Jiahao Chen is a Research Scientist at the Massachusetts Institute of Technology in the Computer Science and Artificial Intelligence Laboratory (CSAIL), where he works toward solving data science problems using the Julia programming language. He is interested in end-to-end big data applications tying together parallel data ingest, analytics using high performance computing, numerical linear algebra, computational random matrix theory, and parallel computing, as well as interactive visualizations.
Jiahao received his BS in Chemistry in 2002, MS in Applied Mathematics in 2008, and PhD in Chemical Physics with Computational Science and Engineering Option in 2009, all from the University of Illinois at Urbana-Champaign. He was previously a postdoctoral associate at the Massachusetts Institute of Technology, a Visiting Scholar at Ritsumeikan University (立命館大学) in Kusatsu City, Shiga Prefecture, Japan, and an acting Member of Technical Staff at DSO National Laboratories, Singapore.
View my CV in PDF format.
View recent talks I have given on Slideshare.
32 Vassar Street
Ray and Maria Stata Center
Massachusetts Institute of Technology
Cambridge, Massachusetts 02139-4307
Directions: From the Dreyfoos elevator lobby with the satellite dish, look for a window on the mezzanine floor with the Julia logo. Enter via the Tidor Group entrance marked 32-211.
Email address: my first name at
The Julia language website lists resources for students to learn about the Julia language. Have a look at course materials using Julia, resources for learning Julia, and communities of Julia users and developers near you. My GitHub account also contains Julia demos in IJulia notebook form, as well as other less-polished IJulia notebooks.
Julia questions sent to me personally may not receive immediate attention. Instead, please post your question to the julia-users mailing list, or open an issue on the appropriate GitHub repository.
If you are interested in Julia, consider attending a future meeting of the Cambridge Area Julia Users Network, or a similar user group in your area.