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Daniel Wong
Growth @ Meta
Daniel Wong is a final year PhD student in the Computer Science Department at Carnegie Mellon University (CMU).12 He is a member of the Parallel Data Laboratory and is advised by Professor Greg Ganger.15
Academic Background
Daniel received his BA in Computer Science from the University of Cambridge before pursuing his doctoral studies at CMU.1 His LinkedIn username is danielwong.4
Research Focus
Daniel's research interests lie at the intersection of machine learning and scalable distributed systems.1 His current thesis work focuses on machine learning for flash caching.1 Previously, he has worked on:
- High-performance distributed systems with next-generation storage
- Systems for efficient machine learning
Professional Experience
During his doctoral studies, Daniel has gained valuable industry experience through internships at prominent tech companies:
- At Google, he worked on scheduling for model parallelism in TensorFlow
- At Dropbox and Facebook, he focused on consistency in large-scale distributed storage1
Achievements
Daniel has received recognition for his work in cybersecurity:
- Winner of the Cybersecurity Challenge Singapore
- Participated in the Cambridge 2 Cambridge cybersecurity challenge4
His final year research dissertation at the University of Cambridge was also "highly commended".4
Contact Information
For those interested in reaching out to Daniel or learning more about his work:
- Office: Gates and Hillman Centers, Room 9003 (CMU)
- Email: wonglkd@cmu.edu3
Daniel maintains an active presence in the academic community, with publications available on Google Scholar and a personal website where he shares more information about his research and background.
