IRTG Modern Inverse Problems (MIP)

Contact

Aachen Institute for Advanced Study
in Computational Engineering Science (AICES)
RWTH Aachen
Schinkelstr. 2
52062 Aachen

Office: Room 430
Phone: +49 241 80 99141
Email: sankaran@aices.rwth-aachen.de

Education

7/2019 – Current: Ph.D. Candidate, IRTG at RWTH Aachen

10/2014 – 05/2017: Master of Science in Simulation Sciences, RWTH Aachen University, Germany

8/2010 – 4/2014: Bachelor of Industrial Engineering, College of Engineering Guindy, Anna University Chennai, India

Professional Career

3/2016 – 4/2017: Working student at Informatik 6, RWTH Aachen University, Germany

9/2015 – 2/2016: Working student at Graduate School AICES, RWTH Aachen University, Germany

7/2015 – 12/2016: Working student at JARA HPC, RWTH Aachen University, Germany

Research Interests

• Machine Learning
• High Performance Computing
• Operations Research

Theses

• Analyses of convolutional neural networks for automatic taggig of music tracks (Master’s Thesis, RWTH Aachen, Germany, 2017).

Publication

1. Benchmarking the Linear Algebra Awareness of TensorFlow and PyTorch
   A. Sankaran, NA. Alashti, C.Psarras and P. Bientinesi
   to appear in IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPS Workshop: iWAPT 2022
   Preprint arXiv:2202.09888
2. Performance Comparison for Scientific Computations on the Edge via Relative Performance
   A. Sankaran and P. Bientinesi
   IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW),
   2021, pp. 887-895
   doi: 0.1109/IPDPSW52791.2021.00132.
3. Discriminating Equivalent Algorithms via Relative Performance
   A. Sankaran and P. Bientinesi
   Preprint, arXiv:2010.07226
4. Machine Learning based Performance Modelling
   A. Sankaran and P. Bientinesi
   Proceedings of the 2020 Joint Workshop of the German Research Training Groups in Computer Science, Dagstuhl, 2020, pp.154

Kategorie: Student CVs
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