My research interests include GPU computing, computer architecture, and machine learning. I have been designing scalar-vector GPU architectures to take advantage of compiler- and architecture-level scalar opportunities in GPGPU applications for better performance and power efficiency.
I also have been spending a great deal of time on GPU architecture modeling and simulation. I am a lead developer of NVIDIA Fermi/Kepler simulator on Multi2Sim simulation framework. Also, I was working on the modeling of a complete tessellation pipeline at Samsung Advanced Processor Lab.
Currently, I am working with IBM Research on big data analytics and very large scale machine learning with GPUs.
I am teaching CUDA programming and GPU architecture to undergraduate and graduate students at Northeastern University in Spring 2016.
I am the teaching assistant for a graduate course on Operating Systems at Northeastern University in Spring 2016.
I taught OpenCL programming and GPU architecture to undergraduate students at Northeastern University in Spring 2015.
I assisted Professor Kaeli to teach GPU programming to undergraduate students at Northeastern University in Spring 2011.