The grant supports ongoing development and testing; the announcement does not present the platform as a completed clinical technology or report outcomes in patients. PET radiotracers are compounds that combine a tiny amount of radioactive material with a biological molecule designed to seek a specific target in the body, such as a protein found on cancer cells. Once injected, the radioactive signal is detected by a PET scanner, which creates an image showing where the tracer has accumulated.

Unlike imaging methods that primarily show anatomical structures, PET can reveal biological activity inside the body, including the presence and location of particular molecules or processes and changes over time. The project addresses a bottleneck in translational imaging: scientists can identify promising biological markers more quickly than they can convert them into usable PET tracers. Incorporating radioactive material into a candidate molecule is time-consuming and technically demanding, requiring specialized equipment and facilities.

The USC team’s platform is intended to reduce that production burden by pairing a universal radioactive building block with different biological molecules. In principle, the same compact setup could generate several tracer candidates rather than requiring a separate production configuration for every compound. The announced work focuses on developing that approach, not on an already validated system for routine clinical use.

At the center of the platform are two radiochemistry approaches: click chemistry, which allows molecules to be joined quickly, and droplet radiochemistry, which carries out chemical reactions in extremely small droplets and therefore uses tiny amounts of material. Kai Chen, PhD, a professor of research radiology, radiation oncology, and pharmacology and pharmaceutical sciences at USC, is leading the project with collaborators at UCLA. The device they are building uses a tiny chip to combine the universal radioactive building block with selected biological molecules.

Chen said concentrating the process on the chip could enable radiotracers to be produced rapidly and efficiently, with less reliance on traditional large-scale equipment and dedicated facilities. Preliminary research suggests that the approach can generate radiotracers for multiple cancer biomarkers on a very small scale. One candidate is designed to target fibroblast activation protein, which is found at high levels in many tumors.

The team is also testing tracers intended specifically to detect liver and prostate cancer. Chen said these findings show that click chemistry can rapidly generate tracers for multiple cancer biomarkers and that the compounds can be produced at miniature scale. The results provide early evidence for the platform’s underlying chemistry, but the announcement does not report human diagnostic performance, improved clinical outcomes or a final device ready for routine use.

The next one to two years of the funded project are expected to focus on optimizing the compact device and testing a broader range of radiotracers. The researchers plan to compare some candidates with established tracers to determine how well they perform. After that testing, the team intends to build and refine the final device, conduct quality control and complete preclinical testing before working toward clinical applications.

These are planned stages of the research program. The grant announcement therefore supports a development roadmap involving optimization, comparative evaluation, quality control and preclinical assessment rather than a completed demonstration of clinical benefit. If the platform succeeds, automating and simplifying radiotracer production could lower costs and reduce the resources required to create new tracers.

The USC team says this could make it possible to produce a wider range of customized tracers and potentially expand access to PET imaging. More specialized agents could allow researchers and medical providers to examine molecular features of tumors and track changes over time. Such information could help assess treatment response earlier and more precisely, potentially indicating sooner whether a therapy is working or whether a different approach is needed.

Those benefits are possibilities that depend on successful development and validation of particular tracers, not outcomes already established by the grant-funded project. The modular platform may also be adapted beyond cancer. The researchers are considering uses for radiotracers targeting conditions including neurological diseases, reflecting the broader objective of expanding PET imaging into additional areas of medicine.

Because the construction combines a reusable radioactive building block with biological molecules designed for different targets, the system could support more than one type of tracer. The supplied announcement does not report completed neurological studies or patient cohorts, so that application remains prospective. It also does not establish how broadly the platform could be deployed or what effect it will ultimately have on PET availability.

The program brings together imaging science, chemistry and engineering, with support from NIH grant R01EB040161. Joshua Hirsch, MD, chair of USC’s Department of Radiology and the Stewart Dale Fordham, MD, Chair in Radiology, said the award recognizes the team’s innovative work and its potential to make advanced molecular imaging more accessible, accelerate radiotracer development and ultimately provide better tools for diagnosis and personalized treatment. Those statements describe the anticipated impact of the project.

The demonstrated work to date consists of a miniaturized radiochemistry concept supported by preliminary radiotracer-generation results, while optimization, broader tracer testing, preclinical evaluation and subsequent clinical development remain ahead.

