Mattie, David - 937-776-4467

Mathematical modeling provides quantitative prediction of the dose- and time course- responses of mammalian systems to toxic chemicals. Simple and complex in vitro toxicological models can provide novel findings uncovering chemical-response mechanisms. This research program focuses on using a systems biology approach to address predictive toxicology. Developing methods and computational models ranging from in vitro/single cell to complex whole animal/human systems will allow for a more rapid assessment and prediction of chemical and material toxicity. Research areas support the overall advancement of human toxicokinetic and toxicodynamic modeling of exposure to single operational chemicals and materials, as well as mixtures. Approach sought will aid in development of biologically-based kinetic (BBK) models that incorporate the limiting rate factors for the absorption, distribution, and elimination of chemicals and nanomaterials in human. We seek to generate, interpret, code and integrate data for primary toxicity mechanisms starting from membrane effects and transport after exposure to those differentially modulating critical cell pathway functions prior to final elimination of the insult. Sub-objectives include: 1) developing, building and assessing in silico and in vitro models (cell lines, co- and multi-cell systems) for quantifying toxicity effects. These studies include novel approaches to computational and cell-based validation of key toxicity control mechanisms such as induction or loss of specific pathways or proteins and those incorporating broader rate limiting processes for providing quantitative evaluation of chemical safety. 2) Coding empirical toxicology data from rapidly-acquired, high-throughput and high-content in vitro toxicity studies to aid in developing rate-limiting and mechanistically-based BBK toxicity models, which aid in in vivo toxicity kinetics and response prediction for mammalian systems (an in vitro-to-in vivo extrapolation). 3) Integrating current toxicology modeling with ~omic data sets obtained from current or emerging technologies involving genomic expression through induction, activation and function of cellular proteins. 4) Developing computational approaches to couple in vitro gene expression patterns to protein induction and activation with incorporation of chemical structural activity measures and protein/pathway activity.

Estepp, Justin - 937-938-3602

A person`s physiological response to a task, event, or stimulus can contain a wealth of information about processes underlying cognition and performance. However, `sensing` the right data sources and `assessing` their response with both accuracy and precision pose a number of challenges in a diversity of fields such as engineering, computer science, neuroscience, psychophysiology, and psychology. This topic seeks to theorize, design, and develop methods by which physiological responses can be decoded to make inference about ongoing cognitive processes and how they relate to observable or desired outcomes in the physical world (e.g. task performance, motor actuation, communication). Example scientific fields include but are not limited to cognitive state assessment, brain-computer interfaces/brain-machine interfaces, and cognitive neuroscience. Topics may address any element of the process from observation of a physiological response to inference about it, including but not limited to 1) new sensors or their novel application to observing physiological response, 2) signal processing approaches to preprocessing and/or feature extraction from physiological response data, 3) pattern recognition, machine learning, or other data analytic approach for making inference on the observed physiological response, 4) robustness in realistic conditions, 5) biophysical simulation to aid in the application of signal processing and/or data analytics, and 6) novel use cases for cognitive state assessment, brain-computer interfaces, and brain-machine interfaces. Candidates would ideally be from fields of neuroscience, biomedical engineering, computer science, computer engineering, electrical engineering, statistics, or other science, technology, engineering, mathematics, or medicine (as appropriate).

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. This research aims to: 1) understand the optimal characteristics of MN/skin interface for sensing in ISF; 2) explore signal transduction methods (electrochemical, optical, and others, for enabling biomarker detection via the MNs or in ISF collected by MNs; 3) design and fabricate MN-sensor devices for human performance biomarkers for multi-hour/day use.

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.

Hussain, Saber - 937-626-0196

Airmen constantly endure an evolving spectrum of operational stress scenarios (e.g. extreme physical exertion, high temperatures, excessive G-Force, pressure changes, low oxygen environments, exposure to chemical or particle contaminants) that induce changes in the structural and functional dynamics of mitochondria. Mitochondria are always in constant flux by changing their morphology and energy production in response to the energy (ATP) needs of the cell. The dynamic nature of the mitochondria allows for rapid detection of physical or cognitive impairment by characterizing the structure and the function of the mitochondria. The incumbent will bring innovative ideas and participate in research to simulate Airmen stress scenarios using advanced cell culture models and evaluate structural and functional dynamics of mitochondria through microscopic imaging, biochemical analysis, and in silico simulations using artificial intelligence-based platforms to rapidly extrapolate Airmen performance outcomes from early stage mitochondrial changes due to operational stress responses. This will bring synergy and collaboration through this fellowship program to shape the growing AFRL core research area of system biology.

Hussain, Saber - 937-626-0196

Exposure to physical (e.g. hot/cold temperature, high altitudes) and chemical (e.g. aerosol particles, irritants) operational stress factors challenges the respiratory system by causing lung surfactant (LS) dysfunction that may lead to degraded military physical and/or cognitive performance. LS is a phospholipid-protein complex secreted by the type II alveolar epithelial cells that combines with water in the lungs to create a film at the air-liquid interface. LS serves as a protective barrier to prevent absorption of harmful particles into the bloodstream and reduce surface tension to stabilize alveoli and increase breathing efficiency. Inhalation of aerosols that interfere with LS may diminish normal function and contribute to the onset of collapsed alveoli, acute respiratory distress syndrome, tissue damage, and reduced Airmen readiness & performance. The participant will bring new innovative ideas to assess how LS and lung surfactant producing cells/tissue respond to the combined effects of simultaneously simulated stress scenarios to aid in hazard identification, exposure assessment, and risk analysis. Participants will also have the opportunity to expand, design and modify a new model of constrained drop surfactometer (CDS) to study respiratory health effects of particles & chemicals. Additionally, a predictive or in silico model applying artificial intelligence will be built as a rapid screening tool to predict respiratory health effects of diminished lung surfactant function on Airmen readiness engaged in high-demand, & high-impact mission tasks. This will bring synergy and collaboration through this fellowship program to shape the growing AFRL core research area of system biology.

