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Introductory presentation > Basic info Outline Basic info 1 Previous education 2 Promotion research 3 Albert-Jan Yzelman Introductory presentation > Basic info Basic info Name: Albert-Jan Yzelman Started: September 2007 Age: 23


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Introductory presentation > Basic info

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Previous education

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Promotion research

Albert-Jan Yzelman

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Introductory presentation > Basic info

Basic info Name: Albert-Jan Yzelman Started: September 2007 Age: 23 Hometown: Duiven (near Arnhem) Supervisor: Rob Bisseling Research area: Combinatorial Scientific Computing Hobbies: Music, Anime, Pool, Games, Reading, Movies, Photography

Albert-Jan Yzelman

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Introductory presentation > Previous education

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Education High school, Duiven, 2001

  • BSc. Computing Sciences, Utrecht, 2007
  • BSc. Mathematics, Utrecht, 2007
  • MSc. Scientific Computing, Utrecht, 2007

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Bachelor’s thesis Radiosity; Uses physical relations for energy transmission for global illumination Subdivide surfaces into equally-sized squares Derive a linear system Ax = b to calculate the brightness of each square Solve this system in parallel

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Figure: Sample radiosity-rendered scene. Size of the dense matrix A is 7 · 26 × 7 · 26; thus holding over 200000 elements.

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Figure: Sample radiosity-rendered scene. Size of the dense matrix A is 7 · 214 × 7 · 214; thus holding over 13 million elements.

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Master’s thesis R-tree project Internship at Alten Nederland, a technical consultancy group

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Master’s thesis R-tree project Internship at Alten Nederland, a technical consultancy group Improve data access and storage efficiency of Shell’s oil reservoir simulation software

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Introductory presentation > Previous education Albert-Jan Yzelman

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What are R-trees?

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Combinatorial Scientific Computing Supports the more general area of Scientific Computing by researching common problems such as: Load balancing Mesh generation Sparse matrix operations

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Combinatorial Scientific Computing The matrix partitioner Mondriaan (by Rob Bisseling) will be enhanced and applied on secondary problems; Less communication in sparse matrix computations Clustering Improving cache effiency during matrix computations

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✁ ✁ ✁ ✂✁✂ ✂✁✂ ✂✁✂ ✄✁✄✁✄✁✄ ✄✁✄✁✄✁✄ ✄✁✄✁✄✁✄ ☎✁☎✁☎✁☎ ☎✁☎✁☎✁☎ ☎✁☎✁☎✁☎ ✆✁✆ ✆✁✆ ✆✁✆ ✝✁✝ ✝✁✝ ✝✁✝ ✞✁✞ ✞✁✞ ✞✁✞ ✟✁✟ ✟✁✟ ✟✁✟ ✠✁✠ ✠✁✠ ✠✁✠ ✡✁✡ ✡✁✡ ✡✁✡ ☛✁☛ ☛✁☛ ☛✁☛ ☞✁☞ ☞✁☞ ☞✁☞

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✁ ✁ ✁ ✂✁✂ ✂✁✂ ✂✁✂ ✄✁✄ ✄✁✄ ✄✁✄ ☎✁☎ ☎✁☎ ☎✁☎ ✆✁✆ ✆✁✆ ✆✁✆ ✝✁✝ ✝✁✝ ✝✁✝ ✞✁✞ ✞✁✞ ✞✁✞ ✟✁✟ ✟✁✟ ✟✁✟ ✠✁✠ ✠✁✠ ✠✁✠ ✡✁✡ ✡✁✡ ✡✁✡ ☛✁☛✁☛ ☛✁☛✁☛ ☛✁☛✁☛ ☞✁☞✁☞ ☞✁☞✁☞ ☞✁☞✁☞ ✌✁✌ ✌✁✌ ✌✁✌ ✍✁✍ ✍✁✍ ✍✁✍

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✁ ✁ ✁ ✂✁✂ ✂✁✂ ✂✁✂ ✄✁✄✁✄✁✄ ✄✁✄✁✄✁✄ ✄✁✄✁✄✁✄ ☎✁☎✁☎✁☎ ☎✁☎✁☎✁☎ ☎✁☎✁☎✁☎ ✆✁✆ ✆✁✆ ✆✁✆ ✝✁✝ ✝✁✝ ✝✁✝ ✞✁✞ ✞✁✞ ✞✁✞ ✟✁✟ ✟✁✟ ✟✁✟ ✠✁✠ ✠✁✠ ✠✁✠ ✡✁✡ ✡✁✡ ✡✁✡ ☛✁☛ ☛✁☛ ☛✁☛ ☞✁☞ ☞✁☞ ☞✁☞

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Combinatorial Scientific Computing Clustering is certainly one of the more interesting subjects, due to its many possible applications, including: Genomics; mapping DNA chromosomes to hereditary diseases Finding densely linked webpages (web spam, improving search engines)

Albert-Jan Yzelman