Traditional approaches to studying information diffusion have largely modeled communication as a sequence of bilateral exchanges—one-to-one interactions that mirror phone calls or direct messages. However, this framework neglects the richer, more intricate dynamics present when information is exchanged within groups. Aktas’s research confronts this limitation head-on by utilizing advanced mathematical techniques to more accurately capture how messages propagate and morph within social networks where multiple individuals are simultaneously engaged in discourse.

Central to this innovative methodology is the application of the sheaf Laplacian, a sophisticated mathematical construct derived from sheaf theory and spectral graph theory. Unlike conventional Laplacians, which deal primarily with pairwise relationships, the sheaf Laplacian accommodates complex higher-order interactions, allowing the representation of group discussions as cohesive entities rather than disjointed conversations. This approach provides a refined lens through which the influence of collective contexts on information transmission can be systematically analyzed.

The deployment of the sheaf Laplacian facilitates the detection of subtle variations in the nature of messages as they traverse networks. By differentiating between supportive, misleading, and contradictory communications, Aktas’s model sheds light on the mechanisms that drive polarization and leadership emergence within communities. These insights are especially timely given the proliferation of misinformation and the critical need to understand how false narratives gain traction or how echo chambers form in digital platforms.

Aktas emphasizes that understanding communication at the group level grants researchers a more realistic representation of social interactions, whether occurring online or in physical settings such as classrooms or health care teams. For instance, group discussions in educational environments often involve complex exchanges of ideas that shape learning outcomes collaboratively. Similarly, communication within medical teams has critical implications for patient care and clinical decision-making. This research thus has the potential to extend its impact well beyond theoretical realms into practical applications across various sectors.

Collaboration underpins the success of this interdisciplinary project. With NSF funding, Aktas has joined forces with colleagues from Georgia State University and Georgia Gwinnett College to integrate expertise from artificial intelligence, theoretical mathematics, and data science. Georgia State University contributes advances in AI that augment the interpretive power of models, while Georgia Gwinnett College undergirds the theoretical framework that supports the sheaf Laplacian’s unique capabilities. Kennesaw State University drives the applied data science dimension, focusing on harnessing these mathematical insights to extract actionable knowledge from real-world data.

This collective effort not only advances computational techniques but also aims to deliver vital tools for stakeholders across domains. For businesses, the refined understanding of influence dynamics could inform strategic partnerships with key opinion leaders during product launches, enhancing marketing efficacy. Healthcare providers might improve patient-provider matching by analyzing communication networks within medical teams to optimize care pathways. Furthermore, policymakers and community leaders could employ these models to map and mitigate the pernicious spread of misinformation, fostering more informed and resilient societies.

From an academic perspective, the project exemplifies a fusion of rigorous mathematical theory with tangible societal benefits. The research resonates deeply within the College of Computing and Software Engineering at Kennesaw State University, representing its mission to generate impactful, interdisciplinary knowledge. Yiming Ji, the interim dean, highlights that Aktas’s work demonstrates how blending abstract theory with pragmatic application can yield innovations that not only push scientific boundaries but also serve practical decision-making in business, health care, and civic engagement.

Future prospects for the research are robust, bolstered by a startup grant that enables the recruitment of graduate and undergraduate researchers. The imminent opening of an Interdisciplinary STEM Building at Kennesaw State University promises to catalyze further interdisciplinary collaborations, enhancing the depth and scope of investigations into information diffusion and social network dynamics.

As Aktas notes, the data science milieu at KSU is vibrant and collaborative, fostering an environment where novel questions about network behavior can be posed and answered. This project is poised to cultivate a new generation of scholars equipped to untangle the complex web of human communication in an age dominated by rapid and multifaceted information exchange.

By reconceptualizing the spread of ideas as fundamentally group-driven and by leveraging cutting-edge mathematical tools like the sheaf Laplacian, Mehmet Aktas and his collaborators are pioneering a transformative research agenda. Their findings promise to illuminate the underlying structures that govern influence, polarization, and information reliability, ultimately contributing to a deeper understanding of how communities coalesce, communicate, and evolve in the digital age.

