Bunsen in Action: Agentic AI co-scientist deep-dive series for polymers, batteries, and reactivity
Date & Time - November 17th – December 8th, 2026
Location - Virtual
Following our introduction webinar on Bunsen for materials science, we are launching a deep-dive, 3-part webinar series dedicated to Bunsen, Schrödinger’s agentic AI co-scientist. We’ll show how Bunsen is helping polymers, energy storage, and chemical reactivity teams navigate complex, multidimensional design spaces, identify data gaps and modeling risks, and prioritize the most informative candidates for further computation or experiments. By pairing domain-trained generative AI with rigorous physics-based simulation engines (quantum mechanics, molecular dynamics, and machine learning), Bunsen plans, executes, and analyzes end-to-end R&D workflows using natural language guidance.
Join us for this series featuring demonstrations where our scientists show directly how your team can leverage Bunsen for specific applications to accelerate innovation, de-risk experimental testing, and unlock high-performing candidates faster than ever before.
NOV 17 | Polymers & Formulations
8:00 AM PST | 11:00 AM EST | 4:00 PM GMT | 5:00 PM CET
What you’ll see in the session:
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Direct Bunsen to generate and screen polymers and formulations for compatibility and key performance properties such as Tg
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How Bunsen autonomously orchestrates atomistic building, automated equilibration, and property predictions without manual setup
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Extract data and build formulation based ML models
DEC 1 | Batteries & Energy Storage
8:00 AM PST | 11:00 AM EST | 4:00 PM GMT | 5:00 PM CET
What you’ll see in the session:
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Use natural language to command Bunsen to automatically build complex electrolyte formulations, equilibrate with molecular dynamics simulations and calculate properties
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Prompt Bunsen to screen electrolyte formulations for key properties—including density, viscosity and ionic conductivity
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Perform multi-property optimization and selection of additive candidates for improved performance
DEC 8 | Chemical Reactivity
9:00 AM PST | 12:00 PM EST | 5:00 PM GMT | 6:00 PM CET
What you’ll see in the session:
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Prompt Bunsen to explore reaction pathways through supervised discovery (guided by user/agent domain knowledge) or unsupervised discovery (driven automatically by quantum mechanical forces rather than empirical rules)
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Prompt Bunsen to perform reactivity and/or catalyst optimization
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Prompt Bunsen to code a workflow
Our Speakers
Andrea Browning
Senior Director of Polymers and Soft Matter, Schrödinger
Andrea leads initiatives in polymer and soft matter simulations. Prior to Schrödinger, Andrea was a lead research engineer and project manager at Boeing, where she focused on translating engineering problems into fundamental materials insights. She brings over a decade of experience in connecting industrial and engineering problems to root materials issues and how simulations can be used to inform industrial decisions. Andrea earned her Ph.D. in Chemical Engineering from the University of California, Santa Barbara, where she was a National Science Foundation Graduate Research Fellow.
Michael Rauch
Senior Director, Global Portfolio Leader, Schrödinger
Michael earned his Ph.D. from Columbia University in synthetic organometallic chemistry as an NSF Graduate Research Fellow before pursuing a postdoctoral role in organic chemistry at the Weizmann Institute of Science as a Zuckerman Postdoctoral Scholar. Michael is particularly interested in green, sustainable chemistry and transforming the way that synthetic chemists utilize molecular modeling via practical education.
Garvit Agarwal
Principal Scientist, Schrödinger
Garvit Agarwal, Principal Scientist and Scientific Lead for Energy Storage at Schrödinger, works to extend and apply molecular modeling tools for the accelerated discovery of next-generation clean energy technologies. Garvit obtained his Ph.D. in Materials Science and Engineering from the University of Connecticut. He worked as a post-doctoral researcher in the Materials Science Division at Argonne National Laboratory prior to joining the Materials Science team at Schrödinger.
Pavel Dub
Research Leader and Product Manager, Catalysis & Reactivity, Schrodinger
Pavel A. Dub earned a Ph.D. in Physical Chemistry from the A. N. Nesmeyanov Institute of Organoelement Compounds and a second Ph.D. from the Université de Toulouse. He subsequently completed postdoctoral appointments at the Tokyo Institute of Technology and Los Alamos National Laboratory, where he later served as a Staff Scientist and a Project Manager. In 2022, he joined Schrödinger. His research focuses on computational chemistry and materials science across both classical and quantum computing architectures.