Nicholas Gao

Technical University of Munich
Department of Informatics - I26
Boltzmannstr. 3
85748 Garching b. München
Germany

Room: 00.11.056
E-Mail: gaoni(at)in.tum.de

GitHub: n-gao
Google scholar: Google scholar

Research Focus

• Machine learning for graphs and molecules
• Machine learning-based ab-initio quantum chemistry
• Graph neural networks

Selected Publications

• Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
  Nicholas Gao, Stephan Günnemann
  Conference on Neural Information Processing Systems (NeurIPS), 2024 (oral)
• Generalizing Neural Wave Functions
  Nicholas Gao, Stephan Günnemann
  International Conference on Machine Learning (ICML), 2023
• Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
  Nicholas Gao, Stephan Günnemann
  International Conference on Learning Represetation (ICLR), 2023
• Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
  Nicholas Gao, Stephan Günnemann
  International Conference on Learning Represetation (ICLR), 2022 (spotlight)
• Fast and Flexible Temporal Point Processes with Triangular Maps
  Oleksandr Shchur, Nicholas Gao, Marin Biloš, Stephan Günnemann
  Conference on Neural Information Processing Systems (NeurIPS), 2020 (oral)

For a full list, see Google scholar.

Education

• 2017 - 2020: M.Sc. Computer Science, Technical University of Munich
  • Master's thesis: Fast and Flexible Temporal Point Processes using Triangular Maps
  • top 10% - passed with high distinction
• 2014 - 2017: B.Sc. Computer Science, Technical University of Brunswick
  • Bachelor's thesis: Visualizing the IoT with Mixed Reality
  • top 10%

Academic Honors and Awards

• 2019: Deutschlandstipendium awarded by the Technical University of Munich
• 2016: Deutschlandstipendium awarded by the Technical University of Brunswick