The new study, published in Nature Communications under the title Improving coupled cluster theory for strongly correlated molecules with Kohn-Sham density encoding, was led by first author Abdulrahman Zamani, a postdoctoral associate in Kay Carter-Fenk’s group in the Department of Chemistry in the Kenneth P. Dietrich School of Arts and Sciences, together with undergraduate researcher Andrew Ricciuti. They collaborated with John Keith, professor of chemical and petroleum engineering in the Swanson School of Engineering, and his PhD student Barbaro Zulueta. The collaboration itself grew out of a practical engineering problem: Keith and Zulueta were trying to model chromium in order to design better stainless steels for the Navy, and they kept running into the same wall that has frustrated computational chemists for decades.

To understand why that wall exists, it helps to look at the two dominant tools of modern quantum chemistry. The first, coupled cluster theory, is widely regarded as the gold standard for predicting how atoms interact and undergo reactions. It begins with a simplified picture in which each electron moves through the average electric field created by all the others, and then systematically refines that picture by adding back the missing energetics of electron pairs, then triples, and so on. For many molecules, this stepwise correction scheme delivers extraordinarily accurate results. The catch is cost: the computational expense of coupled cluster calculations rises steeply as molecules grow larger, which restricts the method to relatively small systems even on powerful supercomputers.

The second tool, density functional theory, or DFT, takes the opposite approach. Instead of tracking individual electrons, it works with a simpler picture of the overall electron density, which makes it far more efficient and therefore suitable for larger and more complex systems. But that efficiency comes at a price. DFT relies on several cost-cutting approximations and on parameters that researchers have not yet perfected, so its results can be inaccurate in ways that are hard to predict in advance. Neither method, unfortunately, handles abundant transition metals such as iron, cobalt, and chromium well, and chromium in particular has earned a reputation as one of the hardest elements to model accurately.

Keith offers a vivid way to picture the problem. Chromium is a fairly small metal atom, but its electrons are especially crowded into compact orbitals, like residents squeezed into tiny apartments, and modeling those crowded electrons is notoriously tricky. This crowding is what chemists call the strong correlation problem, a situation in which electrons interact so strongly with one another that the simple average-field starting picture breaks down. When that happens, coupled cluster theory can fail outright, and DFT becomes the fallback of choice, even though its accuracy in these cases is, as the Pittsburgh team puts it, hit or miss. Zulueta noted that the community loves using coupled cluster when it can, but with chromium the crowded electrons make the method break, and DFT is used instead with mixed success.

The breakthrough came when the engineers reached out to their colleagues in chemistry. Carter-Fenk and her group are experts in modeling strongly correlated electrons, and together the two teams dug into the accumulated empirical evidence from the literature. Researchers had long observed that DFT sometimes, but not always, provides a better starting picture of crowded transition metal electrons than the reference point normally used with coupled cluster calculations. The prevailing explanation was that DFT simply produced better orbitals, but Carter-Fenk found that reasoning unconvincing. Coupled cluster theory does not care what the individual orbitals look like, she explained, comparing the situation to describing a room: you can use different sets of directions to say where things are, but the room itself does not change. The effect had to be rooted in the underlying mathematics.

Once that insight clicked, the team worked out how to make the approach reliable, achieving the demanding standard known as chemical accuracy for many difficult combinations of atom pairs that standard coupled cluster and DFT both model poorly. Ordinarily, reaching that level of reliably high accuracy on such systems requires weeks or months of supercomputing time. Using coupled cluster theory in the way the Pittsburgh team developed, they obtained almost as good accuracies in minutes to hours, a speedup that could fundamentally change which problems are considered tractable in computational materials science.

