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Sergei Kalinin

Keynote talk: Integrating Autonomous Systems for Advanced Material Discovery: Bridging Experiments and Theory Through Optimized Rewards

Understand the principles and advancements in orchestrating autonomous experimental workflows for scientific research, focusing on the integration of automated and cloud labs, reward functions, and human-in-the-loop interventions.
Sergei was recently recognized by multiple organizations for his outstanding science and technical contributions in nanotechnology and microscopy.

Sergei Kalinin

Keynote talk: Integrating Autonomous Systems for Advanced Material Discovery: Bridging Experiments and Theory Through Optimized Rewards

Understand the principles and advancements in orchestrating autonomous experimental workflows for scientific research, focusing on the integration of automated and cloud labs, reward functions, and human-in-the-loop interventions.
Sergei was recently recognized by multiple organizations for his outstanding science and technical contributions in nanotechnology and microscopy.

Sergei Kalinin

Nadya Peek

Keynote talk: Open-Source Hardware Ecosystems that Support Laboratory Automation Workflows

Learn how to use open-source hardware toolkits to create and customize laboratory automation workflows, promoting open and easily shareable scientific results.
Nadya’s Machine Agency research group at the University of Washington harnesses the precision of machines for the creativity of individuals.

Nadya Peek

Keynote talk: Open-Source Hardware Ecosystems that Support Laboratory Automation Workflows

Learn how to use open-source hardware toolkits to create and customize laboratory automation workflows, promoting open and easily shareable scientific results.
Nadya’s Machine Agency research group at the University of Washington harnesses the precision of machines for the creativity of individuals.

Seiji Takeda

Keynote talk: Project Rhizome: Multi-modal Foundation Models for Accelerated Material Discovery

Discover how IBM is utilizing Rhizome, a multimodal foundation model, to facilitate various downstream tasks in materials science and chemistry by leveraging its capability to handle diverse data modalities such as SMILES, SELFIES, molecular graphs, optical spectra, and more.
Seiji and his team at IBM have developed a number of material inverse design tools, including the cloud-based, AI-driven IBM Molecule Generation Experience.

Seiji Takeda

Keynote talk: Project Rhizome: Multi-modal Foundation Models for Accelerated Material Discovery

Discover how IBM is utilizing Rhizome, a multimodal foundation model, to facilitate various downstream tasks in materials science and chemistry by leveraging its capability to handle diverse data modalities such as SMILES, SELFIES, molecular graphs, optical spectra, and more.
Seiji and his team at IBM have developed a number of material inverse design tools, including the cloud-based, AI-driven IBM Molecule Generation Experience.