Subject of Research: A compact radiochemistry platform for producing PET radiotracers targeting cancer biomarkers.

Article Title: USC researchers launch effort to expand PET imaging for cancer and other diseases

Article References: USC researchers launch effort to expand PET imaging for cancer and other diseases. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: PET imaging, radiotracers, radiochemistry, cancer imaging, click chemistry, droplet radiochemistry, molecular imaging, USC, NIH funding, diagnostic imaging, researchers, launch

The finding offers a cell-level clue about age-related changes in the ability to solve new problems. Fluid intelligence was assessed as part of a broader series of cognitive tests administered before surgery, covering reasoning, memory, attention, language and fine motor coordination. After surgery, researchers used microscopy to identify and count immature astroglia in selected areas of the hippocampus, a brain region involved in learning and memory. Older patients generally had more of the abnormal cells, while greater cell numbers were also associated with lower fluid-intelligence scores. The investigators described the work as one of the first studies to associate astroglial abundance with human cognition.

Astroglia have traditionally been viewed primarily as support cells that help maintain a healthy environment around neurons and support their communication. Their role in cognition has received less attention than that of neurons and has often been investigated through animal models or indirect measures such as gene activity. The new research differs by examining human tissue directly and quantifying the presence of immature astroglia. “We found that older patients tended to have more abnormal immature astroglia—and that higher numbers of these cells were also associated with poorer performance on tests of fluid intelligence,” said first author Aswathy Ammothumkandy, PhD, of the USC Stem Cell lab.

The research was made possible by the unusual availability of tissue removed during surgery to treat severe, drug-resistant seizures caused by mesial temporal lobe epilepsy. The operation yielded hippocampal tissue from 29 patients, allowing the team to pair cellular observations with cognitive testing conducted beforehand. This design provided a rare opportunity to study individual cells in a human brain and compare them with measured reasoning performance. The approach also illustrates why the findings should be interpreted as an association: the small, selected surgical population had epilepsy, and the investigators did not show that removing or changing the cells would alter cognition.

Non-invasive tools commonly used to study brain function, including electroencephalography and magnetic resonance imaging, generally do not resolve individual cells well enough for this type of cell-count analysis. Microscopic examination can reveal cellular features in detail, but tissue from living people is rarely available for research outside specialized clinical circumstances. Here, the integration of clinical care, cognitive assessment, surgery and laboratory analysis gave researchers access to matched biological and behavioral information. The participants’ epilepsy and the surgical context remain central limitations on how broadly the results can be generalized, even though the study was supported in part by the National Institutes of Health and published in Frontiers in Cellular Neuroscience.

Mesial temporal lobe epilepsy can involve seizures and cognitive decline, making the population clinically relevant but also distinctive. The researchers said the findings could have implications beyond epilepsy, and they emphasized that aging affects everyone. “Aging is something we’re all familiar with and all impacted by—it’s a matter of when, not if,” said co-corresponding author Michael Bonaguidi, PhD, who leads the USC Stem Cell lab. “What this study provides is a new therapeutic target that could someday help us slow down or potentially even reverse age-related declines in our ability to solve new problems.” The statement identifies a proposed research direction rather than a demonstrated treatment.

No drug, procedure or clinical intervention was tested in the study, and the researchers emphasized that further work is needed to determine whether abnormal immature astroglia contribute directly to cognitive decline. The data also do not establish that the cells are a cause of the age-related pattern; they could be a marker, a consequence, or part of a broader process involving epilepsy, aging and brain function. The authors’ suggestion that astroglia could represent a target for preserving cognition should therefore be understood as a hypothesis for future investigation, not an available treatment or an established clinical strategy. The scope of the evidence is especially limited because all participants were people undergoing surgery for severe, drug-resistant seizures.

Ammothumkandy is now investigating molecular differences among immature astroglia that might reveal possible drug targets. By comparing cells from people with epilepsy with control samples, she aims to identify features that distinguish abnormal cells and explore ways to restore them to a healthier state. Another possible avenue for future investigation is neuromodulation, which uses electrical or magnetic stimulation to alter nervous-system activity. The broader goal is to understand whether healthy or abnormal astroglial states might become accessible therapeutic targets for cognitive conditions, including accelerated age-related decline in people with epilepsy. These proposed approaches are described in the release as directions for research rather than interventions validated in the present experiment.