A key ingredient in making the method dependable was a simple diagnostic developed in Carter-Fenk’s group. As Zamani explained, the team created a mathematical model that finds the difference between the two starting electron densities and distills that difference into a single number. The magnitude of that number indicates whether the DFT starting point is beneficial for a given molecule or not. In other words, chemists no longer need to guess whether the DFT-informed approach will help; they can compute a diagnostic value first and know in advance whether the strategy will deliver the accuracy they need. That kind of a priori guidance is rare in a field where method selection often depends on trial, error, and intuition.

The implications extend well beyond the immediate improvement in simulation speed. Most machine-learning models in chemistry, including the rapidly growing family of AI tools used to screen candidate materials and catalysts, are trained on datasets generated by DFT calculations. When those datasets involve strongly correlated systems containing chromium, the underlying DFT data is unreliable, which means the AI models inherit those errors. Carter-Fenk emphasized that the new approach helps ensure researchers will get more reliable data, effectively upgrading the foundation on which machine-learning potentials are built. Because the method produces coupled-cluster-quality results at a fraction of the usual cost, it could immediately improve the training data used across the field.

Keith summed up the broader vision: the team now has a pathway to make coupled cluster theory accessible to metals, which will lead to improved machine-learning methods and better models for complex systems such as stainless steel and heavy lanthanides and actinides. In the long run, those improvements could accelerate the discovery of new materials and catalysts, supporting the transition to a cleaner and more sustainable energy future. For now, the work stands as a reminder that progress in computational chemistry often comes not from inventing entirely new theories but from understanding, at the level of the underlying mathematics, why existing tools behave the way they do, and then finding the right starting place for the electrons that matter most.

Subject of Research: Improving coupled cluster quantum chemistry methods for strongly correlated transition metal molecules

Article Title: Finding the right starting place for chemistry’s most difficult molecules

Article References: Finding the right starting place for chemistry’s most difficult molecules. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: coupled cluster theory, density functional theory, transition metals, strong correlation, chromium, stainless steel, quantum chemistry, machine learning, computational chemistry, catalysts, materials science, University of Pittsburgh

Retinitis pigmentosa is a group of inherited retinal degenerations that affects more than 1.5 million people worldwide. The disease progressively destroys the retina’s photoreceptors, the rods and cones that normally capture light and convert it into electrical signals for the brain. Patients typically first notice difficulty seeing at night, followed by a narrowing of peripheral vision that worsens over years, ultimately leading to severe vision loss or blindness. Because the retina is part of the central nervous system, its capacity for self-repair is extremely limited, and once photoreceptors are lost they are not naturally replaced.

One of the central obstacles to treating the disease is its sheer genetic diversity. Retinitis pigmentosa can arise from mutations in any one of more than 100 distinct genes, which makes a mutation-by-mutation strategy impractical for most patients. Gene therapies that correct specific defects have succeeded for other blinding conditions, but building and validating a separate treatment for every causative gene is proving tremendously difficult and costly. The Pittsburgh-led team, under the direction of José-Alain Sahel, chair of ophthalmology at Pitt and director of the UPMC Vision Institute, pursued a fundamentally different logic: rather than fixing the underlying mutation, the therapy aims to make surviving retinal cells light-sensitive again, regardless of which gene caused the degeneration.

The technical approach relies on optogenetics, in which cells are genetically altered to produce light-sensing proteins borrowed from other organisms. In this trial, the researchers delivered a gene encoding a protein called ChrimsonR into surviving retinal ganglion cells through a single injection into the eye. Retinal ganglion cells are the output neurons of the retina; in a healthy eye they relay signals from photoreceptors to the brain, and in advanced retinitis pigmentosa many of them remain viable even after the light-sensing cells above them have died. By equipping these surviving cells with an engineered light-sensitive protein, the therapy effectively converts the retina’s output neurons into a substitute photoreceptor layer.

ChrimsonR alone is not enough, however. The protein responds to specific wavelengths of amber-red light, and ordinary ambient illumination is not structured in a way the modified cells can interpret usefully. To bridge that gap, participants wear specialized goggles with a built-in camera that captures the visual scene and sends the information to a portable processor. The processor converts the image into patterns of light at wavelengths designed to activate ChrimsonR, and a projector inside the goggles projects those patterns back onto the retina. The system can, for example, transform the image of a hand into a simplified pattern of light that stimulates the treated cells, allowing the brain to receive visual information through a completely rewired pathway.

