Welcome to Ke Wang's Home Page
Ke Wang

Staff Research Scientist at Visa Research

About me

I am currently a researcher on system security team at Visa Research, my research area lies in the intersection of Programming Language, Deep Learning and Artificial Intelligence. Previously I obtained my PhD in Computer Science from UC Davis under the supervision of Prof. Zhendong Su.

Visa Research is an emerging industrial research lab. We focus on fundamental research, encourage university collaboration, and emphasize academic publication. If you have a great publication record and are interested in pursuing a research career in our lab. Feel free to reach out at [first name](no space, comma, hyphen, etc.)[last name]@visa.com

Research Highlights

Learning semantic program embeddings is an important problem. Precise and scalable program representation enables the application of deep neural networks to a wide range of program analysis tasks. My reseach tackles this problem from three different angles: dynamic (i.e. learning from execution/symbolic traces, ICLR'18 and S&P'21), static (i.e. learning from source code, OOPSLA'20 and ICLR'20) and hybrid (i.e. learning from both, PLDI'20).

PhD Students/Post-docs/Research Scientists (co-) Advised

Professional Service

  • Program Committe: PLDI 2021, PLDI 2020, MAPL 2020
  • Review Committe: ICLR 2022, NeurIPS 2021, ICML 2021, NeurIPS 2020, USENIX Security 2019
  • Journal Reviewing: Empir.Softw.Eng. 2021, TSE 2021, JSS 2021, ASE 2020, J. Symb. Comput. 2017

Past Employment

02/2017-06/2018    Microsoft Research Redmond
Papers: PLDI 2018, ICLR 2018
Patent: Data-driven feedback generator for programming assignments
Products: Microsoft C# course, Microsoft Python Course
Post: AI for Education: Individualized Code Feedback for Students

09/2016-12/2016    Facebook Inc.

03/2016-09/2016    Microsoft Research Redmond.

09/2010-07/2012    Siemens Corporate Technology.

01/2010-06/2010    Siemens Corporate Research.


I will be reviewing for ICLR 2022.

I will be reviewing for NeurIPS 2021.

I will be reviewing for ICML 2021.

GINN has won a distinguished paper award.

I will be serving on the program committe for PLDI 2021.

GINN to appear in OOPSLA 2020.

I will be reviewing for NeurIPS 2020.

Blended program embedding to appear in PLDI 2020.

I will be serving on the program committe for MAPL 2020.

I will be serving on the program committe for PLDI 2020.

I will be joining Visa Research.

A new Microsoft Python Course shipped with the feedback technology is deployed on edX.

Search, Align and Repair for Feedback Generation to appear at PLDI 2018.

Dynamic Neural Program Embedding to appear at ICLR 2018.

ETS reached out for possible adoption of RPM generation.

I am leading a second team to adapt the feedback technology to a new Microsoft Python course to be launched after the new year.

The product is officially deployed to integrate with Microsoft C# course on edX. Here is the blog post .

I am leading a team to productionalize the research on feedback generation for MOOC.