Charles Liu, MD, PhD, director of the USC Neurorestoration Center and a co-author of the study, said the work could benefit patients while informing wider questions about brain function. “Understanding processes like cognitive decline, which can be accelerated in people with epilepsy, could help us improve these patients’ lives while also shedding light on broader questions about brain function that affect us all,” Liu said. The authors also proposed that astroglia could be a shared target for cognitive decline and seizure control, based partly on previous work by the team. The present experiment, however, directly evaluated the relationship between immature astroglial abundance, age and fluid intelligence; it did not test seizure outcomes or show that targeting astroglia would improve either cognition or seizures.

For now, the most defensible conclusion is that abnormal immature astroglia become more prevalent with age in the hippocampus of this surgical epilepsy cohort and are associated with weaker performance on tests of fluid intelligence. The study supplies direct human-tissue evidence that warrants further investigation into why these cells accumulate, what molecular changes define their abnormal state and whether they actively impair reasoning. It does not establish a general-population trend, a direct causal mechanism or an available therapy. Instead, it identifies a specific cellular feature for additional investigation, with the eventual aim of determining whether modifying astroglial biology could protect cognitive function or support better control of epilepsy. The findings are strongest as an association in the 29-person surgical sample and should not yet be read as proof that abnormal immature astroglia drive age-related cognitive decline in people without epilepsy.

Subject of Research: Associations between immature hippocampal astroglia, age and fluid intelligence in adults with epilepsy

Article Title: Immature brain support cells may be linked to human age-related cognitive decline

Article References: Immature brain support cells may be linked to human age-related cognitive decline. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: astroglia, fluid intelligence, cognitive decline, hippocampus, epilepsy, brain tissue, aging, USC, human brain, cellular neuroscience, Immature, brain

The study was led by Marco Angrisani, senior economist at the USC Center for Economic and Social Research and associate professor (research) of economics at the USC Dornsife College of Letters, Arts and Sciences. Angrisani and his colleagues set out to answer a question that has troubled mental health researchers for decades: why do responses to large-scale societal stressors vary so dramatically from one person to the next? Their answer, drawn from one of the most extensive longitudinal datasets available, points to personality as a meaningful and measurable factor in shaping that heterogeneity. “There is a wide variety of mental health responses to large-scale societal stressors,” Angrisani said. “Our study shows that personality traits, and neuroticism in particular, play a role in shaping heterogeneous responses in a major crisis across individuals and could therefore inform better targeted interventions.”

The evidence base for these conclusions is unusually robust. The researchers followed 4,030 U.S. adults using data from the Understanding America Study, a nationally representative internet panel managed by the USC Center for Economic and Social Research. The analysis drew on more than 100,000 survey responses collected from 2019 through early 2024, a window that allowed the team to compare mental health before, during, and after the pandemic. That temporal span matters enormously. Cross-sectional studies conducted at a single point in time can show that distress was high during the pandemic, but they cannot reveal whether it rose, fell, or lingered afterward. By anchoring their measurements in pre-pandemic baselines and extending them well into the recovery period, the researchers could distinguish acute, transient distress from the kind of prolonged suffering that signals genuine vulnerability.

At the heart of the analysis were the so-called Big Five personality traits, the dominant framework in contemporary personality psychology. Neuroticism describes a tendency to experience worry, emotional sensitivity, and stronger reactions to stress or uncertainty. Extraversion captures the tendency to be outgoing, energetic, and motivated by social interaction. Openness reflects curiosity about new ideas and experiences and a willingness to consider change. Agreeableness denotes a tendency to be cooperative, trusting, and concerned about social harmony, while conscientiousness describes people who are organized, dependable, self-disciplined, and goal-oriented. Crucially, these characteristics exist on a continuum. Everyone possesses some degree of each trait, and a high or low score on any dimension does not constitute a disorder. The Big Five model is valued by researchers precisely because it reduces the enormous complexity of human temperament to five stable, measurable dimensions that can be tracked over time and correlated with real-world outcomes.