Subject of Research: Information diffusion in social networks using advanced mathematical modeling (sheaf Laplacian) to analyze group interactions and communication dynamics.

Article Title: (Not provided)

News Publication Date: (Not provided)

Web References:

• Kennesaw State University Data Science and Analytics: https://www.kennesaw.edu/ccse/academics/data-science-analytics/index.php
• KSU College of Computing and Software Engineering: https://www.kennesaw.edu/ccse/
• KSU Interdisciplinary STEM Building News: https://www.kennesaw.edu/news/stories/2024/ksu-breaks-ground-interdisciplinary-stem-building.php

Image Credits: Matt Yung / Kennesaw State University

Keywords: Group behavior, Human social behavior, Behavioral psychology, Information diffusion, Social networks, Data science, Sheaf Laplacian, Polarization, Misinformation

Integrating AI into personal devices is more than a mere upgrade; it represents a pivotal moment in technology. Current AI systems predominantly operate on robust, expensive servers, often requiring a stable internet connection, which limits their accessibility and usability. Deng proposes a revolutionary approach, allowing AI algorithms to function offline on devices such as smartphones, drones, and even industrial sensors. By doing so, he envisions a future where advanced technology is not just reserved for large corporations or research institutions but can be harnessed by anyone, anywhere.

The core concept of Deng’s research revolves around a technique known as activation sparsity. This ingenious method exploits the fact that in any given AI model, only a fraction of neurons are actively engaged during computation. Instead of overwhelming devices with demands for all data to be loaded simultaneously, this approach allows the system to anticipate which data points will likely be required and pre-load only those necessary components. This not only conserves memory resources but also accelerates processing speeds while significantly lowering energy consumption—an essential factor in prolonging the lifecycle of portable devices.

In essence, the current methodology employed to reduce the size and complexity of AI models typically involves either diminishing the precision of data or eliminating less significant parameters. However, the innovative activation sparsity technique proposed by Deng diverges from these traditional methods. By predicting which values will activate during the course of a model’s operation, he can combine this strategy with existing methods like pruning and quantization. This multi-faceted approach ultimately leads to an unprecedented level of efficiency in AI systems that could redefine how developers conceptualize and deploy their software solutions.

Deng’s research team is engaging in empirical studies to test tiny machine-learning models as predictive support for larger systems. This interplay between small-scale predictive models and more extensive systems may bridge gaps that previously existed between advanced AI applications and user-friendly technologies. The implications of this work stretch beyond the technical realm; they highlight a shift towards embedding AI capabilities into the very devices we use daily, thus streamlining processes and enhancing user experience.

A major aspect of Deng’s initiative includes the development of an open-source simulator, which is designed to allow students and fellow researchers to interact with and refine this pioneering technology. By fostering an environment of collaboration and shared learning, the simulator could accelerate innovation in the field of AI, providing a robust platform for testing and iteration that goes beyond the walls of Kennesaw State University.

The significance of this NSF-funded project cannot be overstated, as it is positioned to impact educational programs, particularly at Kennesaw State, which recently launched a Master of Science in Artificial Intelligence program. The potential applications of Deng’s research extend beyond academia into numerous industries, with prospects ranging from monitoring factory robotics to addressing predictive maintenance in various sectors. This fusion of academic inquiry and practical application stands to enhance the way industries operate, making smarter and more effective use of AI strategies.

Within the supportive ecosystem at Kennesaw State, Deng has noted the substantial assistance he has received, which has been conducive to his research and its administrative aspects. The university has provided him the necessary resources and a conducive environment to pursue such ambitious projects. This collaboration highlights the crucial role that educational institutions play in nurturing groundbreaking research and fostering innovation that advances technology.

As AI technology continues to evolve, forward-thinking researchers like Deng are crucial in steering its development towards responsible and beneficial uses. By focusing on accessibility and efficiency, his work promises to remove barriers to AI engagement and make advanced computational tools available to a broader audience. Institutions such as Kennesaw State are paving the way for a new generation of innovations that can bridge the gap between high-tech and everyday uses.

