Tyler Derr

Image of Tyler 

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

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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)

News (See past news before joining VU here)

2022

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