Science That Matters, Now More Than Ever
Heidi Opdyke
- Associate Dean of Marketing and Communications, MCS
- Email opdyke@andrew.cmu.edu
- Phone 412-268-9982
Walking through Carnegie Mellon University’s Mellon Institute on a quiet morning, one might find a researcher watching a set of experiments unfold that could shape new therapies or more sustainable materials. On another floor, chemists are orchestrating algorithms trained to recognize patterns in molecules, accelerating discoveries with implications in medicine and industry. At Wean Hall, mathematicians are refining the logic that underpins those algorithms, helping to power advances in technology and data-driven decision-making, while physicists parse signals from the farthest reaches of the universe, expanding our understanding of fundamental science in ways that often ripple into everyday innovation.
Though their questions differ, their work shares a common purpose: to understand, to solve and to improve.
This is Science that Matters — the Mellon College of Science’s commitment to discovery that expands human knowledge while strengthening society.
“Science is essential to understanding our world — from the smallest biological process to the vast expanse of the universe,” said Barbara Shinn-Cunningham, Glen de Vries Dean of the Mellon College of Science. “It drives the innovations that improve lives, fuels economic progress and prepares the next generation of talent.”
At MCS, discovery begins with fundamental questions: How do molecular interactions within cells give rise to health and disease? How does the brain produce thought and behavior? What mathematical structures govern complexity and uncertainty? What is the universe made of — and how did it evolve? How can we design chemicals that are both effective and environmentally responsible?
From these questions, researchers move toward solutions that improve health, enable new technologies, protect the environment and deepen our understanding of the world.
Understanding life, advancing health
In the biological sciences, MCS researchers investigate life across scales — from molecules to organisms — revealing the mechanisms that drive development, evolution and disease. Their work uncovers how infections spread, how cancers grow, how resistance to antibiotics emerges and how complex cellular systems function and fail.
These insights form the groundwork for new diagnostics, therapies and strategies for prevention.
Increasingly, discovery is powered by the integration of data-rich experimentation with artificial intelligence, advanced imaging and quantitative analysis. This convergence accelerates the pace of research and enables predictive models that shift biology from observation to anticipation.
One example is the work being conducted by Jonathan Henninger, assistant professor in biological sciences. His laboratory, in collaboration with labs at MIT, recently identified a mechanism that controls how biomolecular condensates — tiny liquid-like droplets inside a cell that acts like a specialized compartment to organize and group molecules — form patterns that can be disrupted in diseases like cancer and neurodegeneration.
“This research speaks to an entirely new field of studying how condensates are patterned in a cell,” Henninger said. “Many condensates show very different patterns throughout cells, but we’re not sure why or what function this serves. This study answers that question for the nucleolus, an essential condensate in the cell that makes ribosomes, which produce all the proteins of a cell.”
Understanding the brain
In neuroscience, researchers seek to understand one of science’s greatest frontiers: the human brain. At MCS, this work spans molecular, systems, cognitive and computational levels — linking cells to circuits, and circuits to perception, learning and behavior.
That integration is yielding tangible progress. Today, researchers are significantly closer to new treatments for disorders such as Parkinson’s disease, epilepsy, Alzheimer’s disease and autism than they were just a few years ago.
In a recent paper, Elizabeth Ransey, an assistant professor in biological sciences, demonstrated precision control over neuronal communication by engineering artificial electrical connections between specific types of brain cells. The work has potential applications for treating neurological and psychiatric disorders where faulty communication between brain regions plays a key role.
Achieving that level of precision required engineering the molecular machinery that connects cells: channel forming proteins.
“The goal sounded almost simple,” she said. “Make two proteins interact exclusively with each other. But of course, it was not simple at all.”
The project, which spanned years and multiple experimental systems, sits at the intersection of protein engineering, cell biology and neuroscience. At the center of the work are gap junctions, natural protein channels that allow neighboring cells to directly exchange electrical and chemical signals.
Ransey and colleagues built upon these channels to develop LinCx (Long-term Integration of Neural Circuits using Connexins), to synchronize target neural circuits in living animals. Natural gap junctions are difficult to control because they form broadly and unpredictably across cells. LinCx instead uses a paired, two-component system: two modified gap junction proteins that selectively dock with one another, allowing researchers to create electrical connections selectively between target neural cell populations.
“One of the most important developments was showing that this kind of engineered specificity can work in mammalian systems,” she said. “The proteins largely ignore native mammalian connexins, allowing us to introduce new connections without broadly interfering with existing communication networks.”
Mathematical discoveries shape the world around us
Behind advances in image processing, financial trading, global logistics and even Spotify’s ad targeting systems is the same essential foundation: mathematics.
Mathematics is an engine of modern discovery — providing the language, tools and structure behind breakthroughs across science and technology. Faculty are advancing the frontiers of applied analysis, discrete mathematics, logic, computation, finance and probability, while deepening strengths in areas like number theory and algebraic geometry. Together, this work powers innovation in AI, finance, materials science, public policy and beyond.
Researchers also are redefining how mathematics itself is practiced. Efforts in AI-assisted reasoning and formal proof verification are enabling mathematical knowledge to be encoded, tested and trusted in entirely new ways. At the same time, advances in stochastic modeling and computational mathematics are helping scientists better understand uncertainty, risk and complexity in real-world systems — from supply chains to digital platforms where optimization algorithms ensure the right content reaches the right audience at the right time.
