Organizers

Vassilis N. Ioannidis is an Applied Scientist in AWS AI Research and Education (AIRE). He received his Ph.D. degree for his dissertation in “Robust Deep Learning on Graphs” from the University of Minnesota in 2020. He also received the Doctoral Dissertation Fellowship for his graph representation learning research. Vassilis has published more than 40 conference and journal papers. He worked from June to Dec. 2019 at MERL in graph representation learning. Since Feb. 2020, he is working at AWS in the DGL team, where he develops GNN solutions. He leads the research and development of GraphML modeling solutions that are applied in AWS and Amazon. He worked in developing Neptune ML that is a machine learning service over graph databases deployed in AWS using GNNs. He also works in large scale training of superposition of language models and GNNs for Amazon projects in information retrieval, recommendation and abuse detection.

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Zak Jost is an Applied Scientist at AWS. He previously worked in building ML solutions for fraud systems, both internal to AWS and via the customer-facing Amazon Fraud Detector service. He now helps AWS customers build GNN solutions that are integrated into their graph database via the Neptune ML service.

Minjie Wang is a Senior Applied Scientist in AWS AI Shanghai Lab. He obtained his Ph.D. degree from New York University. His research focus is the interdisciplinary area of machine learning and system including building deep learning systems with high usability and performance, applying machine learning in system optimization. He is also an open-source enthusiast; founder and major contributor of well known open source projects such as MXNet, MinPy and Deep Graph Library (DGL).

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David Paul Wipf completed my Ph.D. at the University of California, San Diego as an NSF Fellow in Vision and Learning in Humans and Machines. Subsequently he was an NIH Postdoctoral Fellow at the University of California, San Francisco developing robust Bayesian statistical models for imaging functional brain activity and for finding sparse representations using large dictionaries of candidate features. After several years at Microsoft Research in Beijing, he has now moved to a new position with the Amazon AI Lab in Shanghai, where his research focus involves generative models and graph neural networks among other things.

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