Presentations

• Mike Kesti, Senior Vice President, 3M

  • Title: Evolving R&D at 3M by leveraging “Digital”

  • Abstract: Mike Kesti, Senior Vice President of R&D, 3M Corporate Research Lab, will provide an overview of 3M’s innovation and technology development framework that is built upon a strong, centralized Corporate Research Laboratory (CRL) – 3M’s “innovation engine”. He will highlight several examples of how 3M is leveraging “digital” to generate value for specific uses cases, share lessons learned from 3M’s multi-year digital transformation journey, and discuss inherent challenges related to scaling “AI” across the enterprise.

• Bea Braun, R&D / TS&D Fellow – Digital Innovation, Dow Chemical 

  • Title: Dow's Digital Transformation: Achievements, Challenges, and Future Prospects 

  • Abstract: This presentation will provide an overview of Dow's digital transformation journey and will highlight a selection of success stories in materials design and production scenarios, where data-driven approaches and hybrid modeling have provided critical insights and innovative solutions. These examples will illustrate how advanced analytics and machine learning techniques have been leveraged to optimize processes and enhance product development.

In addition to showcasing these achievements, the talk will address the challenges and requirements associated with building robust data infrastructure, capturing and generating high-quality data, and fostering a data-centric culture within the organization. We will explore how these elements are essential for transforming the way we conduct research and development (R&D) and run our operations.

The talk will conclude with the importance of tailored upskilling programs across various departments, emphasizing the need for continuous learning and adaptation to keep pace with technological advancements. We will also provide an outlook on the potential impact of large language models and generative machine learning on our future initiatives, discussing how these cutting-edge technologies could revolutionize our approach to problem-solving and innovation.

• Linda Hung, Senior Manager, Toyota Research Institute

• Title: Exploring the design space of energy materials 

• Abstract: With advances in computation and laboratory automation, materials data has reached an unprecedented scale. This has enabled researchers to build new capabilities with AI. This talk highlights how the Accelerated Materials Design and Discovery team at Toyota Research Institute is developing tools and drawing insights from new and existing open materials datasets. We also discuss the challenge of the large design space for materials. It remains an open research question how transferable AI models can be across many modalities of data and variable research goals.

• Vikram Agarwal, Head of mRNA Platform Design Data Science, mRNA Center of Excellence, Sanofi

  • Title: Artificial Intelligence for mRNA Therapeutic design

  • Abstract: Amidst the Covid-19 pandemic, the world saw the rise of the first successful mRNA vaccines that protected millions of people. These vaccines consisted of a lipid nanoparticle (LNP) carrying mRNA that encoded an immunogenic antigen, which stimulated immune protection from severe Covid-19 infection. Here we discuss how artificial intelligence (AI) can be leveraged to improve mRNA manufacturability as well as LNP/mRNA potency. We describe how an AI-guided design strategy could lead to improved patient outcomes and faster turnaround times to design the next generation of mRNA therapeutics.

• Matthew Mills, Advanced Data Science Specialist, 3M

  • Title: Achieving scalable AI readiness for an industrial analytical research laboratory.

  • Abstract: The 3M Corporate Research Analytical Laboratory (CRAL) houses a wide variety of analytical equipment operated by expert scientists working to create a sustainable competitive advantage for 3M by driving growth through fundamental scientific understanding. As the external AI landscape has evolved, the AI-readiness of the lab has been a key factor in planning long-term strategy. An embedded team of data scientists was added to CRAL in 2017, with the goal of building towards a future as a fully data-enabled lab. By focusing on projects with high business value potential and the development of a robust digital ecosystem, CRAL has led the development of digital solutions and automation in analytical science at 3M. The lab has evolved to a state where good data practices, data-science-driven efficiency and capability improvements, and the use of ML and AI are becoming key to the daily work of analysts. The challenges faced in reaching future AI-readiness will be discussed, along with current approaches to their solution.

• Todd Lohr, Principal, Head of Ecosystems, KPMG

  • Title: Navigating the Future of AI: Trends, Agents, Workforce Transformation, and Trust 

  • Abstract: As artificial intelligence continues to evolve at a rapid pace, its impact on industries and the workforce is becoming increasingly profound. This presentation will provide a comprehensive overview of the current AI landscape, drawing on recent survey data to highlight key trends and adoption rates across various sectors. Looking ahead to 2025, we will delve into the anticipated shift towards AI agents and explore what this evolution means for business operations and strategies. As AI agents become more prevalent, understanding their capabilities and implications will be crucial for maintaining a competitive edge. Furthermore, the talk will address the significant impact of AI on the workforce, discussing opportunities for enhanced productivity and new roles that are emerging as a result of AI integration. We'll explore strategies to effectively integrate AI in the workplace while fostering a culture of continuous learning and development. Finally, the presentation will emphasize the importance of maintaining trust in AI applications. We will discuss best practices for ethical AI use, transparency, and building stakeholder confidence to ensure sustainable and responsible AI integration in business practices.

• Gregory Mulholland, CEO, Citrine Informatics

  • Abstract: The most significant hurdle to achieving meaningful outcomes with AI in enterprise, is not the technology or the data, but the people. Over its 12-years in industry, Citrine has honed the science and art of people-centric implementation, with value attainment as our North Star.  This presentation will share Citrine’s value frameworks, along with its guiding principles for implementations. We’ll discuss case studies to highlight not only best practices, but also pitfalls. Join us as we share our hard-won lessons learned with the intention of helping our community to advance the transition toward better products enabled by AI. 

• Thomas von Tschammer, Co-Founder and U.S. Managing Director, Neural Concept

  • Title: Leveraging AI for Engineering & Design at scale, what are the key enablers? 

  • Abstract: Through his extensive experience with Neural Concept, Thomas will share some of the key enablers to deploy AI for Engineering and Design workflows at scale, through some practical implementation examples within some of the largest engineering companies. This presentation will also focus on the value and outcomes that companies can expect from these AI-driven workflows, once applied at the core of the engineering processes.

• Mark Huntington, Managing Director, North America, PhysicsX

  • Title: Accelerating Hardware Innovation with AI-Driven Physics Simulations  

  • Abstract: Mark will discuss how AI-driven physics simulations are transforming hardware engineering across critical industries. With engineering bottlenecks and talent shortages increasingly limiting innovation in sectors such as automotive, semiconductors, aerospace, and advanced materials, AI-powered solutions offer transformative efficiency gains—reducing development timelines, drastically cutting costs, and accelerating performance optimization. Through real-world case studies, Mark will illustrate how PhysicsX’s platform rapidly operationalizes high-fidelity simulations, significantly outperforming traditional numerical methods, and enabling unprecedented scalability and speed in product and process design.