“Clearly AI is going to be disruptive, but exciting too,” said Prasad Tetali, the Alexander M. Knaster Professor and head of the Department of Mathematical Sciences. “The progress in AI technology is too rapid to predict the precise extent of how research and education in math will evolve in the next few years. We are constantly discussing and taking steps to adapt what and how we ‘do the math’, but also what we should be teaching without compromising on the rigor.”
Designing the molecules of the future
In chemistry, MCS researchers are designing the building blocks of modern life — molecules and materials that drive advances in sustainability, medicine and advanced manufacturing.
Their work spans catalytic processes, recyclable polymers, nucleic acid chemistry and environmental and analytical techniques. Increasingly, it also includes the “lab of the future,” where automation, robotics and AI accelerate discovery and improve safety.
By connecting quantum theory with computation and experiment, MCS chemists are creating pathways to cleaner energy, innovative therapeutics and environmentally responsible materials.
More than 10,000 synthetic chemicals are used to make plastic products. Advancing sustainable chemistry requires the capability to predict what changes chemicals may undergo and what happens to the resulting transformation products.
Ryan Sullivan, associate director of Carnegie Mellon University’s Institute for Green Science and professor of chemistry and mechanical engineering; Carrie McDonough, assistant professor of chemistry; Olexandr Isayev, the Carl & Amy Jones Professor of Interdisciplinary Science; and Ana Torres, assistant professor of chemical engineering, are working to change that.
The researchers are developing high-throughput experimental and computational methods that acquire the chemical data needed to inform environmental molecular lifecycles. They said that these environmental and biological chemical reaction networks will screen for transformation products that are likely persistent or prone to bioaccumulation. This more rapid chemicals analysis will then guide sustainable chemical assessment such that likely harmful chemicals can be identified much earlier in their development lifecycle.
“Our big focus is to assess the ability to predict the fate of a molecule under environmental and biological conditions. What does it turn into? And where does it go?” Sullivan said.
Sullivan said that by understanding how molecules can transform and how quickly under different conditions, the data can inform how long they’ll exist in the environment.
“It’s an understudied — but important — topic,” he said. “We need to work to connect the world of environmental chemistry and what we know and how we use that information to better evaluate and design chemicals and materials that are more sustainable in nature.”
Exploring matter, energy and the cosmos
In physics, MCS scientists investigate the fundamental laws that govern the universe — from the smallest particles to the largest cosmic structures.
Their research ranges from gravitational waves and multi-messenger astrophysics to quantum materials and technologies. Through collaborations such as the McWilliams Center for Cosmology & Astrophysics and the Pittsburgh Quantum Institute, they work across disciplines to tackle some of science’s most profound questions: What is the universe made of? How did it evolve? What laws govern it?
Using advanced instrumentation, large-scale simulations, theoretical models and AI-driven analysis, they are expanding the boundaries of what we can observe and understand — while enabling next-generation sensing, computing and modeling capabilities.
“Advancing the frontiers of physics requires a global effort, one that brings together major collaborations, advanced computational efforts together with AI,” said Manfred Paulini, associate dean for research and professor of physics. “At Carnegie Mellon, we contribute deep expertise in data analysis, instrumentation and AI to international initiatives such as the CMS experiment at CERN and the Vera C. Rubin Observatory, along with other international collaborations that expand our understanding from the smallest particles to quantum materials, living cells and the universe.”
Paulini said what makes this especially powerful is how closely research and education are linked: MCS students are directly engaged in these efforts, gaining hands-on experience with the most ambitious scientific projects in the world.
“By integrating global partnerships with CMU’s strengths in science, engineering, and AI, we not only accelerate discovery but also prepare the next generation of scientists to lead it,” he said.
Convergence for impact
What unites this work is not just excellence within disciplines, but the deliberate integration of discovery, application and innovation across them. At MCS, theory, experimentation, computation, automation and AI form a continuous ecosystem — one in which fundamental insights inform applied research and technological advances, in turn, open new frontiers for discovery. This convergence reflects a distinctly Carnegie Mellon approach: bringing together scientists, engineers and technologists to accelerate progress in ways no single approach could achieve alone. The result is a model of science that becomes more predictive, efficient and responsive — linking curiosity-driven inquiry with the tools to translate knowledge into societal impact.
“The most important scientific advances today happen at the boundaries between disciplines,” Shinn-Cunningham said. “At the Mellon College of Science, we intentionally position ourselves at that intersection and bring together expertise in science, engineering and artificial intelligence to tackle problems no single field can solve alone. By building on Carnegie Mellon’s unique strengths across those areas, we create an environment where collaboration drives discovery and where new ideas can move seamlessly from fundamental insight to application and real-world impact.”
A purpose-driven future
“Science that Matters” has become a guiding principle for MCS, Shinn-Cunningham said — not as a departure from foundational research, but as an extension of its value. By advancing fundamental knowledge while cultivating pathways to application, MCS researchers ensure that discovery is part of a larger continuum. Ideas evolve into solutions, technologies and deeper understanding, reinforcing the essential role of science as both a driver of innovation and a public good. Together, this integrated approach helps build a world that is safer, healthier and more resilient.
