Hough, Alexander - 937-255-9492

Misinformation and influence operations are a prolific threat due to advances in technology and social media platforms. There have been numerous successful influence operations perpetrated by our adversaries and many have been documented. There is ongoing research with detection of and spread of misinformation akin to a contagion, however, there are significant gaps in our scientific understanding of how these phenomena affect human cognition and behavior. Foundational research is needed to understand cognitive processes and mechanisms of decision-making to predict, explain, and simulate human behavior in this cognitive warfare space. We need to understand how, when, and why cognitive vulnerabilities/biases could be exploited using misinformation to degrade decision-making. This includes developing experiments and cognitive models to explore the: 1) interaction between cognitive, social and emotional factors, 2) qualities of misinformation that increase/decrease impact, 3) the extent that individual and cultural differences affect misinformation effects, 4) mitigations that are most likely to work in various contexts, and 5) how individuals spread misinformation in groups and subsequently social networks.

Haggit, Jordan - 614-316-8505

This research requires US citizenship. This research will focus on supporting cognitive warfare through state-of-the-art science and human-machine teaming to help intelligence leaders achieve a strategic decision-making advantage in highly dynamic, complex, and uncertain environments. This work should build upon the wealth of findings from highly relevant scientific domains such as behavioral game theory, systems thinking, complexity science, geo-political forecasting, hybrid (i.e., human-machine) collective intelligence, coordinated action, trust, and influence. For example, cognitive hierarchy theory could be leveraged to characterize the strategic sophistication of individuals, units, and organizations in realistic warfare scenarios. Research-based tools and machine learning models could be developed to assist analysts in estimating the level of their counterparts’ strategic sophistication from records of their past actions. These estimates could be used by combatant entities to set their own level of strategic sophistication to exploit the counterpart’s weaknesses (e.g., by choosing one level above the counterpart’s level) or to mislead the counterpart (e.g., by choosing a much lower level). At a system-of-systems level, the research could attempt to understand the complex dynamics of the adversarial and cooperative relationships between the counterparts to identify system archetypes, tipping, and leverage points, which can be useful in maintaining or attaining desirable equilibria.

Dooley, Christopher - 513-703-5761

Biosignals, or data that can be extracted from the body, can be used to monitor the physiological response to operational aerospace stressors such as sustained Gz, reduced pressure, and high noise. Data derived from these signals can be used to monitor and predict adverse physiological and psychological states, providing advanced warning for improved safety and performance during operations. Wearable sensors enable the measurement of biosignals outside of the laboratory environments, but they can be cumbersome/obtrusive, susceptible to motion artifacts, and unable to accommodate a wide range of individual differences in physiology. Each of these factors impacts both the performance of wearable sensor systems in the operational environment, and the performance of models designed to classify operator state based on these measurements. Thus, it remains unknown how to successfully design, develop, and evaluate wearable sensors for operational environments as well as extract and utilize biosensor features to enhance mission effectiveness. Work in this area should focus on both the examination of individual biosignals and their contribution to operator state estimation, and the design of innovative hardware to support successful unobtrusive and accurate measurement in the operational environment.

Haggit, Jordan - 614-316-8505

This research requires US citizenship. This research will focus on supporting operator sensemaking and decision making during dynamic replanning activities in highly complex and uncertain environments. Operators in the USAF are increasingly leveraging AI/ML technologies to gather, monitor, and forecast resource needs. This places new demands on individual and team sensemaking that are not well understood. For example, as more information exists within the joint cognitive system it will be critical to carefully design human-readable display outputs that support planner decision making, facilitate team situation awareness, and reduce coordination costs associated with establishing common ground, communication, etc. This project will focus on how data and information visualization can be leveraged to support the replanning process. Example projects may include investigating the cognitive requirements and information visualization needs related to course of action generation and management, determining the right balance between plan specificity and flexibility for ongoing planning, or how AI/ML visualization outputs impact coordination between individuals in an operational team.

Tilly, Trevor - 937-713-5386

Interstitial fluid (ISF) has great promise as a biofluid for minimally invasive wearable sensor deployment. Although other methods exist to access ISF from the skin, microneedles (MNs) have emerged as a leading option to enable human performance biomarker sensing in ISF. There are many materials and variations of MNs used in different applications, however, MNs that are designed for real-time sensing or to interface with sensor modalities for near real-time or post analysis of biomarkers are desired. Alternative methods for biofluid access other than MNs are also of interest. This research aims to: 1) understand the optimal characteristics of device/skin interface for sensing in ISF; 2) explore signal transduction methods (electrochemical, optical, and others for enabling rapid biomarker quantification; 3) design and fabricate sensor devices for human performance biomarkers for multi-hour/day use, and to 4) develop algorithms to predict human performance and stress and fatigue based on biochemical signals obtained directly from Airmen/Guardians.

Chavez Benavides, Jorge - 937-938-3786

Cognitive overload, fatigue and stress affect Airman and Guardians (A/G) in the different environments they operate. These stressors activate different mechanisms that affect brain function and result in compromised performance. Technologies that can sense brain activity and respond to the effects of these stressors would provide an effective means to prevent performance decay and maintain alertness/readiness. This topic is focused on the use of nanomaterials made of soft components (nucleic acids, peptides, etc.) or metals (gold, iron oxide, etc.) or the combination of both to be interfaced with neurons and control their function. Specific challenges to be addressed are: methods to safely deliver the nanomaterials to the brain, control over spatial resolution of the stimulation and the use of non-invasive methods to activate the nanoparticles. The end goal of this topic is to provide a non-invasive means to activate/deactivate or enhance brain function as needed in a closed-loop system.