On safety, the early-stage trial delivered encouraging results. Most eye-related side effects were mild or moderate, consisting mainly of temporary inflammation and short-lived increases in pressure inside the eye. No findings reported in the release suggested the therapy itself caused lasting harm, an important benchmark for a treatment that involves permanently introducing a new light-sensing protein into neural tissue. The researchers emphasize that this was a small, early-stage study, and that the treatment did not restore normal vision or the ability to read. Even so, some participants became better able to detect when an object was present, determine where it was located, and reach toward it accurately while using the goggles, functional abilities that can translate into greater independence in daily life.

The study went beyond behavioral testing to ask whether the new visual signals were actually reaching the brain. Using electroencephalography, a team led by Marlene Behrmann, professor of ophthalmology at Pitt, found evidence that visual signals reached and were processed by the visual cortex when participants viewed objects. That finding is scientifically striking, because it suggests that in people with profound, long-standing vision loss, the brain’s visual processing machinery remains intact and capable of interpreting input delivered through an entirely novel channel. Four participants showed consistent improvements across multiple real-world visual tasks over months to years of testing, indicating that the gains were not fleeting artifacts of a single laboratory session.

Sahel noted that the results demonstrate the visual system retains a remarkable capacity to process new information even after profound vision loss. He also pointed to the approach’s broader potential: because the strategy targets surviving retinal ganglion cells rather than any specific mutation, it could in principle help patients with other blinding diseases in which light-sensing cells have been lost but ganglion cells remain viable, a group that currently has few or no treatment options. That mutation-agnostic design is what distinguishes optogenetic therapy from the growing but still narrow portfolio of gene-specific treatments.

The new findings build directly on a landmark 2021 study published in Nature Medicine, which reported the first partial recovery of visual function in a blind patient following optogenetic therapy, the first clinical application of optogenetics in medicine. That work, carried out with longtime collaborator Botond Roska of the Institute of Molecular and Clinical Ophthalmology Basel, who is also a corresponding author of the current study, earned the two researchers the António Champalimaud Vision Award, the largest prize in the field, last month. The current trial was conducted as part of the PIONEER clinical study with support from GenSight Biologics, and included collaborators from Sorbonne Université, Institut de la Vision, and L’Hôpital Fondation Adolphe de Rothschild in Paris, the Institute of Molecular and Clinical Ophthalmology Basel and University of Basel in Switzerland, Streetlab in Paris, and Moorfields Eye Hospital in London.

The optogenetic program is one of several complementary strategies the Pittsburgh-led team is pursuing for end-stage retinal disease. Last year, Sahel was senior author of a New England Journal of Medicine paper describing vision restoration using an implanted prosthetic device, known as PRIMA, in patients with end-stage age-related macular degeneration. That technology has since received European Union authorization to be marketed for clinical use in many European countries. Together, the two approaches illustrate a shifting landscape in which blindness once considered irreversible is being reclassified as a engineering problem: if light-sensing cells are gone, the task becomes finding surviving neural tissue that can be repurposed to carry visual signals, whether by genetically reprogramming ganglion cells or by implanting a photovoltaic prosthetic. For the retinitis pigmentosa community, the new trial offers the strongest evidence yet that such repurposing can work safely in humans, while underscoring how much work remains before the therapy could move from a small trial toward approved, widely available treatment.

