[jie chen's photo]Jie Chen

Research Staff Member
IBM Thomas J. Watson Research Center
1101 Kitchawan Road
Yorktown Heights, NY 10598, USA
Office phone: +1 (914) 945-1829
Email: chenjie -AT- us.ibm.com

My research interests root in matrices, fundamental mathematical objects that are not numbers, but tables of numbers and also mappings between two universes. What I study are as deep as the theory and the computation, as wide as numerical analysis, scientific computing, and parallel processing, and as applied as statistics and machine learning. My work is heavily convoluted with data, because numerical and scalable computations play a crucial role there. Currently, my efforts focus on linear-complexity computations of large dense matrices defined by kernels. In practice, they entail the most common structure for matrices that are both large and dense. By "large," we mean a size of billion by billion and beyond. Linear complexity is the right, if not the only, way to match the theoretical appeals of matrix methods with the Moore's law progress of computer technology and the surge of data and information.

I work on deep learning for a living.