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Daniel Wong received a BA from the University of Cambridge, and is a PhD student in Carnegie Mellon University's Computer Science Department. Daniel's research interests are in ML for Systems and scalable distributed systems. Daniel is a member of the CMU Parallel Data Laboratory and currently works on ML for caching. Daniel has also worked on consistency for large-scale distributed systems during internships at Dropbox and Facebook, and on scheduling for model parallelism in TensorFlow at Google.

Last updated: June 2020

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Daniel Wong is a 6th-year CSD PhD student advised by Professor Greg Ganger. He received his BA degree in Computer Science from the University of Cambridge. His current research focuses on ML for caching systems. Previously, he worked on high performance distributed systems with next-generation storage, and systems for efficient machine learning.

Last updated: Oct 2022

More details: Résumé | LinkedIn