Subject of Research: Optogenetic gene therapy for restoring visual function in advanced retinitis pigmentosa

Article Title: Optogenetic therapy safe, shows signs of vision restoration in patients with advanced retinitis pigmentosa, according to international study led by Pitt scientists

Article References: Optogenetic therapy safe, shows signs of vision restoration in patients with advanced retinitis pigmentosa, according to international study led by Pitt scientists. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: optogenetics, retinitis pigmentosa, gene therapy, retinal ganglion cells, ChrimsonR, visual prosthesis, New England Journal of Medicine, University of Pittsburgh, vision restoration, clinical trial, retinal degeneration, visual cortex

The technical logic behind the initiative rests on a simple observation: lasers have become one of the most versatile tools in modern manufacturing, and the skills to wield them are in short supply. High-power fiber lasers and pulsed laser systems now perform cutting, welding, surface treatment and precision drilling across industries ranging from shipbuilding to energy to semiconductor fabrication. Kevin P. Chen, the Paul E. Lego Chair Professor of Electrical and Computer Engineering at the Swanson School and the project’s principal investigator, argues that experienced industrial workers already possess much of the foundational competence these careers demand. “Southwestern Pennsylvania built its economy on making things, and lasers are increasingly part of how those things are made,” Chen said. “Experienced workers bring valuable skills in safety, problem-solving and operating in demanding environments. This project builds on that experience with the laser-processing skills needed for new opportunities in advanced manufacturing.”

Two training programs anchor the workforce side of the project. The first, Advanced Laser Processing, is a 10-week hands-on course that will run twice a year at the United Mine Workers of America Career Center in Greene County. Participants will learn to operate high-power fiber and pulsed lasers, program motion control systems in G-code, and apply laser welding, surface treatment and precision drilling techniques before completing a two-week capstone on industry-grade equipment. The curriculum deliberately mirrors the toolchain of a modern laser job shop: a technician who can set beam parameters, align optics, program multi-axis motion, and understand how pulse duration and power density interact with different metals is immediately employable in sectors where micron-level tolerances determine product quality.

The second program, Fiber Optic Sensing, was developed with the International Brotherhood of Electrical Workers training school and targets a different but equally urgent skills gap. Distributed fiber-optic sensors — which use the light-scattering properties of optical fiber itself to measure temperature, strain and acoustic signals along kilometers of cable — have become essential infrastructure for AI data centers, power systems and other critical facilities. These systems can detect hot spots in electrical infrastructure, identify fires before they spread, and monitor equipment health in real time, but they require trained electricians to install, calibrate and maintain them. The program will prepare union electricians to deploy these sensing networks, positioning them for work in the rapidly expanding data center economy that is reshaping regional energy demand. Both programs award a certificate of completion, connect graduates directly to hiring partners, and require no college degree to enter. Together they aim to train at least 320 participants — 120 in Advanced Laser Processing and 200 in Fiber Optic Sensing.

ARC Federal Co-Chair Gayle Manchin framed the award as an investment in the region’s long-term economic resilience. “Building a workforce equipped with the skills needed for emerging industries is essential to creating a path to lasting economic vitality throughout Appalachia,” Manchin said. “Through our POWER initiative, ARC is proud to support the University of Pittsburgh as it connects workers with the training needed to pursue high-quality careers in growing fields. Not only will the Pittsburgh Laser Engine help strengthen the region’s workforce, but it will also prepare communities across Southwestern Pennsylvania to compete in an evolving economy.”

Beyond the classroom, the project will establish a laser engineering center designed to give regional companies access to equipment and expertise that would otherwise be difficult or costly to obtain. Pitt and Robert Morris will combine their existing laser facilities with new instrumentation, including a femtosecond laser system capable of nanometer-scale precision and an ultra-high vacuum processing facility for cryogenic and quantum work. Femtosecond lasers, which deliver pulses lasting quadrillionths of a second, remove material with so little heat transfer that they can machine features with minimal thermal damage — a capability critical for medical devices, microelectronics and optical components. The combined operation will open to outside users as what the team calls a Laser Maker Space, with the goal of serving 40 regional businesses, helping at least 20 of them post measurable gains in productivity or competitiveness, and helping participating companies collectively secure more than $3 million in federal and private investment by the project’s close in April 2029.

