We are pleased to welcome Heemeng Foo, a seasoned engineering leader with a strong track record of building quality/test teams, growing engineering leaders, leading high profile projects, architecting test frameworks, and devising test strategy in the Media and Digital Agriculture space.
The survey paper “Machine Learning Testing: Survey, Landscapes and Horizons” by Zhang et al. (Dec 2019) is probably the most comprehensive study on the topic of Machine Learning Testing. As such, it is also long (37 pages). In this talk, Heemeng hopes to provide a sort of “Cliff Notes” of the paper so that interested parties can zoom in on the parts that interest them.
About our speaker: Heemeng Foo is a seasoned engineering leader with a strong track record of building quality/test teams, growing engineering leaders, leading high profile projects, architecting test frameworks, and devising test strategy in the Media and Digital Agriculture space. Thought leader in the use of technology in quality efforts and highly experienced in working across matrixed organizations and geographically dispersed and diverse teams. Strong foundation in Test Engineering, DevOps, Customer Support, Account Management, Project Management, and Applied R&D. Expert in all aspects of Mobile: Mobile Web, Native Apps. Keen interest in Data Science.
