No model or mathematical formula alone can capture the complexity of our world, with all its emotional, cultural, and human variables that are difficult to define and measure. Therefore, we must design. To cope with complexity, we often oversimplify and seek quick models to make sense of the world and predict outcomes. However, this approach can hinder creative problem-solving and contradict the essence of innovation.
As a method of synthesis, design is a fundamental human ability that relies on intuition, prediction, and facts to envision and create pathways to a better future. Designing generates meaning by inventing new wholes that exceed the sum of their parts through an interactive, collaborative process. By involving stakeholders in the design process to deeply understand their needs and the context of innovation, design uncovers opportunities for problem-solving that conventional analytical methods alone cannot achieve. The design process reveals hidden opportunities within complex situations, enabling a creative way forward. Thus, design is essential in our quest for a more sustainable and equitable future alongside science and technology.
The MIT community relies on our enterprise systems for a range of activities — everything from hiring and evaluating employees to managing research grants and facilities projects to maintaining student information. Our vision in updating our systems is 1) to create easy-to-use and well-integrated systems, streamlined processes, and comprehensible and accessible data for reporting and analysis; 2) to simplify our business processes to improve efficiency and effectiveness; 3) to modernize our enterprise systems and data architecture to take advantage of more innovative technology and functionality; and 4) to make our data accessible and actionable by implementing more robust data governance through clear ownership and accountability.
This talk shares both our plan and some best practices from recent efforts at transforming a complex collection of digital and non-digital assets into a more cohesive landscape, including a) addressing systems, processes, and data wholistically; b) developing a thoughtful and actionable multi-year roadmap of digital transformation projects; and c) engaging and assisting our entire community every step of the way.
Corporate culture is one of the most important enablers—or obstacles—to innovation, but culture is notoriously difficult to measure. Recent advances in LLMs enable leaders to mine employee feedback to understand and improve their corporate cultures. This session will discuss how to leverage AI to measure culture and share insights from an ongoing study of innovative culture at companies including NVIDIA, SpaceX, and Novo Nordisk.
Firms always face a choice for where to source their innovation: do they hire internal researchers? Work with startups or external companies? There are many options. In this talk, I will present results from research on how firms are sourcing digital innovations, and then I will speak specifically about AI and how to view it in this framework.
Solid-state electronic devices and biological systems exhibit drastically disparate materials properties. While semiconductor devices are often hard, brittle, and bound to flat wafers, biological electronics, such as our nervous system, are soft, mobile, and three-dimensional. Our group bridges this material divide between synthetic and biological electronics by creating multifunctional fibers capable of minimally-invasive interfacing with the organs while integrating advanced sensing and stimulation capabilities. This talk will highlight the development and applications of multifunctional fibers to recording and modulation of neural activity in the brain and in the gastrointestinal tract in behaving subjects. Finally, it will demonstrate how bioelectronic devices can be applied to uncover neural circuits underlying gut-brain communication, paving the way to future gut-centric therapies for neurological and psychiatric disorders.
Chimeric Antigen Receptor (CAR) T cell therapy has revolutionized cancer care, yet its manufacturing remains challenging due to variability in quality and efficacy. In this talk we introduce a novel microfluidic, label-free cellular biophysical profiling assay that rapidly assesses the functional phenotypes of CAR T cells. Our assay leverages biophysical features such as cell size and deformability to directly correlate with critical functional attributes, including the CD4:CD8 ratio, effector and central memory subtypes, and killing potency. Validated through extensive longitudinal studies across multiple CAR T batches from different donors and culture platforms, this method requires fewer than 10,000 cells and completes profiling within 10 minutes. The assay provides an efficient means to predict CAR T cell quality at critical manufacturing stages, thereby potentially reducing batch failure rates and enhancing therapeutic consistency.
The thousands of inputs a single neuronal cell receives can interact in complex ways that depend on their spatial arrangement and on the biophysical properties of their respective dendrites. For example, operations such as coincidence detection, pattern recognition, input comparison, and simple logical functions can be carried out locally within and across individual branches of a dendritic tree. In this talk, we will present the hypothesis that the brain leverages these fundamental integrative operations within dendrites to increase the processing power and efficiency of neural computation. We will focus on sensory processing and spatial navigation, with the goal of understanding the mechanistic basis of these brain functions.
Physical neural networks made of analog resistive switching processors are promising platforms for analog computing and for emulating biological synapses. State-of-the-art resistive switches rely on either conductive filament formation or phase change. These processes suffer from poor reproducibility or high energy consumption, respectively. Our work, on one hand, focuses on understanding and controlling the variability of the conductive filament formation in insulating oxide materials. On the other hand, we are innovating alternative synapse designs that rely on a deterministic charge-controlled mechanism, modulated electrochemically in a solid state, and that consists of shuffling the smallest cation, the proton. As typical throughout our research, here, too, we combine experimental synthesis, fabrication, and characterization with first principles-based computational modeling to gain a deep understanding and control of these promising devices.
AI’s influence is undeniable in the digital realm, affecting consumers’ lives and corporate operations. Transferring these advancements to sectors producing physical goods, such as drug discovery and biotech, commodity chemicals, materials for energy and sustainability, and manufacturing, presents a thrilling prospect and a translational challenge. This talk will explore the present use cases and the potential of applying generative AI within the chemistry and materials domain. Unlike a large part of the tech sector, these industries are capital-intensive and cautious, meaning that AI must bridge an “execution gap” between the digital and physical realms for value generation. We will outline strategies to overcome current technical and cultural hurdles.