Research applying artificial intelligence across science and engineering. Covers machine learning, sensing and quality control, immune and health prediction, and 5G networks.
A new study published in the journal Cognition found that people attribute less consciousness to AI than humans, even when AI behaves identically. Participants rated AI's responsiveness to its surroundings as more conscious than humans', but drew a clear line between intelligent behavior and consciousness.
NTU Singapore has successfully launched the CRIMSON-1 satellite, carrying pioneering perovskite solar cells and AI capabilities to test their performance in space. The satellite aims to evaluate lightweight perovskite solar technology and on-orbit AI-based image processing in extreme environments.
The articles discuss digital initiatives improving access to PMOS treatment in India, smart textiles' applications in medical care and climate adaptability, and the FDA's TEMPO pilot regulating AI-enabled devices. Researchers also explore the ethics of mining data from public forums.
Researchers used a visual illusion to examine AI vision capabilities, finding gaps in computation that affect spatial representations. Human observers and primate visual cortex showed similar responses to the illusion, highlighting the need for AI to replicate these computations.
This section will publish peer-reviewed research on the clinical value of AI in cardiovascular medicine, including evidence of effectiveness and impact on access and equity. Submissions are invited on various topics, including clinical diagnosis, multimodal data integration, and implementation in real-world cardiovascular care.
A new path-tracing method simulates event camera data from virtual 3D scenes efficiently, reducing computational costs for applications like autonomous driving and robotics. The method uses physically-based path tracing and adaptive temporal search to precisely determine event timings, enabling more efficient training-data generation.
A multi-year study by Radboud University found that primary school pupils who use an AI-supported learning tool learn arithmetic more quickly than those who don't. The teacher's role remains crucial, even with AI, as they oversee lessons and adapt to individual pupils' needs.
Satellite data can provide crucial information on renewable energy potential, land availability, and climate risks, enabling more strategic data center planning. The authors argue that governments and regulators should require satellite evidence in decision-making processes to support the clean energy transition.
The Peninsula Innovation District, a collaboration between the University of Tennessee and UT Medical, has received the 2026 Emerging Community of Innovation award. The award recognizes the district's potential for continued growth and its commitment to building sustainable ecosystems that move technology from early-stage ideas toward ...
A new computational model accounts for individual differences in human color vision, revealing why modern display colors can vary across viewers. The model suggests that adjusting the primary colors of a display can improve color consistency for a wider range of people.
A study by MIT researchers found that algorithmic monoculture, like using a single algorithm in hiring, can create informational echo chambers that hinder exploration. However, bundling multiple algorithms together can overcome this limitation, enabling monoculture to perform as well as or better than a polyculture.
Eisty's Software Analytics and Intelligence Lab aims to leverage AI in scientific software pipeline while maintaining reproducibility, correctness, and long-term utility. The team will evaluate AI-generated tests for scientific relevance and develop guidelines for responsible AI-assisted software testing across diverse research domains.
A new framework trains AI models to screen AI-generated content using performance data from past marketing campaigns. The models provide content recommendations and ratings, streamlining the decision-making process for marketers. Human capital plays a vital role in the successful use of these new technologies.
Researchers from the University of Osaka have successfully accelerated protons to record energies using ultrathin graphene and long-pulse lasers, demonstrating improved capabilities for long-pulse laser-driven ion acceleration. The team achieved a record energy of 132 MeV, nearly half the speed of light, using a moving electric field t...
Research in SLAS Technology Vol. 40 explores smartphone glucose sensing and RNA-based therapeutics in Crohn's disease. The publication showcases innovative technologies and scientific advancements in life sciences discovery and development.
Researchers at Chalmers University of Technology created an AI scientist capable of generating scientific hypotheses, designing experiments and interpreting results. The AI system, Eve, identified promising biological questions, recommended experiments and evaluated outcomes, and iteratively refined its understanding based on new evide...
Researchers developed an AI system, Ataraxos, that excels at Stratego, a two-player game of imperfect information, by combining efficient training algorithms with new techniques for calculated decision-making. The system defeated top human players and outperformed other models in strategic games, demonstrating its potential to help hum...
Researchers developed the Motion Style Slider framework for continuous control of motion style intensity in generated human animation. The framework achieves consistent style control and smooth transitions using only two motion samples, allowing animators to refine character performances according to their creative vision.
Researchers identified 88 sites hosting AI-generated non-consensual intimate imagery, with 5 key players facilitating the problem. The study calls on technology providers to block or suspend services of sites hosting AI-NCII and deploy preventative safeguards.
A proof-of-concept study tested three techniques for alerting users to hallucinated statements from embodied AI agents in VR systems. The findings suggest that embodied cues improve immersion, text cues offer clear interpretability, and icon cues strike a middle ground.