The overarching vision espoused by Deng and his team underscores a key aspect of future technological development: that the most powerful tools should not only be in the hands of the few but should empower individuals and small enterprises. This vision aligns with Kennesaw State’s mission to prepare students for an increasingly technology-driven future while simultaneously addressing real-world challenges in diverse domains.

As we stand on the brink of a new age of technology, where artificial intelligence becomes an integral part of our daily lives, the work being done by Kennesaw State University’s Bobin Deng exemplifies the innovative spirit and forward-thinking mindset that will drive this evolution. By making AI more accessible and efficient, we can anticipate a world where the possibilities of technology are continually expanded, fueling significant advancements across all sectors of society.

Through research initiatives like Deng’s, the landscape of artificial intelligence is not just being explored; it is being redefined. As these advancements unfold, they promise to enhance the global understanding of AI, fostering greater acceptance and use in a multitude of contexts, ultimately leading towards a more connected and intelligent world.

The convergence of advanced AI techniques with personal and industrial devices could soon mark a transformative chapter in technology, fostering a scenario where cutting-edge capabilities are available to everyone and facilitating a future filled with potential innovations and breakthroughs that benefit society at large. Such work underlines the importance of continuing investment in scientific research and education, essential components for nurturing the next generation of leaders in technology and engineering.

Subject of Research: Accessibility of Artificial Intelligence through Activation Sparsity.
Article Title: Revolutionizing AI: Making Artificial Intelligence Accessible Beyond the Cloud.
News Publication Date: October 2023.
Web References: Kennesaw State University, NSF.
References: National Science Foundation Grant Documents.
Image Credits: Darnell Wilburn / Kennesaw State University.

Keywords

Artificial Intelligence, Activation Sparsity, Kennesaw State University, National Science Foundation, Sustainable Smart Systems, Machine Learning.

Current food safety routines typically rely on sensory cues—mainly the visual assessment of food items or olfactory detection through smell. However, these methods fall short when it comes to the invisible pathogens responsible for foodborne illnesses, such as salmonella and E. coli. These pathogens can lurk in food products, rendering them hazardous for human consumption without any outward signs that traditional senses can detect. As a response to this critical concern, Choi’s e-nose employs cutting-edge technology to analyze volatile organic compounds (VOCs) emitted by food, which may signal the presence of harmful bacteria.

The e-nose harnesses the capabilities of artificial intelligence and machine learning to identify and quantify these chemical signals. By training AI algorithms on extensive datasets consisting of various VOC samples, researchers can create a robust model capable of differentiation between contaminants and safe food, thus significantly enhancing the chances to avert foodborne illnesses before they reach the consumer’s plate. Choi’s innovation may ultimately change how we approach food safety, steering us toward a future where food testing is not only faster but also non-destructive.

Foodborne illnesses represent a pressing public health issue, with the Centers for Disease Control and Prevention (CDC) estimating that there are approximately 128,000 hospitalizations and around 3,000 deaths each year in the United States alone. This grim statistic emphasizes the critical need for rapid and accurate diagnostic tools that can assure the safety of the food supply. Moreover, Choi’s work aims to benefit not only food sanitation but also has implications that could extend into other fields, such as healthcare and security.

Choi is particularly focused on pathogens like salmonella and E. coli due to their prevalence and potential for causing widespread illness. The evolution of the e-nose will enable it, over time, to identify a broader spectrum of pathogens, potentially creating an all-in-one diagnostic tool for food safety. This multi-faceted function of the e-nose can redefine how industries that deal with food production and retail conduct their quality assurance processes.

Rapidly evaluating food safety without destructively sampling the product could also mean significant savings for manufacturers and retailers. By adopting e-nose technology, companies could mitigate food waste, which is increasingly becoming a focal point in efforts to promote sustainability. The economic benefits of such innovation resonate well beyond mere waste reduction; they could translate into lower costs for consumers, a crucial aspect in today’s economy deeply impacted by inflation and food prices.

Choi’s ongoing work on the e-nose has received funding from the U.S. National Science Foundation, highlighting the project’s potential national impact and recognition within scientific communities. The NSF’s support underlines the importance of innovation in food technology as a response to both health and environmental crises.

