Teachings and Codes

Teachings

Graduate course:

• Data driven modeling for engineers and designers

• ETH Zurich

• Lecture notes and codes

  • • https://github.com/sevamoo/data_driven_modeling_2018

    • https://github.com/sevamoo/data_driven_modeling_2017

    • https://github.com/sevamoo/data_driven_modeling_2016

Undergraduate Course:

• Urban modeling with Big Data and machine learning

• Southeast University (Nanjing), April 2019

• Lecture notes and codes

  • https://github.com/sevamoo/SEU_2019

Selected invited talks

• Computational Science Lab, Informatics Institute, university of amsterdam UvA, January 2020

• The Alan Turing Institute, November 2019

• UCL, School of Architecture, November 2019

• Open Data Science Meetup Zurich, May 2019

• South East University, China, April 2019

• Institute of real estate and financial services, Lucerne University of Applied Sciences, Switzerland, April 2019

• Foster and Partners, London, February 2019

• School of Engineering, Newcastle University, February 2019

• Polyhedral Structures Laboratory, School of Design, University of Pennsylvania, November 2018

• Department of Architecture, TU Vienna, November 2018

• Swiss Federal Institute of Aquatic Science and Technology, EAWAG, October 2018

• Green peace Switzerland, May 2018

• Department of Urbanism, TU-Delft, The Netherlands, March 2018

• School of Computing, National University of Singapore (NUS), Singapore, March 2018

• Research Colloquium, Chair of Structural Design, ETH Zurich, Uitikon, Switzerland, December 2017

• Machine intelligence summit, Amsterdam, June 2017

• Department of architecture, TU Vienna, March 2017

• PyData Zurich, February 2017

• Chair of information architecture, ETH Zurich, November 2016

• School of architecture, civil and environmental engineering, EPFL, July 2015

• Future cities lab, ETH- Singapore Centre, April 2015

• MIT CENSAM, Singapore, June 2014

• SAP Singapore, September 2013

Codes and open source projects

• Github repository: https://github.com/sevamoo

• Open source contributions:

  • SOMPY (A Python implementation of Self Organizing Map (SOM) algorithm, https://github.com/sevamoo/SOMPY)