Lisa Hamada

Title

Research Scientist

Bio

Lisa Hamada is a Research Scientist at IBM Research - Tokyo.

Apr 2021 -, Researcher in IBM - Research (Accelerated Material Discovery)

Apr 2019 -, Researcher in IBM - Research (Accessibility & Healthcare)

Sep 2016 - Apr 2019, Ph.D. in Engineering (biomedical and optical engineering), Keio University

Apr 2015 - Sep 2016, Master of Fundamental Science and Technology (Applied Physics and Physico-Informatics), Keio University

Apr 2011 - Mar 2015, Bachelor of Science and Engineering (Applied Physics and Physico-Informatics), Keio University

Publications

AI powered, automated discovery of polymer membranes for carbon capture
- - Ronaldo Giro
  - Hsianghan Hsu
  - et al.
- 2023
- npj Computational Materials
Foundation Model for Material Science
- - Seiji Takeda
  - Akihiro Kishimoto
  - et al.
- 2023
- AAAI 2023
Accelerating material design with the generative toolkit for scientific discovery
- - Matteo Manica
  - Jannis Born
  - et al.
- 2023
- npj Computational Materials
Accelerating Material Design with the Generative Toolkit for Scientific Discovery (GT4SD)
- - Matteo Manica
  - Joris Cadow
  - et al.
- 2022
- MRS Fall Meeting 2022
A Data-driven Discovery Pipeline for Flue Gas Separation Homopolymer Membranes
- - Hsianghan Hsu
  - Matteo Manica
  - et al.
- 2022
- MRS Fall Meeting 2022
Accelerating Material Design with the Generative Toolkit for Scientific Discovery (GT4SD)
- - Matteo Manica
  - Joris Cadow
  - et al.
- 2022
- ACS Fall 2022
Molecular Descriptors Accounting for Intramolecular Interactions and Application to Chemical Property Prediction
- - Lisa Hamada
  - Seiji Takeda
  - et al.
- 2022
- ACS Fall 2022
Molecular Descriptors Based on Global Structure Information of Substructures
- - Lisa Hamada
  - Seiji Takeda
  - et al.
- 2022
- JSAI 2022
Computational Design and Validation of Polymer Membranes with high CO2 Permeability
- - Hsianghan Hsu
  - Ronaldo Giro
  - et al.
- 2022
- APS March Meeting 2022
Accelerate Polymer Membrane Discovery for CO2 Separation with Graph-Based Generative Model and Molecular Dynamics Simulation
- - Hsianghan Hsu
  - Akihiro Kishimoto
  - et al.
- 2021
- MRS Fall Meeting 2021

Top collaborators

Hajime Shinohara

TA of Research - Tokyo / Research Scientist / Happy Friday Staff

Indra Priyadarsini S

Research Scientist

Eduardo Soares

Research Scientist

Emilio Vital Brazil

Senior Research Scientist - Manager AI-Assisted Decision Making