Myers, Chris - 937-938-4044

Most computational theories of cognition lack a representation of physiology. Understanding the cognitive effects of compounds present in the environment is important for explaining and predicting changes in cognition and behavior given exposure to toxins, pharmaceuticals, or the deprivation of critical compounds like oxygen. This goal of this research is to integrate physiologically-based pharmacokinetic model predictions with computational cognitive models to help predict and explain changes in cognitive performance from exposure.

Kim, Steve - 937-938-3713

Data-driven chemical and biochemical monitoring systems based on real-time biological and environmental probing are the future of human performance monitoring, as well as occupational safety and medicine. In combination with a better understanding of physiology, these advances should lead directly to improved safety and preparedness of the war-fighter. Molecular biomarkers indicative of human physiological and psychological status vary person-to-person and the measurement point of the time. Thus, developing highly sensitive, selective, robust, cost-effective, and miniaturized chemical and biochemical sensors that profile/report biomarkers throughout 8-24hr time frame of individual operators will greatly benefit USAF personnel health and performance. In this research, we aim to 1) probe the governing factors in the molecular affinity of molecular targets to the biomimetic recognition elements at operation-relevant setting, 2) build array based on highly selective sensing elements, 3) design, fabricate, and miniaturize electronic/electrochemical/optical sensors. The sample collection, delivery, signal processing, and device-to-device communication for the miniaturized sensors and devices are being explored as well to ultimately achieve high performance molecular signature sensors that transition to flexible, wearable, and/or body-conformal chemical/biochemical monitors.

Kim, Steve - (937) 938-3713

The ultimate goal of performance monitoring is to build sensors capable of continuous, real-time analysis of biomarkers for targets indicating stress, fatigue, vigilance, and overall other physiological conditions. Biomarkers found in biofluids can be extremely indicative of physiological state. Traditionally, these biomarkers are assessed with labor intensive biofluid (blood, saliva, urine) sampling and analysis with complex equipment and assays (HPLC, ELISA etc.). To make biomarker tracking a feasible monitoring system, sensor platforms must be developed for rapid to real time analysis. These can be in handheld form factors such as a lateral flow assays or in a wearable form factor such as a transdermal patch.
The objectives of this research are to develop sensor platforms that are amenable to either rapid or real-time analysis of biofluids. Of particular interest are blood and sweat. Sensor platforms should have a small/portable form factor for handheld assays or flexible/wireless capability for wearable form factors. Platforms should be capable of detecting a wide range of molecule types from small <300 Dalton to proteins >3000 Dalton. Additional interest lies in pre-processing of biofluids to increase sensitivity/selectivity of the sensor platform.

McGee, Stephen - 602-418-9513

The U.S. Air Force is investing heavily in commercial-off-the-shelf and specialty developed medium- and high-fidelity contexts for readiness training and rehearsal. The focus is to create and or leverage methods and technologies to securely blend real world and synthetic environments for learning and performance in operational test and training contexts. The environments allow local and distributed, at-distance connection of virtual simulators, computer-generated human-performance models, gaming environments, and relevant live operational systems, such as actual aircraft or other actual combat systems.
This topic focuses on critical research needs across a number of relevant topical areas: (a) Identification of essential knowledge, skills and developmental experiences required for successful task, job, and mission performance. (b) Digital tools that can assist human instructors to design content for scenarios based on "a" above and on the specific mission objectives, using principled instructional approaches. (c) Creation and validation of multi-level data, measures, and metrics to predict, diagnose, monitor and assess the performance of learners as individuals and as members of teams. These methods will assist in the prescription and tailoring of content and remediation to address knowledge and skill gaps as well as help develop new classes of human performance and machine learning-based models. (d) Novel research designs to promote longitudinal explorations and periodic assessments of individual and team performance and proficiency in synthetic environments and in operational settings. (e) Strategies and measures of the appropriateness of instructional and training environments for a given level of readiness or proficiency in training. In other words, how much of what kind of training and remediation or rehearsal is accomplished feasibly in separate and "blended" environments. We are interested in developing and validating criterion measures related to the impact of blended environments on learning, proficiency and readiness that help quantify intervals necessary for refresher training. Research can include:
• Developing training scenario design, delivery and management tools
• Developing synthetic task environments that leverage augmented and virtual-reality environments; game-based systems; intelligent and adaptive training environments; and part-task trainers and job aids that promote and sustain engagement and involvement in the learning as well as improve performance and retention
• Rapid prototyping of novel approaches to more unobtrusive human-performance monitoring, modeling, assessment and feedback
• Developing more precise as well as generalizable ways to manage multi-source "big data" performance measurement and proficiency-tracking data and innovations (i.e. how best to visualize and package feedback data for after-action reviews)
• Evaluating the training necessary for (1) humans and machines as teams to ensure to promote teaming and task/mission success, (2) shared proficiency among human-human and human-machine teams, and (3) overall task and mission performance effectiveness.

Thompson, Eric - 937-255-4381

The goal of the research project is to understand the mechanisms and principles by which effective communication and speech perception occur in acoustically-challenging environments (high-noise and/or “cocktail-party” scenarios) with potentially degraded speech signals (e.g., low bandwidth, or low bitrate), and explicitly apply the knowledge gained to develop effective, robust and intuitive interfaces for not just human-human communication, but also human-machine communication. Areas of research includes: 1) characterizing and modeling the sensory and cognitive constraints in complex acoustic environments with multi-sensory inputs, 2) characterizing and modeling the intelligibility of speech that has been passed through non-linear and lossy signal processing (e.g., low-bitrate vocoders), 3) Bi-directional listener-talker interactions and adaptations, 4) Characterizing the impacts on communication efficiency and effectiveness with decreasing speech intelligibility, 5) Developing intuitive, next-generation, and robust speech-based displays/speech output systems that will enhance speech and improve communication in operation environments not only for humans but also for human-machine communication.