Hussain, Saber - 937-626-0196

Biophotons, weak light emitted as part of chemical reactions taking place inside each cell during normal or stressed conditions, can be a form of non-molecular cellular communication. However, despite a century of research, little is known about the specific mechanisms of biophoton generation and reception as well as the information encoded in biophoton signaling. The goal of this research is to characterize intracellular biophoton emission and understand how this intracellular emission can control and modulate cellular communication. The participant will bring new innovative ideas and participate in designing experiments to understand the significance, mechanisms for photon generation and detection, and quantification of spectra, intensity, and spatial and temporal distribution. The understanding of biophotons and its molecular and quantum interactions could close the gaps in our knowledge of cell signaling (signal generation, transduction, processing) and lead to the development of non-invasive tools to to detect cell signaling to understand the mechanism of performance. As a communication mechanism that impact cellular function, biophotons can be altered to treat diseases or enhance human performance. This will bring synergy and collaboration through this fellowship program to shape the growing AFRL core research area of system biology.

Myers, Chris - 937-938-4044

Autonomous systems are a new frontier for pushing sociotechnical advancement. Such systems will eventually become pervasive, involved in everything from manufacturing, healthcare, defense, and even research itself. However, proliferation is stifled by the high development costs and the resulting inflexibility of the produced systems. As advances are made toward more rapid development of autonomous systems through interactive or written instruction, other challenges have been identified for further improving the flexibility and generalizability of systems capable of learning from instruction. Specifically, few instructions are complete and one cannot assume a system will have all the requisite knowledge to execute instructions as intended: knowledge gaps can be pervasive and a hindrance to teachable models. The goal is to research foundational aspects of knowledge gap detection, identification, and resolution processes for intelligent machines.

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.

Vidulich, Michael - 937-255-8896

To ultimately create operator sensing-and-assessing systems to guide system adaptations in Air Force operations, the systems must be robust for assessing changes in representative real-time operator cognitive states. In real-world tasks stressors such as time pressure, uncertain information and so forth will be expected to be countered by human expertise, automated assistance, interface design, and so forth. The purpose of this project is to advance the understanding and assessment of human cognitive states during such task performance. Specifically, the goals are to 1) to expand the understanding of how fundamental changes in the human, such as the development of expertise in complex task performance, influences assessment, 2) to explore new psychophysiological assessment technologies to determine their potential contributions to form a more complete picture of the human’s cognitive state, and 3) to investigate how task stressors can impact the robustness of assessments. Not only will the proposed research be very valuable as basic research to expand the understanding of crucial cognitive state assessment issues, but it will be extremely beneficial in making progress in developing assessment capabilities to guide assessment and augmentation in operational systems or to guide success in the progress of training programs.

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.

Brill, John - (937) 656-5966

The US Air Force is investing heavily into the development of autonomous systems. As such, there is considerable interested in studying human-autonomy teams. In many circumstances, it may be necessary to transfer custody/control of autonomous assets. We are interested in learning more about the information required for effective transfer of authority (TOA), including interface transparency to quickly gain situation awareness, factors that facilitate calibrated trust in systems and between operators, and ethical considerations for TOA. A visiting faculty member, if selected, will work with the Collaborative Interfaces and Teaming Branch, a large group within AFRL focused on research and technology development of facilitators for human-autonomy teaming. This opportunity is available in-person or virtually, depending upon the nature of the proposed project, its goals, and methods.

Anderson, Timothy - (937) 255-8817

The objective of this research is to develop advanced human language technologies (HLTs) such as automatic speech recognition, machine translation, named entity tagging, part-of-speech tagging, and morphological analysis for use in multilingual multimedia information extraction and retrieval applications. Of particular interest are (1) algorithms and techniques to incorporate broader context(i.e., across sentences and utterances) as opposed to (or in addition to) current techniques that generally process inputs one sentence or utterance at a time without regard to prior sentences or utterances; (2) deep neural networks, long short-term memory networks, and other advanced algorithms for HLTs; (3) active on-line learning of possible translations and/or transliterations of out-of-vocabulary words encountered in machine translation; (4) methods for segmenting multi-story videos(e.g., news broadcasts) by jointly using speech and video frame information; and (5) improved methods for processing languages with little labeled training data.

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.

Bennett, Winston - 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 better blend real world and synthetic environments for learning and performance. The environments allow local and wide-area connection of virtual simulators, computer-based human-performance models, gaming environments and relevant live operational systems, such as actual aircraft.
This research topic focuses on critical research needs across a number of relevant topical areas: (a) Identification of essential knowledge, skills and experiences required for successful task, job and mission performance and the representation of these at appropriate levels of analysis. (b) Methods and tools capable of designing 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. These methods will assist in the prescription and tailoring of content and remediation to address knowledge and skill gaps as well as help develop a new class of human performance and machine learning-based models. (d) Longitudinal explorations and periodic assessments of individual and team performance and proficiency in synthetic environments and operational settings. (e) Strategies and measures of the appropriateness of instructional and training environments for a given level of readiness or proficiency training. In other words, how much of what kind of training and remediation or rehearsal is accomplished feasibly in separate and "blended" environments, including live operational contexts? In this context, 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:
• Improving the quality and precision of needs assessment, gap and trade-space analyses
• 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) human and machine environment interaction necessary to promote teaming, (2) shared proficiency 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.