Mental distress in the study was measured with the PHQ-4, a brief validated questionnaire that assesses symptoms of anxiety and depression. A score of six or higher on the PHQ-4 indicates moderate-to-severe symptoms, although the instrument is a screening tool rather than a clinical diagnosis. Using this threshold, the researchers quantified how the probability of moderate or severe distress shifted across the pandemic for people at different points on the personality spectrum. The results were striking. Increases in the probability of moderate or severe distress were approximately 11 to 20 percentage points greater among participants who scored in the highest 25 percent for neuroticism compared with those in the lowest quarter. In practical terms, this means that highly neurotic individuals were dramatically more likely to cross the threshold into clinically significant distress as the crisis unfolded.

Just as important as the size of the effect was its persistence. The association between neuroticism and elevated distress held across young, middle-aged, and older adults, and it remained evident into the post-pandemic observation period. This durability is what distinguishes the finding from earlier work documenting short-lived spikes in anxiety during lockdowns. The pandemic has largely receded as an acute threat, yet the psychological shadow it cast appears to have lingered far longer for people high in neuroticism than for their more emotionally stable counterparts. For health systems still grappling with elevated demand for mental health services, that pattern suggests the pandemic’s toll was not merely an episode but, for a vulnerable segment of the population, a lasting shift.

The study also uncovered behavioral differences that may help explain the mechanism. Participants higher in neuroticism perceived greater health and financial risks during the crisis, adopted more protective behaviors, and reported exercising and relaxing less frequently while consuming more alcohol. These patterns sketch a coherent picture: people who react strongly to uncertainty tend to perceive danger more acutely, respond with heightened caution, and simultaneously withdraw from the very activities, such as exercise, relaxation, and moderate drinking habits, that buffer against psychological distress. Measurements of extraversion, openness, and agreeableness showed weaker or inconsistent associations with distress trajectories, while conscientiousness appeared modestly protective, particularly among adults aged 60 and older. That last finding hints that the self-discipline and structure characteristic of conscientious individuals may function as a psychological resource in older adults facing prolonged disruption.

The practical implications extend well beyond pandemic planning. The findings could help clinicians and emergency planners recognize who may need closer follow-up after disasters, public-health emergencies, or other prolonged disruptions. Public information campaigns could also be tested to ensure they inform people without unnecessarily increasing distress among those who are more vulnerable to it. Angrisani was careful to emphasize, however, that personality should be just one part of a broader risk assessment, considered alongside current symptoms, previous mental health conditions, and social circumstances, rather than serving as a label or an automatic trigger for treatment. Neuroticism is a risk factor, not a diagnosis, and it does not determine any individual’s mental health destiny. In the paper, the authors advocate for monitoring and stepped care: following people over time and offering treatments such as cognitive behavioral therapy or emotion-regulation training when significant, persistent symptoms emerge, rather than treating people solely because of a personality score.

Like all observational research, the study has limits that the authors acknowledge. It identifies associations and cannot prove that personality, especially neuroticism, caused the distress patterns observed. All personality and mental distress measures were self-reported, which introduces the possibility of reporting bias, and the findings may not generalize beyond the United States. Even so, the scale and duration of the dataset give the results considerable weight, and they point toward a concrete strategy for the future: crisis communication that emphasizes practical, controllable actions, combined with accessible mental health support, could help protect psychologically vulnerable groups when the next major disruption arrives. As climate events, geopolitical instability, and future pandemics test societies around the world, the USC-led study offers a deceptively simple insight with far-reaching consequences. The question of who will suffer most in a crisis may be partly answerable in advance, and answering it could mean the difference between reactive care and genuinely preventive support for the millions of people whose minds bear the longest scars of collective trauma.

Subject of Research: The influence of personality traits, particularly neuroticism, on the persistence of mental distress during and after the COVID-19 pandemic

Article Title: Personality traits influence level of lasting distress during a crisis, USC-led study finds

Article References: Personality traits influence level of lasting distress during a crisis, USC-led study finds. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: neuroticism, personality traits, Big Five, mental distress, COVID-19 pandemic, anxiety, depression, PHQ-4, Understanding America Study, stepped care, observational study, USC

The trial, formally known as Evaluation of Integrated Digital, Biomarker and Neurophysiological Tracking in Mindfulness-Assisted Psilocybin Therapy, or EVIDENT-MAP, is led by Rael Cahn, a clinical associate professor of psychiatry and the behavioral sciences at the Keck School of Medicine of USC, who also directs the USC Center for Mindfulness Science. Cahn and his colleagues hypothesize that the combination will help people with depression better integrate the insights that often surface during psychedelic sessions and sustain improvements in their symptoms long after the drug itself has left the body. The premise rests on a growing body of evidence from both laboratory and clinical settings suggesting that psilocybin can open a window of heightened neuroplasticity, a period in which the brain becomes unusually receptive to change, and that practices such as meditation may help patients walk through that window rather than watch it close.

