Jens Deussen

Dr. rer. nat.

Contact Details

• Mail 
  Informatik 12: Software and Tools for Computational Engineering
  RWTH Aachen University
  D-52056 Aachen, Germany
• Office: Seffenter Weg 23, 52074 Aachen
• Room: 229
• Phone: +49 (0)241/80 29224
• Email: deussen (at) stce.rwth-aachen.de
• Researcher at STCE: since 2015
• Office Hours: on request

Research

• Interval-adjoints in global optimization
• Subdomain separability
• Interval-adjoint significance analysis for approximate/unreliable computing (SCoRPiO project)
• AD in differential algebraic equation with optimization criteria solvers
• Hybrid MPI/OpenMP parallel computation of higher derivatives
• Sparse higher derivatives

Publications:

• 2023
  • Deussen, J., Hüser, J., Naumann, U.: Numerical simulation of differential-algebraic equations with
    embedded global optimization criteria. Preprint on https://arxiv.org/abs/2305.05288 (2023)
  • Deussen, J., Naumann, U.: Subdomain separability in global optimization. J Glob Optim 86, 573–588 (2023). https://doi.org/10.1007/s10898-022-01265-6

• 2021 
  • Deussen, J.: Global Derivatives. Dissertation, RWTH Aachen University, Aachen (2021).
• 2020
  • Deussen, J., Naumann, U.: Subdomain separability in global optimization. Preprint on arXiv. https://arxiv.org/abs/2010.09591 (2020)
  • Deussen, J., Hüser, J., Naumann, U.: Toward global search for local optima. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds.) Operations Research Proceedings 2019, pp. 97–104. Springer, Cham (2020)
• 2019
  • Deussen, J., Naumann, U.: Efficient computation of sparse higher derivative tensors. In: Rodrigues J. et al. (eds) Computational Science – ICCS 2019. ICCS 2019. Lecture Notes in Computer Science 11536, pp. 3–17. Springer, Cham (2019)
  • Deussen, J., Naumann, U.: Discrete interval adjoints in unconstrained global optimization. In: Le Thi H., Le H., Pham Dinh T. (eds.) Optimization of Complex Systems: Theory, Models, Algorithms and Applications, pp. 78–88. Springer, Cham (2019)
• 2018
  • Deussen, J., Mosenkis, V., Naumann, U.: Fast estimates of Greeks from American options: a case study in adjoint algorithmic differentiation. Technical Report AIB-2018-02, RWTH Aachen University, Aachen (2018)
• 2016
  • Vassiliadis, V., Riehme, J., Deussen, J., Parasyris, K., Antonopoulos, C.D., Bellas, N., Lalis, S., Naumann, U.: Towards automatic significance analysis for approximate computing. In: Proceedings of CGO 2016 the 14th International Symposium on Code Generation and Optimization, pp. 182–193. ACM, New York, NY (2016)
  • Deussen, J., Riehme, J., Naumann, U.: Automation of significance analyses with interval splitting. In: Joubert G. R. et al. (eds) Parallel Computing: On the Road to Exascale, pp. 731–740. IOS Press, Amsterdam (2016)

Talks:

• 2023
  • Invited Talk at ADOPT meeting, Virtual: Subdomain Separability in Global Optimization
• 2022
• Invited Talk at NAG, Virtual: Global Derivatives
• 2020 
  • 23rd European Workshop on Automatic Differentiation, Virtual:
    Generalization of Separability for Optimization Problems
• 2019 
  • 6th World Congress on Global Optimization, Metz, France:
    Discrete Interval Adjoints in Unconstrained Global Optimization 
  • International Conference on Computational Science, Faro, Portugal:
    Efficient Computation of Sparse Higher Derivative Tensors
•  2018
  • 18th SIAM Conference on Parallel Processing for Scientific Computing, Tokyo, Japan:
    Adjoint Methods for Stochastic Approximate Computing
  • SIAM Workshop on Combinatorial Scientific Computing, Bergen, Norway:
    Recursive Compression of Sparse Derivative Tensors
• 2017
• 3rd Workshop on Approximate Computing, Stockholm, Sweden:
  Compression of Higher Derivative Tensors in Stochastic Significance Analysis
• Aachen Conference on Computational Engineering Science, Aachen, Germany:
  On the Efficient Computation of Higher Derivative Tensors (Poster)

• 2016
  
  • 19th European Workshop on Automatic Differentiation, Kaiserslautern, Germany:
    dco/scorpio: An Interval-Adjoint Significance Analysis Tool
  • 2nd Workshop on Approximate Computing, Prague, Czech Republic:
    Interval-Adjoint Significance Analysis: A Case Study
  • SIAM Student Chapter, Seminar Series on Hot Topics in Applied Mathematics, Aachen, Germany:
    Greeks for American Options by Adjoint Algorithmic Differentiation
• 2015
  • Mini-Symposium on Energy and Resilience in Parallel Programming, Edinburgh, Scotland:
    Automation of Significance Analyses with Interval Splitting
  • Workshop on Approximate Computing, Paderborn, Germany:
    Interval Derivative Based Significance Analysis
  • 18th European Workshop on Automatic Differentiation, Paderborn, Germany:
    Fast Delta-Estimates for American Options by Adjoint Algorithmic Differentiation

Teaching:

• Advanced C++
• Introduction to Programming (C++)
• Computational Differentiation
• Combinatorial Problems in Scientific Computing
• Software Engineering Lab