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

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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. Before that, he received his PhD in Computer Science from Michigan State University in 2020 under the supervision of Dr. Jiliang Tang. He has published 50+ papers in highly ranked journals and top conference proceedings, with h-index 30 and i10-index 55 (Google Scholar).

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 neurodiversity. He has mentored his Ph.D. students to receive numerous honors and awards, including Vanderbilt’s C. F. Chen Best Paper Award in 2022 and Runner-Up Award in 2023, the sole recipient of Vanderbilt’s Graduate Leadership Anchor Award for Research in 2023, Finalist in Vanderbilt’s Three Minute Thesis (3MT) Competition in 2023, 1st place in Vanderbilt’s AI Showcase in 2024, and Vanderbilt’s Outstanding Doctoral Student Award in 2024. They have also received the NVIDIA Academic Hardware Grants in 2022 and the DOE Computational Science Graduate Fellowship in 2024.

He is actively involved in the research community, both through publishing extensively at top conferences and serving as a reviewer and committee member (AC/SPC/PC), earning three Best Reviewer Awards. His research has also been recognized with the Best Paper Award at the GLFrontiers Workshop at NeurIPS’23, the Best Student Poster Award at SDM’19, and Paper Digest selections for top-10 Most Influential Papers at CIKM’22 and WWW’23. He has served on organizing committees for major international conferences, including CIKM, DSAA, KDD, SDM, and WSDM, and co-founded the Machine Learning on Graphs (MLoG) Workshop series, which has run for six iterations. In addition, he serves as an Associate Editor for Tsinghua Science and Technology, ACM Transactions on Knowledge Discovery from Data, and IEEE Transactions on Big Data.

Passionate about education and dissemination, he has delivered tutorials on Graph Neural Networks at AAAI, CIKM, KDD, and SDM, and given numerous invited talks at places including the ACM Web Conference’s Knowledge Graph Day, Oak Ridge National Laboratory’s Core Universities AI Workshop, Tsinghua University's Foundation Model Research Center, Nanyang Technological University (NTU), and the Max Planck Institute for Mathematics in the Sciences (MPI MiS).

Tyler has been recognized for research excellence through several prestigious honors, including the NSF CAREER Award (2023), an NVIDIA Academic Grant Program Award (2024), and selection for the Visiting Faculty Research Program at AFRL/RI (2023). Additionally, he has received multiple Vanderbilt awards for excellence in teaching and mentorship, including the School of Engineering’s Fall 2020 Teaching Innovation Award, the 2024 Provost Immersion Grant for Faculty, and the 2025 Career Catalyst Impact Award.

Research Interests

data mining, machine learning, social network anlaysis, recommender systems, deep learning on graphs, responsible and trustworthy AI, and interdisciplinary social good applications (e.g., drug discovery, education, political science, and neurodiversity)

[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

  • Machine Learning on Graphs in the Era of Artificial General Intelligence Workshop at KDD'25 (Link to Details)

    • Workshop Organizer along with Yu Wang, Yu Zhang, Zhichun Guo, Harry Shomer, Haoyu Han, Nesreen Ahmed, Mahantesh Halappanavar, and Jiliang Tang

    • Submission Deadline: May 31th, 2025

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Recent News (before 2024 can be seen here)

2025

2024