Conference Schedule

Moderator:

• Nipun Gupta

Speakers:

• Paul Dingwall | Enabling high throughput kinetic experimentation for homogeneous catalysis in flow
• Milad Abolhasani | Data-rich autonomous fluidic labs for accelerated materials discovery
• Andre Charette | Expanding the toolbox of synthetic organic chemistry using continuous flow technologies towards local production of active pharmaceutical ingredients
• Christopher Hone | Development of an autonomous modular flow platform for optimization and model generation in drug substance process development
• Kakasaheb Nandiwale | Automated self-optimization of continuous flow synthesis of pharmaceuticals

Moderator:

• Keith Brown

Speakers:

• Jie Xu | Polybot: an AI-guided robotic laboratory empowering innovation in polymer electronics
• Kai Huang | Automated synthesis for closed-loop discovery of lanthanide-doped luminescent nanocrystals
• Claudiane Oullet-Plamondon | Optimization of blended concrete for sustainable robotic 3D printing
• Yi Liu | High-throughput experimental and machine learning optimization of composition and processing for high-strength and high-conductivity copper alloys beyond the scale of thousand samples per year
• Turab Lookman | Compositional design of multicomponent alloys using reinforcement learning
• Mitra Taheri | Autonomous, High Throughput Characterization Enabling Discovery of Cobalt-Lean Heusler Alloys

Moderator:

• Brandon Lines

Speakers:

• Basita Das | DiSCO : A modular [Di]scovery, [S]ynthesis, [C]haracterization, and [O]ptimization platform with adaptable deposition method and data collection pipeline
• Andrew Kukor | Takeda’s vision for a self-optimizing high throughput workflow
• Thomas Malig | Combining data rich experimentation & data science to accelerate mechanistic investigations of a catalytic sulfur(VI) desymmetrization
• Lilo Pozzo | Engineering soft-matter with agent-driven high-throughput experiments
• Kazunori Nishio | Digital laboratory for thin-film materials exploration using machine learning and robotics
• Curtis Berlinguette | Flexible automation enables self-driving labs

Moderator:

• Ian Foster

Speakers:

• Josh Schrier | Large language models are a strong baseline for inorganic synthesizability and precursor selection prediction
• Henry Sprueill | ChemReasoner: bridging generative AI and computational chemistry
• Katerina Christofidou | Extracting complex concentrated alloys properties from scientific literature with LLMs
• Mehrad Ansari | Inverse design of materials with chemist AI agents
• Kevin Jablonka | Transforming chemistry with transformers
• Tong Xie | Are large language models ready for materials discovery?

Moderator:

• Madeleine Gaidimas

Speakers:

• Michael Greenwood | Materials acceleration platform for evolving and optimizing 3D printable structures for carbon capture
• Leonard Wei Tat Ng | MicroFactory: demonstrating a printing-inspired self-driving digital twin for the high-throughput, closed-loop optimization of roll-to-roll printed photovoltaics
• Michael Eikerling | Accelerating the design and integration of electrocatalyst materials for hydrogen technologies with theory and computation
• Udo Bach | Experimental high-throughput energy materials discovery
• Yangang Liang | Automation-accelerated redox flow battery research
• Thomas Heumüller | Discovering one molecule out of a million – Inverse design of molecular materials tailored for perovskite solar cell operation

Moderator:

• Tejs Vegge

Speakers:

• Taylor Sparks | HONEGUMI: changing the way we code for optimization in the era of LLMs
• Shijing Sun | Learning to incorporate domain expertise in autonomous experiments
• Calvin Li | Blameless post-mortem culture – What to do when things go wrong?
• Sterling Baird | Teaching AI and automation with physical hardware

Speaker:

• Nadya Peek, University of Washington

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Speaker:

• Jason Hein | Chair, Accelerate Conference 2024