The underlying technology of the e-nose benefits from interdisciplinary collaboration, involving expertise from fields such as AI, environmental science, food technology, and public health. This multifaceted approach can yield a more holistic understanding of food safety issues, which are often complex and influenced by various factors—ranging from agricultural practices to distribution logistics.

Choi’s vision for the e-nose does not end with food safety. The technology has the potential to be adapted for healthcare applications, where it can analyze breath samples to detect a multitude of diseases. This capability could pave the way toward non-invasive diagnostic techniques that revolutionize how healthcare providers monitor and treat patients. Imagine a future where your doctor has a simple device that can assess your health within moments, detecting chronic illnesses or diseases just from a breath.

Furthermore, the security sector could benefit from similar VOC-sensing technologies, enabling rapid threat detection in various contexts, such as identifying hazardous substances or detecting explosives. In a world where safety is paramount, such advancements would represent significant strides in enhancing public safety measures across multiple domains.

As artificial intelligence continues to evolve and integrate into everyday life, its incorporation into food safety technologies not only showcases the possibilities of modern science but also reinforces the role of research in addressing pressing societal concerns. With the ongoing support from academic institutions and research organizations, pioneering projects like Choi’s e-nose are set to lead the frontline in ensuring a safer, healthier future for consumers everywhere.

The impactful research led by Taeyeong Choi resonates on multiple levels—addressing urgent public health concerns, contributing to economic sustainability, and paving the way for groundbreaking technological advancements. The e-nose project is a testament to the power of innovation in shaping not just scientific practices but daily lives, ensuring that the simplest human necessity – food – remains safe and accessible for all.

Subject of Research: Development of an electronic nose (e-nose) for detecting foodborne pathogens
Article Title: Kennesaw State University Innovates Food Safety with Electronic Nose Technology
News Publication Date: October 2023
Web References: Kennesaw State University
References: Centers for Disease Control and Prevention
Image Credits: Credit: Kennesaw State University

Keywords

Food safety, electronic nose, artificial intelligence, foodborne illnesses, volatile organic compounds, pathogens detection, machine learning, sustainable food practices, public health.

Zhao’s research centers on developing innovative technology that evaluates Fractional Flow Reserve (FFR), a crucial measurement in diagnosing coronary artery disease (CAD). CAD stands as the leading cause of mortality in the United States, with the Centers for Disease Control and Prevention reporting between 375,000 to 400,000 deaths annually due to this condition. The statistics underline an urgent need for improved diagnostic methods, which is precisely the gap Zhao aims to bridge through his work.

Historically, traditional FFR measurement techniques involve invasive procedures that can be both time-intensive and costly. They often depend on computational fluid dynamics methods that may take hours to yield results. Zhao’s innovative approach intends to create a non-invasive method for evaluating FFR that dramatically shortens the evaluation time to mere seconds. This breakthrough could not only enhance the speed of diagnoses but also lessen the associated risks for patients undergoing cardiovascular evaluations.

The technology being developed by Zhao capitalizes on coronary computed tomography angiography (CCTA) scans to assess FFR. Traditional techniques involve threading a wire into the arteries to analyze pressure differentials and thereby diagnose blockages, a method fraught with risks and discomfort for the patient. By shifting to a non-invasive technique, Zhao is redefining how diagnoses can be performed, aiming ultimately for an approach that maximizes patient comfort while optimizing accuracy.

Zhao articulated the transformative potential of his research, stating that it is not merely an improvement to an existing diagnostic method but an overhaul of the entire cardiovascular diagnostic workflow. Real-time results, he suggests, could empower healthcare providers to make quicker, more informed decisions regarding patient care. This immediacy could be life-saving, emphasizing the real-world implications of his research efforts.

The accolades for Zhao’s work extend beyond its technical prowess, with Sumanth Yenduri, the Dean of the College of Computing and Software Engineering at Kennesaw State University, commending his contributions. Yenduri emphasized that Zhao’s research exemplifies the transformative capacity of interdisciplinary work, effectively merging the realms of computer science with healthcare in a way that highlights significant societal impacts.