A new AI tool, Tessera, has been developed to map smallholder crops in Senegal with high accuracy, providing essential data for food security planning. The technology, trained on satellite images, outperformed existing methods and can be used to guide support decisions, helping vulnerable populations.
Large language models (LLMs) evaluate humans based on cooperation and social norms, with most models favoring cooperation and punishing bad behavior. The LLMs' judgements often depend on the recipient's gender and cultural background, and may be influenced by prompting interventions.
A closed-loop modeling and assessment framework for aerospace engineering managers' AI competency is proposed, capturing governance priorities and multi-attribute interdependencies. The framework, comprising five dimensions and twenty attributes, provides a traceable decision-support tool for selection, performance management, and care...
A real-world study of 8,391 patients found that autonomous AI could free up enough clinical capacity to provide over 8,500 additional face-to-face dermatology appointments across two UK hospitals over 16 months. The technology identifies patients with benign lesions, enabling safe management without specialist review.
Researchers developed a label-free platform combining microfluidic cell sorting with AI to enrich and identify rare CTCs. The integrated strategy uses inertial microfluidic enrichment and YOLOv8-based deep learning for bright-field image recognition, achieving 96.0% accuracy in distinguishing tumor cells.
A new framework, PhysMat AI, integrates physical knowledge into AI for materials discovery, enabling more interpretable and testable predictions. This approach helps move materials discovery beyond correlation-based prediction toward reasoning based on physical principles.
UVA Engineering AI researcher Chen Chen is developing trustworthy AI systems to forecast infectious disease epidemics, combining multiple data sources like reported cases, wastewater surveillance, and human travel data. Her approach aims to predict where diseases will spread and help public health officials respond effectively.
A new AI tool, ChromAgeNet, analyzes 3D chromatin organization in blood stem cells to identify age-related changes, which can inform rejuvenation strategies. The model outperforms previous methods, revealing subtle changes in nuclear architecture that can be used to detect age-associated states.
Researchers found that AI chatbots give users a uniform range of information, similar to a conventional web search, but with a narrower scope. The study's authors warn of 'knowledge collapse' as language models become increasingly trained on AI-generated text, potentially reducing diversity and nuance.
Researchers at MIT have found a way to stabilize lipid nanoparticles used to deliver RNA vaccines, making them more heat-resistant. This breakthrough could allow for wider distribution and enable novel administration methods like microneedle patches.
Researchers developed a self-powered, flexible neuromorphic sensing platform that mimics human tactile perception, demonstrating hierarchical memory processes and spike-rate-dependent plasticity. The device operates entirely without an external power source, converting mechanical stimuli into electrical signals.
Researchers have developed a technology that stacks semiconductor devices with different response speeds to process fast and slow signal changes together. The technology could be applied to small devices that analyze movement and physiological signals, enabling the recognition of changes in motion over time.
Researchers developed a method called Concentration-Dependent Yield Analysis (CYAN) to connect reaction optimization and kinetic analysis. CYAN extracts kinetic information from yield data, estimating reaction speeds without requiring separate experiments. This approach helps chemists design complex high-yield reactions.
A new study evaluated the ethical properties of large language models (LLMs) in generating advice for urban design and health, finding that they avoid harm but lack consistency on community participation and human oversight. The study suggests that LLMs could serve as an initial input for urban designers, but should not replace profess...
A new study by Ateneo researchers explores the cost-effectiveness of AI-assisted chest radiograph interpretation in isolated and disadvantaged Filipino communities. The study finds that AI-assisted interpretation is estimated to be more cost-effective than manual interpretation, with a potential annual cost savings of Php 877,330. The ...
Researchers at NUS CDE have developed a reconfigurable transistor that can switch between filtering image data and performing AI network functions, reducing energy consumption and improving accuracy in handwritten-digit recognition simulations. The device uses a spiking neural network-in-logic architecture to selectively pass relevant ...
A recent study from Georgetown University and the University of Washington suggests AI-generated summaries can manipulate people's memory, even when accuracy is assured. Participants who read misleading AI summaries were significantly less likely to accurately recall the original event, according to the study.
Researchers developed an AI approach to predict glioblastoma recurrence, allowing for targeted treatments before the cancer becomes visible on MRI. The tool uses microscopic images of fresh, unprocessed tissue and scored based on tumor infiltration, with an accuracy of predicting recurrence within 5-10 millimeters of the sampled tissue.
A new AI tool predicts organ failure in acute pancreatitis with high accuracy, using multiphase CT imaging and outperforming standard scoring systems. The model achieves early automated prediction, with 55% of cases predicted at least 3 hours in advance.
