Faculty

We are interested in the design, synthesis, and characterization of soft materials.

We study life-like biochemical systems to understand their fundamental properties and address emerging challenges in biotechnology and infectious disease.

The Di Carlo Lab uses micro & nanoscale technology to study and engineer biology at its ultimate limits.

Organometallic chemistry for rational block copolymer synthesis

We conduct research at the interface of organic, organometallic, and physical organic chemistry, enhanced by modern data science and machine learning.

The Fredrickson group has pioneered a new class of computer simulation techniques based on molecularly-informed statistical field theories. Such field-theoretic simulations enable the investigation of classical soft material and quantum many-body systems at an unprecedented range of length and timescales.

Our group aims at advancing the field of organic solid-state chemistry by taking advantage of the reduced entropy and emergent properties that characterize the crystalline solid state.

Uncertainty quantification, surrogate models, inverse design, stochastic processes, and data science.

Preparing, educating and inspiring the next generation.

Prof. Helgeson is an expert in rheological and structural characterization of soft materials, including the development of new high-throughput methods for microrheology.

Maynard and her group synthesize novel functional polymers for applications in biomaterials, biotechnology, and nanotechnology.

The Mills lab engineers and studies protein assemblies and materials to create accessible, bioengineered solutions in spaces like plastic waste degradation and oral vaccine delivery.

We use simulations and machine learning to gain molecular level insights and develop testable hypotheses.

We design, synthesize, and characterize soft bio-inspired materials.

His research group seeks creative, synthetic solutions to problems at the interface of chemistry and material science.

Assistant Professor of Chemistry & Biochemistry focused on structure-based scientific discovery.

Our lab develops computational and theoretical methods for automation, synthesis prediction, and materials design.

Bioinspired polymer synthesis and self-assembly to control properties.

Prof. Shell develops novel molecular simulation, multiscale modeling, and statistical thermodynamic approaches to address problems in contemporary biophysics and soft condensed matter.

We harness electrostatic and other non-covalent intermolecular interactions to design self-assembled soft materials.

My research lab is interested in natural product biosynthesis and biocatalysis.

Soft material mechanics, design and manufacturing of bio-inspired materials, adhesion, rheology, instrument development .

The primary objective of my research is to explore foundational models in artificial intelligence, customize these models for data mining, and examine their application across domains such as finance, healthcare, and science. Historically, we have made significant advancements in graph data mining and we have inadvertently pioneered the use of Transformer-based methods in time series forecasting.