I’m an Assistant Professor at UCLA. I optimize modern data systems with advanced techniques from programming languages and databases. If you want to join my lab, please read this before contacting me. I’m very lucky to work with many brilliant students:
| PhD | Zheng Luo, Sai Achalla (co-advised w/ Sam Kumar) |
| MS | Alan Yao, Jiahe Yan |
| UG | Paul Zhang, Daniel Yang, Tom Binford, Vishal Yathish |
[SIGMOD’23] SIGMOD Research Highlight Award We propose free join, a new join algorithm unifying and generalizing traditional binary joins with worst-case optimal joins. Free join brings the best of both worlds, and outperforms both binary join and WCOJ in practice.
[EGRAPHS’22] We tease out deep connections among e-graphs, finite-state tree automata, and version space algebra. By fusing together powerful ideas from these different perspectives, we gain orders-of-magnitude speedup and discover a new technique for automated proofs.
[PODS’22] Best Paper Datalogo is a query language that generalizes Datalog. It can express a wide range of computation from shortest paths to network centrality. In the paper we study its convergence behavior.
[SIGMOD’22] Invited to SIGMOD Record We also developed a query optimizer for Datalogo based on program synthesis.
[POPL’22] Using advanced join algorithms, we made pattern matching in a rewrite system asymptotically faster.
[MLSys’21] Tensat is an optimizer for deep learning inference using equality saturation. It achieves state-of-the-art inference speed with very fast compilation.
[POPL’21] Distinguished Paper egg is the rewrite engine underlying a new class of optimizers including Tensat and SPORES (see below). It implements an efficient algorithm for equality saturation.
[OOPSLA’21] Distinguished Paper We used egg to invent rewrite rules that are in turn given to egg itself for equality saturation.
[VLDB’20] SPORES is an optimizer for large scale linear algebra. It transforms linear algebra code through the powerful abstraction of relational algebra.
