Background: Prior to joining Rutgers University, I was a postdoctoral researcher at the Supertech Research Group at MIT. I completed my Ph.D. in Computational Electromagnetics from McGill University in 2012 in the Computational Electromagnetics Laboratory . During my Ph.D. I have also worked as a visiting researcher in the The Parallel Computing Laboratory advised by Prof. James Demmel and in the Parallel Systems & Computer Architecture Lab .
Research: My research group, ParaMathics, works on various aspects of cloud computing, machine learning, numerical analysis, domain-specific compilers, high-performance computing, and computational biology. We develop scalable numerical methods, high-performance libraries, and domain-specific languages and compilers for high-performance and cloud computing platforms.
- The cloud computing course and its special number (SPN) waiting list are full for Fall 2017. I can not provide any more SPNs. Interested students should consider registering in future semesters.
- There are mutiple MSc, PhD, and Postdoctoral positions available in my group. Interested applicants are advised to contact me and attach their CV to proceed. More information at: Positions (PDF)
- Paper on "Avoiding Communication in Proximal Methods for Convex Optimization Problems" available at: Paper
- Paper on "Sympiler: Transforming Sparse Matrix Codes by Decoupling Symbolic Analysis" accepted at SC17. Paper
- Paper on "A Unified Optimization Approach for Sparse Tensor Operations on GPUs" accepted at Cluster17. Paper
- Paper on "Autotuning divide-and-conquer stencil computations" accepted at Concurrency and Computation. Paper
- Kazem Cheshmi wins First Place in the 2017 Grand Finals of the ACM’s Student Research Competition for our work on "Decoupling Symbolic from Numeric in Sparse Matrix Computations." The SRC Grand Finals are the culmination of a year-long competition that involved more than 300 students presenting research projects at 25 major ACM conferences.
- Maryam Dehnavi receives the NSF CRII grant on Performance-in-Depth Sparse Solvers for Heterogeneous Parallel Platforms.
- Aaditya Shukla successfully defends his MSc thesis on "Fault Tolerant Numerical Methods" and is now a data scientist at IBM Watson Research.
- Kazem Cheshmi wins First Place in the ACM CGO Student Research Competition 2017.
- Aadiya Shukla wins the best poster award in the ECE research day for: Fault Tolerant Iterative Solvers with Adaptive Reliability.
- Kazem Cheshmi becomes the Adobe Research Fellowship finalist 2017.
- Kazem Cheshmi receives the NSF travel grant for CGO/PPOPP 2017.
- Paper on "Autotuning divide-and-conquer stencil computations" accepted at Concurrency and Computation: Practice and Experience - Decision, 2017.