Psilocybin’s therapeutic credentials have been building steadily over the past decade. The compound has shown promise in trials for depression and substance use disorder, and in 2019 the U.S. Food and Drug Administration granted breakthrough therapy designation to a psilocybin-based treatment for major depressive disorder, a move that accelerated clinical research into its effects. Yet a persistent challenge has been durability: even when psilocybin therapy produces dramatic reductions in depressive symptoms, those benefits can fade over weeks or months. This is where the USC team sees an opening. Previous studies of experienced meditators suggest that a long-standing meditation practice may enhance a person’s response to psychedelics, and the researchers have translated that observation into a structured mindfulness and meditation intervention specifically designed to amplify and extend the benefits of psychedelic therapy.

Psychedelics appear to ignite something in the brain and behavior that allows people to adopt new perspectives, according to Assal Habibi, an associate professor of psychology at the Brain and Creativity Institute at the USC Dornsife College of Letters, Arts and Sciences and one of the project’s principal investigators. But after that ignition, she explained, people need tools to help maintain the mindset of self-exploration and discovery that the experience opens up. The mindfulness program is intended to be exactly that toolkit. Participants assigned to the meditation arm will complete an eight-week course designed to cultivate mindful awareness, loving kindness and compassion, including daily meditation practice at home. The first of their two psilocybin sessions will fall between weeks two and three of the meditation program, so that a foundation of practice is already in place when the psychedelic experience begins.

The protocol itself reflects the current state of the art in psychedelic clinical research. Every participant, regardless of group, will complete two psilocybin sessions spaced about one month apart. Before the first session, each will attend six hours of preparatory psychotherapy to establish expectations and trust. Between the two sessions, and again after treatment is complete, participants will attend three integration sessions each, structured conversations designed to help them process and make sense of what they experienced. Cahn notes that during the psilocybin sessions themselves the team deliberately departs from the standard approach to psychotherapy, which tends to be structured and guided. Instead, the therapist serves more as a supportive observer than an active intervener, allowing the inner experience to unfold without direction.

What sets EVIDENT-MAP apart from many earlier psychedelic trials is the sheer density of measurement. Throughout the study, researchers will collect detailed data on each patient to track the therapy’s effects across multiple biological and behavioral levels. Electroencephalography and magnetic resonance imaging will capture changes in brain activity and structure. Saliva, blood and stool samples will allow investigators to examine molecular and microbial signatures that may correlate with recovery. Psychological and cognitive assessments will chart shifts in mood, thinking and emotional processing, and wearable trackers will supply continuous real-world data on sleep, activity and physiological rhythms between clinic visits. This multimodal approach aligns with the mission of ARPA-H’s EVIDENT initiative, which stands for Evidence-Based Validation & Innovation for Rapid Therapeutics in Behavioral Health and aims to accelerate behavioral health research through detailed, real-time clinical data collection, with de-identified data flowing into a secure national repository that researchers can mine for patterns associated with rapid changes in mental health.

The trial also builds directly on the team’s own prior work. An ongoing USC study has so far tested psilocybin combined with mindfulness training in 24 people without mental health conditions, and the early results have been striking. Cahn reports that almost everyone in that study described the experience as one of the most meaningful of their lives, even months later. The new trial now asks whether that same combination can improve the lives of people with depression, and whether mindfulness can deepen those benefits. The question is far from academic. Depression remains one of the world’s leading causes of disability, and a substantial fraction of patients do not respond adequately to existing antidepressant medications, fueling intense interest in novel mechanisms of action.

