Daniel (Lin-Kit) Wong

Hi! I am a final year (7th) PhD student at Carnegie Mellon University. I am advised by Greg Ganger. I am a member of the Parallel Data Laboratory & Computer Science Dept.

I am a systems builder and designer with a focus on distributed systems and ML.

Résumé (Mar ‘24) | Publications (10 papers, 2 patents):

Other interests: Security, Bioinformatics [BMCGenomics13], Neuroscience, Cloud Computing.

I'm always keen to talk about research. Reach out if you have problems, insights, or data to share! Details at bottom.

Feb ‘24: I presented Baleen at FAST 2024 (PDF, Code, More).

PhD Research (Publications)
  • Ongoing: ML for Flash Caching:
    • Automated drift mitigation in caching Spring ‘24 - Present
    • ML for eviction, placement, optimizing for peak Spring ‘23 - Present
    • Baleen: ML for flash admission and prefetching Spring ‘20 - Spring ‘23
      Daniel Lin-Kit Wong, Hao Wu, Carson Molder, Sathya Gunasekar, Jimmy Lu, Snehal Khandkar, Abhinav Sharma, Daniel S. Berger, Nathan Beckmann, Greg Ganger - FAST 2024
    • Students: if you're interested in ML for caching, email me! Some project ideas:
      • Online version of Baleen (track episodes on-the-fly, adaptive score cut-off)
      • Using episodes to design eviction & other caching policies
      • Baleen for CDN and key-value caches
  • Past work - ML and Systems:
  • Past projects - Distributed Systems:
  • Past projects - Dimensionality reduction on neuroscience datasets:
    • 10-708 (PGM) project: Stitching neural population recordings (electrophysiological) from different days. Spring ‘20
      Adam Smoulder, Sami Horn, Daniel Wong
  • Keen to explore:
    • Applications of clustering & dimensionality reduction for time series and graphs.
      I'm keen to explore interpretable machine learning methods that find correlations in time series and graphs, with an especial interest in visualizations, interpretability and causality.
    • Areas I have a soft spot for: neuroscience, systems security, HCI, psychology.
  • Past explorations - Failures in Systems (keen to revisit with new data)
    • Transient failures (grey failures). Fall ‘19
      How can we balance initiating recovery quickly and overreacting to transient failures?
    • Affordable robustness to failures in distributed storage. Spring ‘19 - Fall ‘19

      3-way cross-region replication is expensive and slow. It helps mitigate rare risks like a hurricane taking out a data center, but why pay that price for common events like equipment failures? Can we detect and predict correlated failures?

      Poster on theoretical modelling on transient failures. Despite strong industry interest, we lacked real world data. Email me if you have datasets to share!
Teaching & Coursework at CMU
Other highlights

I'm a tinkerer at heart. I am always on the lookout for novel challenges to work on; I optimise for learning and doing meaningful, impactful work. I bask in the energy of synergistic collaborations, and the opportunity they give me to wade into new domains and learn from cool people.

I'm a software engineer and have a relentless urge to automate and optimize all parts of my work process.

I enjoy musicals, singing and karaoke (car karaoke setup), cooking, Singaporean food, skiing & snowboarding, gliding, long scenic drives (and walks), waterfalls, baking, rock climbing, ice skating, computer games, scuba diving, and last but not least, good nigiri (including making it). I did my undergraduate studies at the University of Cambridge and am a member of Churchill College. I grew up in Singapore, am a 华中子弟, and am a proud alumnus of my high school computer club EC3 (where I learnt to code and hack stuff together.)

Get in touch: | [same username]@cmu.edu | LinkedIn | Facebook | Twitter | Mastodon | Keybase | PGP key

My stuff: Quora | GitHub | Google Scholar

More about me: Publications | Biography