Tyler Derr

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Assistant Professor
Computer Science, Data Science
Department of CS, Data Science Institute
Vanderbilt University

Network and Data Science (NDS) Lab

Email: Tyler (dot) Derr (at) vanderbilt (dot) edu
Office: 4030 Sony Building
Mail: 400 24th Ave S Rm 254, Nashville, TN 37212

Google Scholar

Short Bio

Dr. 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 received his PhD in Computer Science from Michigan State University in 2020 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 complete his MS in Computer Science at The Pennsylvania State University in 2015 and dual BS in Computer Science and Mathematical Sciences at The Pennsylvania State University in 2013.

Tyler directs the Network and Data Science (NDS) lab, which conducts research in the areas of data mining and machine learning, with emphasis on social network analysis, deep learning on graphs, and data science for social good with applications in drug discovery, education, political science, and autism research. His PhD students received Vanderbilt's C. F. Chen Best Paper Award in Computer Science in 2022 and Runner-Up Award in 2023. He is actively involved in top conferences in his field, both in terms of publishing and serving as an SPC/PC member, while receiving recognition such as the Best Student Poster Award at SDM’19 and Best Reviewer Awards at ICWSM’19 and ’21, as well as WSDM’22. He has contributed to the organization of international conferences, including serving as the Publicity Co-Chair of KDD’22 and ’23, Doctoral Consortium Co-Chair of WSDM’22, Student Travel Awards Co-Chair of WSDM’24, and Proceedings Co-Chair of KDD’21. Being passionate about sharing knowledge, he has co-organized multiple workshops including Machine Learning on Graphs (MLoG) Workshop at WSDM’22 and ’23 along with at ICDM’22 and ’23; he has delivered tutorials on Graph Neural Networks at KDD’20 and AAAI’21. He serves as Associate Editor for Elsevier Big Data Research and Topic Editor in Frontiers in Big Data. Additionally, he was honored with the Fall 2020 Teaching Innovation Award from the School of Engineering at Vanderbilt University, highlighting his dedication to exceptional teaching. Tyler received the prestigious NSF CAREER Award in 2023.

Research Interests

data mining, machine learning, mining and learning on graphs, social network anlaysis, graph neural networks, ethical and responsible AI, recommendation systems, data science for social good (e.g., drug discovery, education, political science, and autism research)

[Open positions]
I am recruiting PhD students to work with us in the NDS Lab on topics in our general interests (see NDS Lab research interests to the right).
Master's and undergraduate students within Vanderbilt University and visiting scholars are also welcome. Please feel free to email me.
Please see here for position details.

Call for Papers

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News (See past news before joining VU here)





  • 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