The center’s longer-term research ambitions extend into some of the most demanding frontiers of photonics. The Pittsburgh Laser Engine aims to advance stand-off laser sensing, the fabrication of radiation-hardened distributed optical sensors, target manufacturing for inertial confinement fusion, and advanced diamond processing. Inertial confinement fusion — the approach that achieved scientific ignition at the National Ignition Facility — depends on fuel capsules and targets manufactured to extraordinarily tight specifications, and laser-based fabrication is central to producing them. Radiation-hardened optical sensors, meanwhile, are needed for nuclear facilities and space applications where conventional electronics degrade. To guide this portfolio, the center has assembled a leadership group that includes Dr. Yongfeng Lu, former president of the Laser Institute of America, as technical director, and Dr. Ming-Jun Li, a Corning Corporate Fellow and National Inventors Hall of Fame inductee, in a board role.

The economic case for the project is grounded in stark regional data. Between 2010 and 2020, Greene County’s population fell 7.1 percent and Westmoreland County’s fell 2.9 percent, even as the nation as a whole grew 7.4 percent. Southwestern Pennsylvania also loses roughly half of its college graduates to out-migration, even as employers in photonics and advanced manufacturing report they cannot fill skilled technical openings. The market opportunity is substantial: the U.S. laser processing market is worth $5.1 billion and growing about 8.5 percent annually, and the photonics sector is projected to need 42,000 new technicians nationally by 2030. Chen believes the region’s industrial heritage positions it unusually well to capture that growth. “Greater Pittsburgh has been a manufacturing powerhouse for the United States for generations, and today our region is home to world-class capabilities across the laser and photonics ecosystem,” Chen said, citing companies such as Coherent in laser and photonics technologies and Aerotech in precision motion control and automation. “We believe Pittsburgh has the ingredients to become a national hub for laser and photonics manufacturing and the high-paying skilled jobs that come with it.”

The project arrives with unusually broad regional backing. Nineteen organizations submitted letters of support, including the Naval Nuclear Laboratory, the National Energy Technology Laboratory, AIM Photonics, the Penn State Electro-Optics Center, Coherent, Corning, Aerotech, ANSYS, Lake Shore Cryotronics, MECCO, TRUMPF and Thorlabs, along with startups Laser Universal, AiMiLi, Z9 Machining and Dvorchak Enterprises and the City of Pittsburgh. Separately, 17 corporate partners have committed more than $2.2 million in equipment donations, according to Chen, giving trainees access to the same commercial systems they will encounter on the job. The Engineering Education Research Center at Pitt will evaluate learning outcomes for both training programs, an accountability measure intended to ensure the curricula deliver measurable workforce results.

For Michele V. Manuel, the U. S. Steel Dean of the Swanson School, the initiative represents a deliberate fusion of university research capacity and vocational training infrastructure. “Regional manufacturers need access to advanced equipment and technical expertise, while workers need pathways into fields such as laser processing and fiber-optic sensing; the Pittsburgh Laser Engine is designed to address both needs at the same time,” Manuel said. The Swanson School’s approach brings cutting-edge research in laser processing, photonics, AI and fiber-optic sensing directly into hands-on vocational programs, pairing the school’s technical expertise with the practical training infrastructure of its union and workforce partners. If the project meets its targets, the result will be a region that once defined itself by coal and steel defining its next chapter by the manipulation of light — one trained technician, one fiber sensor and one precision weld at a time.