The AI model achieves higher specificity while preserving sensitivity in breast cancer risk classification, reducing false-positive classifications and supporting its potential use as an adjunctive tool for refining positive imaging findings.
Researchers developed an innovative approach to identify insect sex pheromones by analyzing olfactory receptors, which can help control pest populations and improve crop protection.
Mizzou researchers have developed an AI tool called MeLSI that can identify specific microbes driving key biological changes in the gut microbiome, which may indicate early warning signs of disease. The tool has shown promising results in detecting meaningful patterns in microbiome data that conventional methods miss.
The 13th Heidelberg Laureate Forum discussed AI's impact on mathematics, with mathematicians debating its benefits and drawbacks. The forum also covered topics such as quantum threats, trustworthy computation, and the role of mathematics in society.
Researchers at the Stowers Institute used AlphaFold2 and evolutionary data to predict protein structures in aphids, which were previously inaccessible to AI. The study reveals a common architectural plan among 2,400 BICYCLE proteins, showcasing the evolution's role in helping AI predict protein structures.
Researchers developed a machine learning-based method to identify chemical compounds that can safely repel honey bees from pesticide-treated crops. The model identified 130 compounds with strong potential as bee repellents, which were tested in lab and field experiments, confirming their efficacy.
Researchers developed an AI model that uses routine chest CT scans to identify patients at risk of pneumonitis, a potentially life-threatening form of lung inflammation. The model, called CIPHER, achieved high predictive power and maintained strong performance despite differences in patient populations and imaging protocols.
The 2026 World Medical Innovation Forum brought together 250+ leaders to discuss emerging treatments, AI, and scientific breakthroughs. Mass General Brigham's Chief Innovation Officer highlighted the forum's goal of accelerating innovation to improve patient care.
A new framework IDEAI organizes embodied AI around explicit intent, combining perception, knowledge, planning, action and values. It provides a structured commitment that can be inspected, revised and verified, guiding action and ensuring safety.
Researchers identified shared and disease-specific molecular changes in human brain tissue, contributing to neurodegeneration, psychiatric illness, and cognitive decline. The collection establishes a foundational resource for understanding brain disorders, accelerating discovery and therapy development.
A UCF researcher and her team used AI to screen existing FDA-approved drugs for potential treatments of schwannoma tumors in children with Neurofibromatosis type 2. The research identified 10 promising candidates, with the most favorable targets stopping tumor cell growth by impacting different cellular mechanisms.
Researchers at Bar-Ilan University and Weizmann Institute successfully engineered immune cells to recognize and attack cancer and viral targets. The enhanced T cells demonstrated stronger immune responses and greater cancer-killing ability, improving survival in mice.
Researchers developed an AI framework that can represent complex three-dimensional hydraulic conductivity fields more efficiently and use monitoring data to improve predictions of PFOA movement in groundwater. The framework, VA-LSGAN, compressed complex fields into a smaller set of variables while preserving important spatial patterns.
The Goldilocks Program aims to reduce the timeline for new health technologies from 12-18 months to 90 days through continuous feedback and testing. Key findings include the potential to move critical care toward a predictive, precision-based field that identifies and corrects dangerous immune system dysregulation.
A quadruped robot, RAIBO2, completed a 42.195 km marathon without battery swap, capturing 4 hours and 19 minutes of real-world running data. The research team developed design principles for long-distance operation, focusing on system-level efficiency and reliability.
The use of AI in consular affairs is increasing, with automated systems screening passport photos and pre-sorting visa applications. However, concerns arise about human oversight, with experts warning that AI can shape what information officials see before making decisions that affect people's lives.
Researchers from the University of East London have developed a new method to predict how different chemicals behave, which could help identify the most promising battery materials. The method, published in the Journal of the American Chemical Society, uses X-ray photoelectron spectroscopy and computer modeling to predict the behavior ...
The proposed framework integrates knowledge graphs and large language models to diagnose space TWTAs, achieving high adoption rates and robust stability, with a 94.56% adoption rate and 95% accuracy in real-scenario testing.
The Research Highlighter-MatchMaker Project streamlines research collaboration and funding discovery using AI and natural language processing. It offers a searchable portal and automated email recommendations to facilitate connections between researchers and funding opportunities.
Brodsky is exploring the translation potential of Microgrid Optima, a platform to optimize energy storage operations and minimize peak power demand. The project aims to address the rising energy demand by 2030, partly due to growing AI computational requirements.
Researchers identify brain circuit that supports flexible behavior, but is hijacked by cocaine to drive repetitive actions. Activating or suppressing opposing neural pathways can either promote rigid behavior or interrupt cocaine-driven repetitive behavior.