E r i c     P o l i z z i

photo polizzi

Associate Professor
Department of Electrical and Computer Engineering
University of Massachusetts, Amherst

Phone: (413) 577-0861
Office: Marcus 201C
polizzi @ ecs.umass. edu

My research group and I are conducting interdisciplinary research activities at the intersection between advanced mathematical techniques, parallel numerical algorithms, and computational nanosciences. We aim at developing new computational methodologies and algorithmic paradigms for addressing the fundamental problems of accuracy, robustness and parallel scalability in large-scale first-principle electronic calculations with applications ranging from quantum chemistry and material sciences, to solid-state electronics and nanotechnology.
Such realistic quantum simulations have also motivated the design of novel numerical algorithms that are both capable of processing a considerable amount of generated data and achieving significant parallel scalability on modern high end computing architectures. Our innovative activities in numerical algorithms for solving linear systems and eigenvalue problems have then led to the development of the world fastest banded system solver SPIKE (2003-present), and the groundbreaking FEAST algorithm and FEAST solver (2008-present). SPIKE and FEAST which are both free software, can exploit the capabilities of the current and upcoming parallel architectures with the perspectives of major broader impacts in many areas of Science and Engineering.

R E S E A R C H     I N T E R E S T S

    Computational Nanosciences:
  • O(N) electronic structure calculations using all-electron first-principle Density Functional Theory (DFT)
  • First-principle electronic ground state and excited state calculations
  • Real-time TDDFT and electronic spectroscopy: x-ray, UV, visible, THz
  • Quantum transport calculations and non-equilibrium nanoscale physics
  • Simulations of complex molecular systems, emerging nanostructure materials and nanoelectronic devices

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    Scientific Computing:
  • Continuous (PDE-based) mathematical modeling and numerical methods (non-linear models, domain decomposition, Finite Element Method)
  • Numerical linear algebra, data analytics (matrix computations): linear systems and eigenvalue problems
  • Parallel numerical algorithms and high performance computing

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