Zhao’s fascination with cardiovascular research initiated during his doctoral studies, during which he first engaged with advanced cardiovascular imaging techniques. This early exposure ignited a desire to harness computer science in the realm of medical imaging, with the ultimate aim of refining and improving diagnostic processes. The idea to utilize CCTA for FFR prediction stemmed from a commitment to eliminating the risks associated with invasive methodologies.

The conventional approach to FFR prediction, despite its widespread use, involves significant complications. CCTA scans capture images of the coronary arteries but calculating FFR from these images using traditional computational flow dynamics methods requires extensive time and resources. Zhao recognized the potential for leveraging deep learning combined with physics-informed neural networks to revolutionize this tedious process, aiming to produce both accuracy and efficiency.

In addition to addressing current diagnostic challenges, Zhao’s vision encompasses a broader horizon. He hopes to explore the untapped potential of artificial intelligence within the realm of medical diagnostics. By refining the technologies at his disposal, he aims not only to enhance the process of diagnosing heart disease but also to potentially expand his methodologies to other medical fields.

The ultimate goal of Zhao’s research is the improvement of patient outcomes and quality of life on a global scale. He envisions a future where breakthroughs in medical imaging are commonplace, offering unprecedented advancements in diagnostics that could alter the landscape of patient care. This ambition drives his ongoing research, propelling him forward into uncharted territories of medical and technological innovation.

Zhao’s journey highlights the importance of interdisciplinary collaboration in driving meaningful advancements in health care solutions. As the fields of computer science and healthcare continue to converge, the implications of such research could pave new pathways to understanding and treating a multitude of conditions that afflict populations worldwide.

As technology continues to evolve, Zhao’s work stands at the forefront of transformative medical research. Not only is he developing methodologies and technologies that could redefine patient diagnostics, but he is also contributing to a broader narrative about the convergence of technology and medicine, hoping to inspire the next generation of researchers to explore these vital intersections.

The future of cardiovascular diagnostics may very well hinge on innovations like those being introduced by Chen Zhao. As he continues to push the boundaries of what is achievable in medical imaging, the potential benefits for countless patients around the world remain at the core of his objectives, driving his research forward with both rigor and compassion.

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Subject of Research: Non-invasive blood flow prediction in cardiovascular disease diagnostics
Article Title: Kennesaw State University’s Chen Zhao Receives 2025 AHA Award for Groundbreaking Cardiovascular Research
News Publication Date: October 2023
Web References: N/A
References: N/A
Image Credits: Darnell Wilburn / Kennesaw State University

Keywords: Cardiovascular disease, Coronary artery disease, Blood flow, Medical imaging, AI in healthcare, Research enhancement, Non-invasive diagnosis, Health technology.

At the core of Sucosky’s project is an inventive concept titled “A Novel Microphysiological Valve-on-Chip for Elucidating the Mechano-Etiology of Bicuspid Aortic Valve Disease.” This ambitious initiative aims to construct an advanced device that replicates the anatomical and functional characteristics of the bicuspid aortic valve, providing insights into how abnormal mechanical stresses contribute to the premature degradation of this crucial heart structure. As research in this area continues, Sucosky’s team endeavors to reveal the intricate biological dynamics that trigger the early onset of valvular disease, which often leads to serious health ramifications.

The device under development by Sucosky’s team in the Multi-Scale Cardiovascular Bioengineering Laboratory (MSCBL) creates a sophisticated in-vitro platform capable of mimicking the environmental conditions faced by both normal and diseased aortic valves. By simulating the unique biomechanical forces encountered by the bicuspid aortic valve, this research aims to elucidate the biological mechanisms responsible for premature calcification. Such advancements could play a pivotal role in identifying potential treatment options and therapeutic strategies to mitigate the disease’s progression.

Bicuspid aortic valve disease presents a significant challenge in cardiovascular health. Unlike typical heart valves that undergo calcification around the age of 65, individuals born with a bicuspid aortic valve experience calcification much earlier, often in their 30s. The abnormal structure leads to undue strain on the heart and increased risk of complications, frequently necessitating surgical intervention. This rampant early calcification not only accelerates disease progression but also complicates treatment options, as replacement valves generally exhibit limited lifetimes, prompting the need for multiple surgical procedures over a patient’s lifetime.