Subject of Research: A federally funded workforce training and laser manufacturing innovation initiative in Southwestern Pennsylvania

Article Title: University of Pittsburgh wins $1.62 million ARC grant to launch Pittsburgh Laser Engine

Article References: University of Pittsburgh wins $1.62 million ARC grant to launch Pittsburgh Laser Engine. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Appalachian Regional Commission, University of Pittsburgh, laser processing, fiber-optic sensing, workforce development, coal communities, advanced manufacturing, photonics, POWER Initiative, AI data centers, Swanson School of Engineering, Southwestern Pennsylvania

The Moore Foundation’s Experimental Physics Investigator initiative is deliberately structured to fund what traditional grant programs often cannot. Launched in 2022, the program is designed to back bold new directions and ambitious, potentially high-payoff projects that might struggle to attract this level and duration of support from conventional funding sources. It plans to support roughly 120 mid-career scientists across six annual cohorts, and it is open to researchers from any scientific discipline. The only requirement is that the core science be experimental physics, a bar that Fullerton clears through work that spans chemistry, materials science, and device physics all at once.

Fullerton leads the Nanoionics and Electronics Lab at Pitt, where her group pursues an idea that sounds almost paradoxical: using ions, the charged atoms and molecules more familiar from batteries and electrolytes, as active components inside electronic devices rather than as contaminants to be eliminated. Her winning project, titled “Structure and Dynamics of Electric Double Layers on Two-Dimensional Crystals,” focuses on what happens when ions are used to control charge in transistors built from molecularly thin materials, crystals just one or a few atoms thick.

The physics at the heart of the project is subtle. When ions are brought to the surface of a two-dimensional crystal, they arrange themselves into an electric double layer, an ultrathin, densely packed sheet of charge separation that sits directly against the transistor channel. This buried structure is what allows ions to gate, or switch, the flow of electrons through the device, and it is the reason ion-controlled devices can in principle operate at extraordinarily low power. Yet despite its central role, the double layer has never been directly measured. Researchers know it exists and can infer its effects from electrical behavior, but its precise geometry and dynamics remain hidden.

That gap between inference and observation is what has made device development in this field so dependent on trial and error. According to Fullerton, it is difficult to deliberately engineer these devices without knowing precisely where the ions are located or how they move. She has spent more than twelve years building ion-controlled devices while relying on theory and indirect clues to guide the design process. “Throughout my 12 years of research, colleagues have been asking me the same question: ‘Where are the ions?'” Fullerton said. “It’s difficult to answer – it’s like trying to measure the thickness of a single sheet of paper hidden in the middle of a giant textbook, but without opening the book.”

The Moore award gives her team the resources to open that book. The project will combine neutron measurements, which offer a way to distinguish between different types of atomically light atoms, with surface probes and precise electrical measurements. Each technique provides a different view of the buried interface. Neutron scattering is particularly well suited to the problem because neutrons interact strongly with light elements such as hydrogen, lithium, and sodium, the very species that make up many of the ions used in these devices, and because they can penetrate the surrounding materials without destroying the delicate structures being studied. Layered together, the three approaches should allow the researchers to connect the ions’ physical structure and movement with the electronic behavior of the device, replacing empirical guesswork with rational design.

The motivation for pursuing ion-based computing extends beyond scientific curiosity. “Our brains process vast amounts of real-time data at a fraction of the energy required by standard silicon chips,” Fullerton said. “Next-generation AI and autonomous devices will need that same ultra-low-power efficiency to make real-time decisions at the ‘edge,’ and that’s going to require computing with ions, not just electrons.” The comparison captures the scale of the challenge. As artificial intelligence and sensing systems migrate away from centralized data centers and into autonomous vehicles, drones, medical implants, and remote sensors, the energy budget of every computation matters. Devices that move ions the way biological systems do could, in principle, approach the efficiency of neural processing in a way that conventional silicon transistors cannot.

Two-dimensional crystals are the enabling platform for this vision. Materials such as graphene and related atomically thin compounds can be stacked and combined into devices whose active regions are only molecules thick, putting every charge carrier within reach of the surface. That geometry is precisely what makes ion control so effective, and also what makes the double layer so consequential: in a device this thin, a single layer of ions can dominate the entire electronic response. Understanding where those ions sit, how densely they pack, and how quickly they rearrange under an applied voltage is therefore not a peripheral detail but the central design problem.

