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Alfa Heryudono

faculty

Alfa Heryudono, PhD

Professor

Mathematics

Research Website

Contact

508-999-8516

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Liberal Arts 394H

Education

2008University of DelawarePhD
2002Southern Illinois University EdwardsvilleMS
2000University of IndonesiaBS

Teaching

  • Mathematical and Computational Consulting
  • Numerical Methods for PDEs
  • Numerical Linear Algebra
  • Numerical Optimization
  • Mathematical Modeling

Teaching

Programs

Teaching

Courses

Application of knowledge discovery and data mining tools and techniques to large data repositories or data streams. This project-based capstone course provides students with a framework in which students gain both understanding and insight into the application of knowledge discovery tools and principles on data within the student's cognate area. This course is intended for data science majors only.

Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.

Students research a topic of their choice in scientific computing over two successive semesters. Research skills taught include literature and web searches, reading scientific papers, and organizing and keeping research records.

An introduction to constrained and unconstrained optimization. Numerical optimization is an essential tool in a wide variety of applications. The course covers fundamental topics in unconstrained optimization and also methods for solving linear and nonlinear constrained optimization problems.

An introduction to constrained and unconstrained optimization. Numerical optimization is an essential tool in a wide variety of applications. The course covers fundamental topics in unconstrained optimization and also methods for solving linear and nonlinear constrained optimization problems.

Research

Research awards

  • $ 74,409 awarded by OFFICE OF NAVAL RESEARCH for Data-driven and Machine-learning Optimized Hydrodynamic Models for High-Speed Planing Hull Unmanned Surface Vehicles
  • $ 438,284 awarded by Office of Naval Research for UMassD MUST IV: Learning Nonlinear Dynamical Systems from Sparse and Noisy Data: Applications to Signal Detection and Recovery
  • $ 435,393 awarded by Office of Naval Research for UMassD MUST II: Computational Strategies for Scientific Data-Driven Learning for Marine and Undersea Technology Applications

Research

Research interests

  • Radial basis function methods
  • Spectral and pseudospectral methods
  • Tear film dynamics
  • Numerical conformal mapping
  • Mathematical problems in industry

Alfa Heryudono has been with the UMass Dartmouth Department of Mathematics since 2008. He received his BS in Physics from the University of Indonesia in 2000, M.S. in Mathematics from Southern Illinois University Edwardsville in 2002, and PhD in Applied Mathematics from the University of Delaware in 2008. From 2010 until 2012, He was a Marie Curie Visiting Research Fellow at the Department of Scientific Computing at Uppsala University in Sweden. His research interests include numerical methods for function approximations and partial differential equations, scientific computing, mathematical modeling, and applied computing problems in engineering and industry. Heryudono's research is supported by Marie Curie FP7 EU, NSF, and ONR. He initiated a Mathematical and Computational Consulting (MC2) course as part of university study learning through engagement category to train students in analyzing and working on research problems solicited from local research groups and industries. His university services include the Math Dept Assessment coordinator, the Data Science MS program co-director, and the EAS PhD program co-director. Heryudono is a SIAM (Society of Industrial and Applied Mathematics) member and an associate editor of the Journal of Approximation Software (JAS).

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