EAI-KDD'24 - Keynotes

Invited Keynote Speakers

	James Caverlee, Texas A&M University Short bio: Dr. James Caverlee is a Professor in the Department of Computer Science and Engineering at Texas A&M University. His research research focuses on connecting people to information, with an emphasis on algorithms and systems that are trustworthy, resilient, and responsible. His work has been supported by an NSF CAREER award, an AFOSR Young Investigator Award, a DARPA Young Faculty Award, and grants from Google, Amazon, AFOSR, DARPA, and the NSF. He received the 2022 SIGIR Test of Time Award Honorable Mention, the 2020 CIKM Test of Time Award, plus several departmental and college-level teaching awards.
	Manish Nagireddy, IBM Research Short bio: Manish Nagireddy is a Research Software Engineer at IBM Research and the MIT-IBM Watson AI Lab. His main research goal is to build trustworthy AI solutions. His research interests encompass several areas in machine learning and artificial intelligence, from classical ML methods to natural language processing and the generative context. Manish’s work has been recognized in a variety of venues and communities, from AAAI to NeurIPS to FAccT to CHI and more. Currently, Manish focuses on use-case-centered algorithmic auditing and evaluation in the context of large language models. He is a core maintainer for many open-source trustworthy AI toolkits - AI Fairness 360, AI Explainability 360, and Uncertainty Quantification 360. Before joining IBM Research, Manish graduated from Carnegie Mellon University with a B.S. in statistics, machine learning, and computer science.
	Tyler Derr, Vanderbilt University 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 directs the Network and Data Science (NDS) lab, focusing on data mining, machine learning, social network analysis, deep learning on graphs, and data science for social good, with applications in drug discovery, education, political science, and autism research. Dr. Derr has organized numerous international conferences, co-founded the Machine Learning on Graphs Workshop, and delivered tutorials on Graph Neural Networks at major conferences, including KDD’20, AAAI’21, and SDM’24. He serves as Associate Editor for several journals and has received prestigious awards, including the NSF CAREER Award in 2023 and the Visiting Faculty Research Program at AFRL/RI. He was also honored with the 2020 Teaching Innovation Award and the 2024 Provost Immersion Grant at Vanderbilt University.