Machine Learning for ScienceJing Li Machine learning research engineer@Yokozunadata

Self Introduction @ Interdisciplinary Researcher

Computing physics (Complex dynamics system, MultiObjective optimization learning)

Computing chemistry (Graph probability, search algorithm, supervised/unsupervised learning)

Computing Material (Multiscale modeling, Monte carlo, GraphNN)

Interdisciplinary Research:Solve problems whose solutions are beyond the scope of a single discipline or area of research practice.

Learning approach: “Training my own neural network?”

Cognition Science

Physics

Chemistry

Material

Life Science

Human behavior

Math&Computer Science&Philosophy

Magnetic Refrigeration

Satellite

@Chiba University@NIMS, Cooperated with Toshiba, Samsung, LG, NASA, JAXA.

4K

Complex dynamics system, MultiObjective optimization learning（CNN）

Microgravity Experiment Liquid Oxygen

@From internet

Combustion @Mitsubishi Heavy Industry, Cooperated with Georgia Tech, UC berkeley

Graph Probability Learning

Graph Probability Theory from Paul Erdős

Polymer

Theoretical physics + Quantum chemistry + Material information (Multiscale modeling, Monte carlo, GraphNN)

Thermoset resin* (network)

@Tohoku University, visiting University of Washington, cooperated with Tokyo University

From　会田誠

-Modeling-

“Newton’s apple meet schrodinger's cat”

“Often these studies are not found out to be inaccurate until there's another real big dataset that someone applies these techniques to and says ‘oh my goodness, the results of these two studies don't overlap‘"

BBC NEWS

Machine Learning for Science

Chemistry Research

Existed Quantum Approach

Quantum Chemistry Calculation Tool: Gaussian1970s❏ Based on rapidly developing computer technologies❏ Purely from the fundamental laws of physics

John A. Pople

Successful Application Examples @ Chemistry

Comparing to DFT10000~ times Fast

Material Research

“Softmater material”

Self organization of helical assemblies DNA Viruses

Patterns at multiple spatial scales

https://ajw-group.mit.edu/multiscale-modeling-clays

・SVM (One layer)　・DNN (Multi layers)

Patterns at multiple time scales

Liu, Quan-Xing, et al. "Pattern formation at multiple spatial scales drives the resilience of mussel bed ecosystems." Nature communications 5 (2014): 5234.

August 2009

September 2009

400 days later~

・LSTM

Different pattern for different function@Material

moire pattern graphene“Fractal” of Honeycomb

The influence of environment to pattern

@Singapore @Alaska

Fundamental scientific challenges

24

❏ Is it possible to develop new materials without understanding underlying physical principles?

❏ Understand physical limitations of different materials and design.

Database +Math +Computer science

Fundamental elements:Electrons, Atoms,Molecules

Physics approach

Machine learning approach

Example: Molecular dynamics + statistical mechanics

Develop new materials