The award’s structure reflects the long timeline such a measurement campaign requires. Five years of sustained support, plus dedicated funding for specialized equipment, gives the Nanoionics and Electronics Lab the freedom to build instrumentation, refine sample preparation, and iterate on measurement protocols without the pressure of short funding cycles. “The Moore Award allows us to build the team needed to tackle this problem at a scale standard funding simply can’t match,” Fullerton said. “I’m really excited; I’ve been waiting for an opportunity to answer this question for more than a decade.”

Within Pitt, the recognition is being framed as a signal of where engineering research is heading. Michele V. Manuel, U. S. Steel Dean of Engineering, said Fullerton’s selection reflects both the ambition and the interdisciplinary reach of her work. “Susan asks bold questions at the boundary of chemistry, materials, and physics, and she has the creativity and the persistence to answer them,” Manuel said. “We are proud to see her recognized among the nation’s most inventive experimental scientists.” If the project succeeds, the payoff could reach far beyond a single lab: a direct picture of the electric double layer on two-dimensional crystals would give device engineers everywhere the design rules they currently lack, and could accelerate the arrival of a generation of electronics that computes with ions as readily as today’s chips compute with electrons.

Subject of Research: Direct measurement of electric double layers on two-dimensional crystals for ion-based ultra-low-power electronics

Article Title: Pitt’s Susan Fullerton named a Moore Foundation 2026 Experimental Physics Investigator

Article References: Pitt’s Susan Fullerton named a Moore Foundation 2026 Experimental Physics Investigator. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Susan Fullerton, Gordon and Betty Moore Foundation, experimental physics, electric double layer, two-dimensional crystals, nanoionics, ultra-low-power electronics, neutron measurements, transistors, edge computing, University of Pittsburgh, ion transport

Khanna’s path to the chairmanship was, in a sense, an extended audition. During his fourteen months as interim chair, he undertook what colleagues describe as an unusually systematic listening exercise, meeting extensively with faculty, staff, and students while also engaging the department’s external partners in industry and government. The goal was not ceremonial. He wanted a granular picture of the department’s strengths, its unmet needs, and the opportunities where civil and environmental engineering could grow. Those conversations fed directly into concrete administrative changes, including strengthened departmental operations, more rigorous academic and faculty planning, and the creation of a CEE Honors and Awards Committee designed to formally recognize excellence within the department.

That record of translating consultation into action was central to the case for his permanent appointment. Michele V. Manuel, the U. S. Steel Dean of Engineering, praised Khanna’s interim tenure as a model of responsive leadership. In her assessment, he listened carefully to every constituency the department serves and then converted what he heard into institutional change. She noted that he understands the department deeply, has already strengthened its operations and planning processes, and articulates a clear vision for where civil and environmental engineering at Pitt can expand in education, research, and external engagement. For a school weighing candidates from a national search, that combination of institutional knowledge and demonstrated execution proved decisive.

The search itself was a formal affair, chaired by Sanjeev Shroff and conducted by a committee that drew representation from the department’s faculty, staff, and students, as well as from the Swanson School leadership and the CEE Visiting Committee. That breadth of participation reflected the stakes: the chair of a civil and environmental engineering department sits at the intersection of academic priorities and the practical demands of infrastructure agencies, engineering firms, and municipalities that depend on the department’s graduates and research. The committee’s recommendation of Khanna, following the national search, signaled confidence that an internal candidate offered the strongest vision for the department’s future.

Khanna’s own academic trajectory is unusually broad for a civil and environmental engineer, and it helps explain the interdisciplinary ambitions he brings to the role. He joined the University of Pittsburgh in 2010 and rose through the faculty ranks, being promoted to full professor in 2023. Between 2017 and 2022, he served as the department’s associate chair for graduate studies, a position that placed him in charge of graduate recruitment, admissions, orientation, academic requirements, and program development. He has also chaired faculty searches and sat on committees at both the school and university levels, giving him a comprehensive view of how the institution’s academic machinery operates.

