Maxim A. Ziatdinov

Presentation History

2021 MRS Fall Meeting

Mapping Polarization from STEM and STM Images

Dec 8, 2021, 11:15 AM

2021 MRS Fall Meeting

Prediction of Localized Plasmon Resonances in Complex Nanoparticle Assemblies Using Autoencoder Networks

Dec 8, 2021, 11:00 AM

2021 MRS Fall Meeting

Realizing Physical Discovery in Imaging with Machine Learning

Dec 8, 2021, 10:30 AM

2021 MRS Fall Meeting

High-Throughput Study of Antisolvents on the Stability of Multicomponent Metal Halide Perovskites Through Robotics-Based Synthesis and Machine Learning Approaches

Dec 7, 2021, 2:45 PM

2021 MRS Fall Meeting

Disentangling Ferroelectric Wall Dynamics and Identification of Pinning Mechanisms via Deep Learning

Dec 7, 2021, 11:15 AM

2021 MRS Fall Meeting

Conductive Hotspots in Hf0.5Zr0.5O2—An Automated Experiment Investigation

Dec 7, 2021, 9:30 AM

2021 MRS Fall Meeting

Automated Scanning Probe Microscopy Based on Deep Kernel Learning

Dec 7, 2021, 9:15 AM

2021 MRS Fall Meeting

Reinforcement Learning in Materials Science—Atomic Fabrication and Materials Design in Simulated Environments

Dec 7, 2021, 9:00 AM

2021 MRS Fall Meeting

SPM at the Edge—Bayesian Optimization with Prior Knowledge for Accelerating Spectroscopy in Scanning Probe Platforms

Dec 6, 2021, 2:15 PM

2021 MRS Fall Meeting

Incorporating Physical Priors Into Probabilistic Models in Bayesian Framework

Dec 6, 2021, 1:30 PM

2021 MRS Fall Meeting

Connecting Pathways of Microscopic Images and First-Principles Simulations via Deep Learning

Dec 6, 2021, 11:40 AM

2021 MRS Fall Meeting

Towards the Automation of Structural Discovery in Scanning Transmission Electron Microscopy

Dec 6, 2021, 9:00 AM

2021 MRS Fall Meeting

Decoding the Shift-Invariant Data—Applications for Band-Excitation Scanning Probe Microscopy

Dec 6, 2021, 9:00 AM

2021 MRS Fall Meeting

Machine Learning and AI Methods for Materials Science—Applications to Theory, Characterization, and Smart Experiments - Afternoon session

Nov 29, 2021, 1:00 PM

2021 MRS Fall Meeting

Machine Learning and AI Methods for Materials Science—Applications to Theory, Characterization, and Smart Experiments - Morning Session

Nov 29, 2021, 8:30 AM