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Scientific Computing and Data Science Seminar

We intend the terms scientific computing and data science to be broadly defined and inclusive. Topics of interest include but are not limited to:

  • Novel numerical methods, numerical analysis, high-performance computing, parallel algorithms, and application problems that involve numerical challenges.
  • Machine learning algorithms, deep learning and neural networks, applied/predictive modeling with real-world data, data-enabled science, dimensionality reduction, Bayesian methods, natural language processing, and computational statistics.

During Fall 2022 we will meet on Thursdays, 3:00-4:00pm in ACS 362B. Alternatively, you may also join via Zoom.

This seminar is part of the RTG theme “Scientific Computing and Data Science”. If you have questions, please contact Prof. Changho Kim ( or Dr. Valentin Dallerit (

Schedule Spring 2022

  • Sep 1: Harish Bhat - Intro to JAX
  • Sep 8: John Butcher (University of Auckland, New Zealand) - B-series and Applications
  • Sep 15: Changho Kim - Demystifying Stochastic Integrals
  • Sep 22: Changho Kim - Demystifying Stochastic Processes

Schedule Spring 2022

  • Jan 27: Enrique Mercado
  • Feb 3: Harish Bhat
  • Feb 10: Jocelyn Ornelas Munoz
  • Feb 17: Harish Bhat
  • Feb 24: Harish Bhat
  • Mar 3: Ali Heydari
  • Mar 10: Adam Binswanger
  • Mar 17: Majerle Reeves
  • Mar 24: Spring Recess
  • Mar 31: Tanya Tafolla
  • Apr 7: Hardeep Bassi
  • Apr 14: Valentin Dallerit
  • Apr 21: Kevin Collins
  • Apr 28: Matthew Blomquist

Previous seminars