One of the trial’s most intriguing sub-experiments concerns music. Past research on psychedelic therapy has shown that a person’s physical surroundings, including the soundtrack playing during a session, can significantly shape the experience. Drawing on these findings, Habibi worked with a team of clinicians and music therapists to design a playlist aimed at enhancing the therapy’s effects. The songs are lyric-free and span a range of musical traditions, and they are carefully timed to align with the progression of psilocybin’s effects, with a highly emotional piece reserved for the period of peak intensity. After treatment is complete, researchers will collect MRI scans while patients listen to the same music, testing whether they can detect a brain signal linked to the therapeutic effects of the experience. The long-term ambition is provocative: if a specific musical sequence reliably evokes the neural signature of a beneficial psychedelic session, the same music might one day carry therapeutic utility on its own, without the use of psychedelics at all.

Behind the clinical design sits an unusually interdisciplinary team. In addition to Cahn and Habibi, the third principal investigator is Shrikanth Narayanan, a University Professor at USC who holds the Niki and Max Nikias Chair in Engineering and whose appointments span electrical and computer engineering, computer science, linguistics, pediatrics, otolaryngology-head and neck surgery, and music. That breadth reflects the study’s ambition to fuse neuroscience, contemplative science, computational analysis and the arts into a single experimental framework, using digital tools, brain measures and biological sampling to capture depression and its treatment with a granularity that traditional trials have rarely attempted.

For the field of psychedelic medicine, the stakes of EVIDENT-MAP extend well beyond a single trial. If mindfulness training demonstrably enhances and sustains the effects of psilocybin therapy, the result could reshape how psychedelic treatments are delivered, pairing a pharmacological intervention with a behavioral practice that patients can continue for a lifetime. If the combination shows no added benefit, that too would be informative, sharpening the field’s understanding of what actually drives lasting change after a psychedelic experience. Either way, the USC study represents a rigorous, heavily instrumented attempt to move psychedelic therapy from promising anecdote toward precision medicine, at a moment when federal agencies are willing to fund bold, high-impact research designed to transform outcomes in behavioral health. The results, expected to emerge as the 80 participants complete their sessions and follow-up assessments, will be watched closely by clinicians, regulators and the millions of people for whom conventional depression treatments have fallen short.

Subject of Research: A clinical trial of psilocybin therapy combined with mindfulness meditation for treating depression

Article Title: USC launches clinical trial of psilocybin and mindfulness meditation for depression

Article References: USC launches clinical trial of psilocybin and mindfulness meditation for depression. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: psilocybin, mindfulness meditation, depression, psychedelic therapy, clinical trial, ARPA-H, USC, neuroplasticity, EEG, MRI, breakthrough therapy, mental health

Optimization, in the technical sense, is the science of finding the best possible course of action when time, money, energy, materials or other resources are constrained. It underpins how airlines schedule crews, how utilities dispatch electricity, how warehouses route packages and how factories sequence production lines. Traditionally, these problems have been tackled with exact mathematical programming techniques such as linear, integer and mixed-integer programming, which can guarantee optimal solutions but often struggle when problems grow to enormous scale or when the underlying conditions are uncertain and fast-changing. AI4OPT was created to close that gap by teaching machines to solve such problems more efficiently, blending learning-based approaches with classical algorithmic methods.

The stakes are rising because the systems being optimized are themselves becoming more complicated and less predictable. Power grids that once relied on a manageable number of large, dispatchable generators must now integrate variable renewable sources, distributed storage, electric vehicle charging and fluctuating demand, all while operators respond faster than traditional planning cycles allow. Supply chains that span continents face shortages, geopolitical disruptions and shifting consumer patterns that can invalidate carefully built plans within hours. Manufacturing systems increasingly need to adapt production in near real time. In each case, the challenge is not simply computing a good plan once, but continuously recomputing and revising decisions as conditions change, under uncertainty and at scales that overwhelm conventional methods.

AI4OPT’s response is to develop intelligent systems capable of navigating that uncertainty, making complex decisions and responding quickly as conditions evolve. The researchers aim to explore how AI and optimization can work together to achieve advances that neither field could deliver on its own, and then to move those advances out of foundational research and into large-scale applications. In practice, this can mean using machine learning to guide the search of optimization solvers toward promising regions of an otherwise intractable solution space, using learned models to predict the uncertain inputs that an optimization model must account for, or embedding optimization layers inside learning systems so that the resulting decisions respect real-world physical and operational constraints.