Professor Sucosky emphasizes the profound impact this condition inflicts on patients, particularly concerning their quality of life and the necessity for repeat procedures at a young age. He seeks to unravel the underlying processes that contribute to this hastened calcification to devise innovative strategies aimed at delaying or entirely halting the disease’s progression, with the ultimate goal of improving patient outcomes and reducing surgical burdens.

The research spearheaded by Sucosky has attracted considerable attention from both the AHA and his academic peers at Kennesaw State University. Dean Lawrence Whitman of the Southern Polytechnic College of Engineering and Engineering Technology has praised Sucosky’s initiatives as exemplary within the domain of intersectional research. His work promises to push the frontiers of cardiovascular engineering while simultaneously addressing vital societal healthcare challenges.

Central to Sucosky’s research is the hypothesis that the aberrant morphology of the bicuspid valve induces irregular blood flow patterns, thus exerting abnormal mechanical stresses on the valve tissue. These non-physiological forces are hypothesized to be a substantial factor in the aggressive calcification typically associated with this valvular condition. To rigorously test this hypothesis, Sucosky’s laboratory is advancing a groundbreaking valve-on-chip technology capable of replicating the mechanical dynamics present within the cardiovascular system.

Through this innovative device, researchers can delve deeper into the mechanobiological relationships impacting valve tissue health. Sucosky is hopeful that his investigations will not only enhance the understanding of bicuspid aortic valve calcification but also extend insights into other broader cardiovascular diseases, ultimately laying the groundwork for future pharmaceutical interventions aimed at repositioning how we approach heart valve disorders.

Sucosky believes that tackling this critical area of research could lead to the development of drug-based therapies targeting the calcification process, thereby sparing patients the need for multiple invasive surgeries. By conceptualizing and actualizing these non-surgical alternatives, there is potential not just for innovation in treatment paradigms but also for a significant reduction in healthcare costs and patient morbidity associated with repeated surgical interventions.

The approximately $200,000 funding granted by the AHA over two years enables Sucosky and his MSCBL team to further their heart research significantly. This endeavor is not carried out in isolation; it involves a collaborative environment that includes undergraduate students actively participating in the design and simulation stages of the device. Additionally, the project benefits from the expertise of external collaborators, including Dr. Kartik Balachandran from the University of Arkansas, whose foundational work has informed the current research pathway.

Collaborative efforts are deemed essential by Sucosky, who recognizes that comprehending the mechanical forces at play requires an integrated approach engaging engineers, biologists, and clinicians alike. The insights garnered from this interdisciplinary collaboration are expected to inform both the creation of medical treatments and the refinement of surgical approaches tailored to the unique requirements posed by patients with bicuspid aortic valve disease.

With an eye towards expanding the implications of his research, Sucosky plans to turn his focus towards additional cardiovascular conditions that might also be influenced by aberrant hemodynamics, such as aneurysms and atherosclerosis. By developing a versatile research tool capable of exploring various cardiovascular disorders, he aims to illuminate mechanisms underlying these conditions while simultaneously exploring novel treatment options.

In closing, Sucosky acknowledges that while the current project represents a long-term research pursuit, the potential impact on the medical community and patient care is immense. His innovative exploration into the mechanobiology of heart valve disease has the capacity not only to reshape our understanding of valvular conditions but could also result in a paradigm shift in how we approach a host of other cardiovascular diseases driven by mechanical forces.

His ongoing research efforts are a testament to the nexus between engineering and healthcare, highlighting a future where insights from biomechanics can lead to significant advancements in cardiovascular medicine.

Subject of Research: Bicuspid Aortic Valve Disease
Article Title: Innovative Valve-on-Chip Research Aimed at Unraveling Bicuspid Aortic Valve Disease
News Publication Date: [To be added]
Web References: [To be added]
References: [To be added]
Image Credits: Credit: Kennesaw State University

Keywords: Cardiovascular disease, Clinical research, Mechanical engineering, Surgery, Molecular structure, Circulatory system, Heart