Tyler Derr
 |
Assistant Professor Network and Data Science (NDS) Lab Email: Tyler (dot) Derr (at) vanderbilt (dot) edu |
Short Bio
Tyler Derr is an Assistant Professor in the Department of Computer Science, Teaching and Affiliate Faculty in the Data Science Institute, and Faculty Fellow in the Frist Center for Autism and Innovation at
Vanderbilt University. He directs the Network and Data Science (NDS) lab, which focuses on social computing, data
mining, and machine learning, especially in social network analysis,
deep learning on graphs, and data science for social good with
applications in education, health, political science, and autism research. He received his
PhD (2020) in Computer Science from Michigan State University under
the supervision of Dr. Jiliang Tang
and was a member of the Data Science and Engineering (DSE) Lab and Teachers in Social Media (TISM) Project. He had completed his MS
(2015) in Computer Science at The Pennsylvania State University and
dual BS (2013) in Computer Science and Mathematical Sciences at The
Pennsylvania State University. He was the recipient of the Best Reviewer Award at
ICWSM 2019 & 2021, the Best Student Poster Award at SDM 2019, the “People's
Choice” Award for the 3 Minute Thesis Competition at MSU, and the Fall 2020 Teaching Innovation Award from the School of Engineering at Vanderbilt. Tyler also actively serves as
a reviewer/program committee member for journals/conferences in his
research domain.
[Open positions]
I am recruiting PhD students to work with me on topics in my general interests (seen below). Master's and undergraduate students within VU and visiting scholars are also welcome. Please feel free to email me.
Please see here for position details.
Research Interests
data mining, network anlaysis, social computing, graph neural networks, graph mining, machine learning, network measures and models, data science for social good (e.g., education, health, political science, and autism research)
Call for Papers
Machine Learning on Complex Graphs - Frontiers in Big Data (Topic Editor)
Welcomed topics include: graph kernels/summarization/coarsening/alignment/etc, graph neural networks, network embedding, related applications, etc
We especially invite submissions with emphasis on complex graphs such as dynamic/hyper/heterogeneous/knowledge graphs
Submission Deadline: July 7th, 2022 (link)
The 1st International Workshop on Privacy Algorithms in Systems (PAS) to be held at CIKM’22 (Workshop Co-Chair)
Note that accepted works are non-archival (i.e., not published in a formal proceedings).
Welcomed topics include: privacy preservation in deep learning models and complex data, benchmark analysis of privacy algorithms, privacy attacks, theory of privacy algorithms, etc., and their applications
Submission Deadline: August 15th, 2022 (link)
The 2nd International Workshop on Machine Learning on Graphs (MLoG) to be held at ICDM’22 (Workshop Co-Chair)
Note that accepted works will be published in formal proceedings by the IEEE Computer Society Press. Details: here.
We invite submissions that focus on recent advances in research/development of machine learning on graphs along with their applications.
Submission Deadline: September 2nd, 2022 (link)
The 6th Workshop on Graph Techniques for Adversarial Activity Analytics (GTA3 2022) to be held at IEEE BigData’22 (Workshop Co-Chair)
Note that accepted works will be published in formal proceedings by the IEEE Computer Society Press. Details: here.
We invite submissions that focus on modeling adversarial activites with graphs for ‘‘connecting the dots’’, ‘‘finding a needle in a haystack’’, and ‘‘defending against attacks.’’
Submission Deadline: October 10th, 2022 (link)
News (See past news before joining VU here)
2022
6/2022: Our paper Distance-wise Prototypical Graph Neural Network for Imbalanced Node Classification is accepted by the MLG Workshop at KDD2022
6/2022: Our workshop Privacy Algorithms in Systems is accepted at CIKM2022
6/2022: My PhD student Yuying Zhao's first paper since joining NDS ‘‘Inferring EHR Utilization Workflows through Audit Logs’’ is accepted at AMIA2022
5/2022: My research was highlighted in VU Provost C. Cybele Raver's keynote at The Vanderbilt Summit on Modern Conflict
5/2022: Our paper ‘‘Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage’’ is accepted at KDD2022
5/2022: Our paper ‘‘On Structural Explanation of Bias in Graph Neural Networks’’ is accepted at KDD2022
5/2022: Our paper ‘‘ChemicalX: A Deep Learning Library for Drug Pair Scoring’’ is accepted at KDD2022 and corresponding open-source library is available here
5/2022: Our workshop Graph Techniques for Adversarial Acticity Analytics (GTA3) was accepted at IEEE BigData2022
5/2022: Congratulations to my student Yu Wang for being awarded Vanderbilt's C. F. Chen Best Paper Award in Computer Science for his paper ‘Tree Decomposed Graph Neural Network’!
4/2022: Our workshop Machine Learning on Graphs (MLoG) is accepted at ICDM2022
3/2022: Awarded Outstanding PC Member Award at WSDM2022 (with credit going to NDS subreviewers Yu Wang, Yuying Zhao, Yunchao (Lance) Liu, Zhaoqing Li)
3/2022: Congratulations to my student Yunchao (Lance) Liu for being awarded the Nvidia Academic Hardware Grant for his project on ‘‘Interpretable 3D Graph Neural Networks for Drug Discovery!’’
