Areas of Research
Complex Systems and Data Science

As we end the first fifth of the 21st Century, human societies face global challenges of unimaginable scale. Global pandemics pose the risk of killing millions of people and paralyzing economies. Climate change threatens coastal cities, imperils food supply chains, and contributes to the extinction of numerous species around the globe. Unlike many problems facing engineers in the past, the solution to these challenges involves not only the development of new technologies but also an accounting for human decisions and behaviors. For example, while the consequences of climate change pose particular large costs for coastal cities such as Houston, TX, the economic implications for the area of a decline in the importance of fossil fuels would be staggering.

These complex challenges require not reductionist approaches, or optimal technical strategies, but the understanding of the numerous interlocked components and sub-systems that are part of or interact with human societies. Complexity science has for the last 40 year developed a set of approaches and techniques that allows for the exchange of knowledge among the disciplinary silos and for the manipulation of objects without predefined roles or interactions. These include nonlinear dynamics, fractal geometry, statistical physics, network science, and recently, data science.


Luis Amaral

Network science, Data science methodologies. Applications to systems biology (development, aging, and stress response), adoption of innovations (medical innovations, error mitigation), science of science (quantifying performance, gender, resource allocation), and computational social sciences (personality traits, data transparency).

Linda Broadbelt

Complex kinetics modeling, biological reaction networks, in silico molecule discovery, novel pathway discovery

Michael Jewett

Engineering biology, systems engineering of molecular translation, metabolic biosensors, deep learning to advance bio-discovery and bio-design

Joshua Leonard

We investigate emergent behavior in complex biological systems, including natural and therapeutically engineered immune functions. We also build synthetic biology technologies enabling the composition of complex biological circuits, networks, and systems.

Jeffrey Lopez

Automated and high throughput experimentation for accelerated materials discovery and development, energy storage, electrochemical interfaces

Julius Lucks

The Lucks Lab develops and applies computational algorithms and approaches to study molecular folding dynamics of nucleic acids, the dynamics and design of genetic circuits and large scale next-generation sequencing datasets.

Richard Lueptow

William Miller

Chad Mirkin

Mirkin engineers functional and dynamic colloidal systems of immense complexity by cleverly tuning particle surface chemistry

Milan Mrksich

Monica Olvera de la Cruz

Julio Ottino

Aaron Packman

Randall Snurr

Machine learning, cheminformatics, high-throughput computational screening of materials/p>

Danielle Tullman-Ercek

Keith Tyo

Predicting enzyme behavior using cheminformatics and kinetic models to enable sustainable biosynthesis (in collab. with Broadbelt)