• Ph.D. student at CMU CSD since Fall, 2012.
  • Advised by Garth A. Gibson and Eric P. Xing.
  • Developing distributed frameworks for scaling out machine learning training applications. My work on the Bösen parameter server is part of the Petuum project, which is now a Pittsburgh-based startup.
  • Generally interested in distributed systems, database systems and machine learning applications.
  • B.S. in Computer Engineering, Minor in Mathematics, with Distinction from Purdue University, West Lafayette.
  • CV
Email: jinlianw at cs dot cmu dot edu
Cell: (765) 427-5257
Gates-Hillman Center (GHC) 7505
Computer Science Department
Carnegie Mellon University

Research Summary

My doctoral research is focused on enabling machine learning researchers and practioners to efficiently train large and complex models with big data on distributed systems. After spending a few years on developing distributed systems to make machine learning programs run fast and efficiently, I am now working on automatic parallelization to compile serial machine learning programs to distributed programs to take advantage of the machine learning specific system optimizations.

Selected Publications