[12/2023]: Honored to receive a Two-Year Postdoc Fellowship Grant from the Office of Research and Innovation, Fralin Life Sciences Institute, and the Institute for Critical Technology and Applied Science as PI! Welcome Adithya Kulkarni to join VT as a postdoc (co-advise with Prof. Lifu Huang) working on Hypothesis Generation for Scientific Domains!
[12/2023]: One paper on the Unbiased Graph Generative Model is accepted by ICDE 2024.
[11/2023]: We will organize TrustLOG: The Second Workshop on Trustworthy Learning on Graphs @ WWW'24. See u in Singapore!
[9/2023]: One paper on Data Sanitation for Financial Transaction Networks is accepted by ICAIF 2023. Congrats to my student Shuaicheng as the leading author!
[8/2023]: Honored to receive financial support from Deloitte on the projects of long-tailed learning and predictive maintenance.
[7/2023]: I am invited to serve as session chair and Ph.D. consortium panelist @SIGKDD2023.
[6/2023]: I am invited to give a talk at the Knowledge Graphs and Semantic Computing Seminar@UIUC.
[6/2023]: I am invited to give a talk on Rare Disease Diagnosis@Children's National Hospital.
[6/2023]: I accepted the invitation to serve as SPC of AAAI 2024.
[5/2023]: One paper on Individual Calibration (CaliRare) is accepted by SIGKDD 2023. Congrats to my student Longfeng as the leading author!
[5/2023]: Honored to receive the Commonwealth Cyber Initiative Grant on open knowledge network (OKN) conflict resolution as PI.
[4/2023]: My student Shuaicheng will join the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) as a visiting student to conduct research on the generative graph foundation model.
[4/2023]: One paper on Personalized Federated Learning is accepted by ICML 2023. Congrats to my student Shuaicheng as the leading co-author!
[3/2023]: Congrats to my students Haohui and Shuaicheng, who have been selected as the CCI Cyber Innovation Scholar!
[3/2023]: I am invited to serve as the Vice Program Chair for the IEEE BigData 2023, which will take place in Sorrento, Italy.
[3/2023]: I am invited to give a talk on "Open Environment Rare Category Analysis" to our Deloitte partners.
[2/2023]: Honored to receive the Cisco Faculty Research Award on insider threat detection as PI.
[2/2023]: I am invited to give a talk on "Harnessing Rare Category Trinity for Complex Networks" @Palo Alto Research Center.
[2/2023]: One paper on Algorithmic Fairness is accepted by WWW 2023.
[1/2023]: I accepted the invitation to serve as SPC/PC members of KDD/ICML/IJCAI/SIGIR/CIKM/NeurIPS 2023.
Contact
Office: 3160 F, Torgersen Hall, 620 Drillfield Dr., Blacksburg, VA 24060
Phone: (540) 231-2642
Email: zhoud [at] vt [dot] edu