2/2022: Preprint ‘‘ChemicalX: A Deep Learning Library for Drug Pair Scoring’’
2/2022: Accepted to attend the ASEE DELTA Junior Faculty Institute
2/2022: Invited to serve as PC member for WebSci2022 and Graph Learning Workshop@WebConf2022
1/2022: Our book chapter ‘‘Graph Neural Networks: Self-supervised Learning’’ is published in the new edited Springer book ‘‘Graph Neural Networks: Foundations, Frontiers, and Applications’’!
1/2022: Invited to serve as SPC member for ICWSM2022
2022: Invited to serve as a grant proposal panelist for NSF during 2022
2021
12/2021: Topic Editor of Machine Learning on Complex Graph - Frontiers in Big Data
12/2021: Preprint ‘‘Imbalanced Graph Classification via Graph-of-Graph Neural Networks’’
12/2021: Introduced CS and AI topics to students at Tohoku International School through Skype a Scientist
11/2021: Invited to serve as SPC member for KDD2022
11/2021: Our workshop ‘‘Machine Learning on Graphs (MLoG)’’ is accepted at WSDM2022
10/2021: Preprint ‘‘Distance-wise Prototypical Graph Neural Network for Imbalanced Node Classification’’
9/2021: Preprint of our review on ‘‘Graph Neural Networks: Self-supervised Learning’’
9/2021: Invited to be a judge for VandyHacks 2021 (VU's premier student hackathon)
9/2021: Invited to serve as PC member for The Web Conference 2022
8/2021: Invited to serve as Social Media and Publicity Chair of KDD2022
8/2021: Invited to serve as PC member for GTA3@BigData2021
8/2021: Invited to serve as SPC member for WSDM2022
8/2021: My PhD student Yu Wang's first paper since joining NDS ‘Tree Decomposed Graph Neural Network’ is accepted at CIKM2021
8/2021: Our paper ‘Graph Feature Gating Networks’ is accepted at CIKM2021
8/2021: Our paper ‘Deep Adversarial Network Alignment’ is accepted at CIKM2021
7/2021: Our paper ‘Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries’ is accepted at ACM Hypertext2021
6/2021: Awarded Best Reviewer Award at ICWSM2021
6/2021: Our paper ‘Interpretable Visual Understanding with Cognitive Attention Network’ is accepted at ICANN2021
6/2021: Invited to serve as PC member for ICLR2021
5/2021: Out paper ‘‘Graph Adversarial Attack via Rewiring’’ is accepted at KDD2021
5/2021: Invited to serve as PC member for IEEE BigData2021 and CIKM2021
4/2021: Invited to serve as PC member for EMNLP2021, IRI2021, and NeurIPS2021
4/2021: Awarded SIAM Early Career Travel Award for SDM2021 supported by NSF
4/2021: Our paper ‘‘Self-supervised Learning on Graphs: Deep Insights and New Directions’’ is accepted at SSL@WWW2021
3/2021: Invited to serve as PC member for GNNSys’21 Workshop @ MLSys’21
2/2021: Invited to serve as Doctoral Consortium Chair of WSDM2022
2/2021: I received the Fall 2020 Innovative Teaching Award from the School of Engineering
1/2021: Invited to serve as PC member for WebSci2021
2021: Invited to serve (twice) as a grant proposal panelist for NSF during 2021
2020
12/2020: Invited to serve as PC member for ICML2021
12/2020: Our paper ‘‘Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach’’ is accepted at AAAI2021
12/2020: Invited to serve as PC member for ACL2021
11/2020: Invited to serve as PC member for KDD2021
11/2020: Introduced CS and AI topics to students at Ardsley High School through Skype a Scientist
11/2020: Panelist on the ‘‘Graduate School is not a Job’’ graduate recruitment event
10/2020: Our paper ‘‘Node Similarity Preserving Graph Convolutional Networks’’ is accepted at WSDM2021
10/2020: Our paper ‘‘CopyAttack: Attacking Black-box Recommendations via Copying Cross-domain User Profiles’’ is accepted at ICDE2021
10/2020: Gave an invited talk ‘‘Navigating the Faculty Job Search’’ in Michigan State's College of Engineering Graduate Lunch & Learn seminar
9/2020: Gave an invited talk ‘‘Graph Neural Networks: Social Networks and Beyond’’ in the Biomedical Engineering Department at Vanderbilt Unv.
9/2020: Gave an invited talk at Change++
9/2020: Our tutorial ‘‘Graph Neural Networks: Models and Applications’’ has been accepted by AAAI2021
9/2020: Preprint ‘‘Road to the White House: Analyzing the Relations Between Mainstream and Social Media During the U.S. Presidential Primaries’’
9/2020: Invited to serve as PC member for IJCAI2021
9/2020: Invited to serve as PC member for WWW2021
9/2020: Our paper ‘‘Understanding and Promoting Teacher Connections in Online Social Media: A Case Study on Pinterest.’’ is accepted at IEEE TALE2020
8/2020: Invited to serve as Proceeding Chair of KDD2021
8/2020: Our paper ‘‘Learning from Incomplete Labeled Data via Adversarial Data Generation’’ is accepted at ICDM2020
8/2020: Invited to serve as PC member for AAAI2021
8/2020: Invited to serve as PC member for GTA3@BigData2020
8/2020: Invited keynote at joint workshops Deep Learning on Graphs: Methods and Applications and Mining and Learning with Graphs at KDD2020
8/2020: Invited to serve as a reviewer for EAAI2021.
8/2020: Awarded KDD2020 Student Registration Award (and partial KDD2021 registation credit) from NSF and SIGKDD
8/2020: I joined Vanderbilt University and established the Network and Data Science (NDS) Lab