His educational background spans chemical engineering, statistics, and applied mathematics. Khanna earned his bachelor of engineering in chemical engineering from Punjab University before moving to The Ohio State University, where he accumulated three graduate degrees: a master’s in applied statistics and both a master’s and a doctorate in chemical engineering. That quantitative foundation is evident in his scholarship, which treats environmental systems not as isolated problems but as interconnected networks that can be modeled, optimized, and stress-tested. His methodological toolkit includes systems analysis, life-cycle assessment, optimization techniques, and data-driven modeling, all deployed to examine the environmental consequences of emerging technologies and complex engineered systems.

The subject matter of that research reads like a map of the challenges confronting infrastructure in the twenty-first century. Khanna has focused on water and resource recovery, exploring how wastewater and industrial byproducts can be transformed from liabilities into assets. He has examined the circular economy, asking how materials can circulate through the economy repeatedly rather than flowing from extraction to disposal. His work on resilient infrastructure addresses how civil systems can be designed to withstand shocks, whether from climate-driven extremes or other disruptions, and he has investigated emerging energy and water technologies that promise to decarbonize and democratize access to essential services. The through-line is a conviction that environmental performance must be quantified rigorously before it can be improved.

The scholarly record supporting that conviction is substantial. Khanna has published more than 75 peer-reviewed articles and has served as principal investigator or co-principal investigator on nearly $10 million in externally funded collaborative research, a figure that reflects both the competitiveness of his proposals and the collaborative character of his science. Since 2017, he has served as an editor of Resources, Conservation and Recycling, one of the leading journals in the field of resource sustainability, where he has helped shape the scientific conversation around material flows and circularity. His professional service extends to leadership roles within the Sustainable Engineering Forum of the American Institute of Chemical Engineers, and he participated in the National Academy of Engineering’s Frontiers of Engineering Education Symposium, a program that convenes rising leaders to rethink how engineers are trained.

Now, as permanent chair, Khanna has laid out a forward-looking agenda built on the premise that civil and environmental engineering is inherently interdisciplinary and should be organized as such. Among his stated priorities is a deeper integration of artificial intelligence into the department’s curricula, ensuring that graduates are fluent in the machine learning and data analysis tools increasingly used to design, monitor, and manage infrastructure. He also plans to develop new graduate pathways that connect civil and environmental engineering with public health and computing, formalizing the links between water quality, environmental conditions, and human health outcomes. In parallel, he intends to expand IRISE, the department’s initiative in resilient and intelligent infrastructure, and grow its partnerships, while strengthening research at the nexus of water, the environment, and public health.

The vision, as Khanna himself frames it, is grounded in the everyday ubiquity of the discipline he now leads. Civil and environmental engineering, he notes, shapes the systems that people rely on every single day, from the water that arrives at the tap to the roads and bridges that carry daily commutes. His ambition is to strengthen those systems through interdisciplinary education and research, working alongside the department’s faculty, staff, students, and external partners. In an era when infrastructure must simultaneously adapt to climate change, incorporate intelligent technologies, and serve public health, the University of Pittsburgh has placed its confidence in a leader whose entire career has been devoted to quantifying and improving the environmental performance of the systems that hold modern life together.

Subject of Research: Appointment of sustainability researcher Vikas Khanna as Chair of Civil and Environmental Engineering at the University of Pittsburgh Swanson School of Engineering

Article Title: Vikas Khanna named Chair of Civil and Environmental Engineering at Pitt

Article References: Vikas Khanna named Chair of Civil and Environmental Engineering at Pitt. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Vikas Khanna, University of Pittsburgh, Swanson School of Engineering, civil engineering, environmental engineering, sustainability, life-cycle assessment, circular economy, resilient infrastructure, artificial intelligence, water resource recovery, public health