At USC, the effort will be co-led by Bistra Dilkina, co-principal investigator of AI4OPT and the Dr. Allen and Charlotte Ginsburg Early Career Chair in Computer Science and associate professor of computer science at the USC Viterbi School of Engineering. Dilkina’s research focuses on advancing the state of the art in combinatorial optimization techniques for solving real-world large-scale problems, particularly those arising in sustainability domains such as biodiversity conservation planning and urban planning. That background in applying rigorous optimization to consequential societal problems mirrors the institute’s broader mission of translating basic science into tools with tangible impact.

“This renewal allows us to dig deeper into AI and optimization, moving basic science toward real-world applications that make a tangible difference in society,” Dilkina said. Her counterpart at the helm of the institute is Pascal Van Hentenryck, the A. Russell Chandler III Chair and professor at Georgia Tech, who will continue to serve as lead principal investigator. Alper Atamtürk of UC Berkeley joins as the third co-principal investigator, giving the renewed institute leadership distributed across three of the country’s leading research universities. “By fusing AI and optimization, AI4OPT is changing how we solve energy, supply chain and manufacturing challenges that are at the core of society,” Van Hentenryck said.

The renewal represents a substantial escalation of USC’s involvement. The university will receive $5.6 million, more than twice its funding during the institute’s first phase, and will expand its research team from two researchers to five. The new interdisciplinary team draws faculty from across USC Viterbi, the USC Mark and Mary Stevens School of Computing and Artificial Intelligence, and the USC Marshall School of Business, reflecting the fact that the problems AI4OPT targets are simultaneously technical, computational and economic. “With an expanded team and increased support, USC is excited to collaborate with our partners to push boundaries and amplify our collective strengths,” said Dilkina, who also co-directs the USC Center for AI in Society.

The potential applications span the critical infrastructure that modern society depends on. For utilities, intelligent optimization systems could help balance increasingly complex power grids, coordinating generation, storage and demand in ways that maintain reliability while accommodating clean energy resources whose output changes with weather and time of day. For manufacturers, the same underlying methods could adjust production schedules dynamically as materials, orders and machine availability shift. For supply chain operators, the tools could support rapid responses to shortages and disruptions, rerouting goods and reallocating inventory before small disturbances cascade into systemic failures. What unites these domains is the structure of the underlying problem: enormous numbers of interdependent decisions, hard constraints, uncertain and changing conditions, and severe penalties for slow or poor choices.

Beyond the research itself, the renewed institute places heavy emphasis on education, with initiatives that stretch from high school classrooms to doctoral training. As part of the renewal, USC will bring the Seth Bonder summer camp in computational and data science for engineering to high school students in Los Angeles, extending hands-on exposure to data-driven engineering methods to a new audience. At the graduate level, the institute’s presence at USC has already helped catalyze the university’s leadership in AI and optimization education, including the launch of the first PhD specialization and certificate in AI plus optimization, known as USC’s ORAI program, supported by a National Science Foundation Research Traineeship grant. Together, these efforts are designed to create educational pathways for students at different stages to build skills in AI, optimization and their real-world applications, addressing a persistent shortage of researchers who are fluent in both machine learning and mathematical decision science.

The five-year renewal through 2031 signals a long-horizon commitment to a research agenda that many experts consider essential for the energy transition and the resilience of global commerce. As AI systems move from generating text and images to making consequential operational decisions, the ability to guarantee that those decisions are feasible, efficient and robust becomes paramount. AI4OPT’s bet is that the fusion of learning and optimization is the key to that guarantee, and that the resulting methods will determine how well power grids, factories and supply chains absorb the shocks of a rapidly changing world. With USC’s expanded role, one of the country’s largest urban research universities is now positioned to shape both the science of that fusion and the workforce trained to deploy it.

Subject of Research: AI-driven optimization for power grid, manufacturing and supply chain decision-making

Article Title: USC joins $20M NSF effort to transform power grids and supply chains

Article References: USC joins $20M NSF effort to transform power grids and supply chains. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: artificial intelligence, optimization, power grids, supply chains, manufacturing, NSF, AI4OPT, USC, Georgia Tech, machine learning, combinatorial optimization, STEM education