Affiliate Expert Search

Collaborative research and scale up experiences in Food Safety, Quality and Production Technologies.

The small grains breeding and genetics program at Virginia Tech is dedicated to the development and enhancement of technology for plant breeding and precision agriculture. We combine high dimensional genomics with high-throughput phenotyping to build the high depth genome to phenome networks necessary to drive accelerated breeding decision making.

Utilizes - omics tools and precision technology to elucidate biological mechanisms that drive early animal health. Her research aims to improve cow and farm efficiency through various approaches including genetic selection, high throughput phenotyping, and use of biodegradable resources for feed storage.

Our lab is focused on development and deployment of precision animal agriculture technologies that can provide actionable information, generate management solutions and be readily adopted by beef cattle producers.

The Shenandoah Valley AREC creates, integrates, and shares knowledge to improve livestock, forage, and forestry production systems in Virginia by partnering with researchers, extension agents and specialists, and industry personnel.

Unmanned robotic systems to study the transport of pests in agricultural systems.

The Bargmann lab works on fundamental and translational studies towards crop improvement through genome-editing and tissue-culture.

My research spans the areas of artificial intelligence (AI) and cyberbiosecurity for water systems and smart agriculture. My team and I develop AI applications and assurance algorithms to address persisting water security and agricultural public policy challenges, such as: analyzing international ag trade, protecting water supply systems, optimizing smart-farming and precision agriculture, and understanding the economic effects of outlier events on biological systems (such as rivers and watersheds) using data-driven methods.

The focus of my research has been on insect ecology and improving pest management through the implementation of IPM strategies in several cropping systems. My main research areas have included the biology, life history and natural enemies of my focal studied organisms. I am also interested in using new technologies to complement the execution of pest management tactics in farmscapes.

Currently my lab is collaborating with three start-up companies investigating the potential of automatically counting and identifying plant-parasitic nematodes with several modern technologies including soil biome genomics and machine learning.

My research and extension program focuses on solving weed management challenges currently facing the Commonwealth, with emphasis placed on sustainable and economic solutions. Herbicide resistant weeds are one such challenge that must be met with strong, proactive approaches to weed management. Currently, these include harvest weed seed control, cover crops, and automated weed recognition.

Utilizes high-resolution stream and floodplain monitoring and remote sensing from drones for environmental and agricultural/forestry management. As such, I am interested in improved data analytics and visualization to better understand the large datasets I collect.

My research focuses on the bio-processing design to valorize various agricultural and food wastes for the generation of multiple value-added chemicals, materials, and biofuels for the seeking of a sustainable development of the agricultural and food systems.

As a restoration ecologist, my research and teaching aim to improve regional and global outcomes in biodiversity conservation, climate change mitigation, and livelihood improvement by assisting the recovery of damaged ecosystems. My research focuses on tropical forests in Latin America and Madagascar and temperate woodlands and grasslands in the eastern United States.

I work with best management practices for soil and water conservation including cover crops, fertilizer efficiency, and nutrient management as they relate to vegetable, grain, and oilseed production systems.

Boris A. Vinatzer’s research group focuses on fast and sensitive detection of plant disease outbreaks so that they can be contained before turning into epidemics and pandemics. By developing new experimental and bioinformatics tools for sequence-based classification and identification of plant pathogens, Dr. Vinatzer’s group helps protect Virginia, US, and world agriculture from current and emerging diseases.

I have had a number of research collaborations with CALS faculty in plant sciences going back to the days of microarrays (about twenty years). Research has involved gene expression, genomics, biological networks, machine learning, and data analytics. I see myself as a good contact for putting CAIA faculty in touch with appropriate computer science faculty.

Research focus is on agricultural development and its impacts on poverty and food insecurity in developing countries. I use a combination of household and other data to understand barriers to technology adoption and the potential of agricultural technology to enhance well-being.

I currently work with the AgrAbility and HARVEST programs at Virginia Tech continuing my work in user-centered design in agriculture. In addition to addressing usability and accessibility of precision agriculture technologies, I am studying how to best utilize big data in agriculture while also protecting the privacy and security rights of growers.

I’m looking at ways to make berry crop production more sustainable, and am interested in potential low input, technological innovations and solutions. I am also interested in automation tools and services to address human labor shortages at farm level to help the berry industry.

Using computer technology for the automatic and precise feeding of pregnant sows. New technologies for decreasing odor and nutrient release from pork production units.

My research focuses on developing food- and bio-processing technologies to produce food ingredients, animal feed, and green chemicals from agricultural and food products for improving the sustainability of the food production chain. Our group is specifically interested in exploring novel solutions (e.g., fermentation, extraction, fractionation, etc.) to convert food waste/byproducts to value-added product.

Flavor scientist interested in food quality improvement.

My area of inquiry is in identifying the contextual needs of the end-user in order to provide relevant and vital products.

I am interested in looking at agricultural applications of blockchain, as well as other emergent technologies like AI, IoT, and cybersecurity. I manage the Virginia Tech Blockchain Initative that has tremendous potential for innovating food supply-chains, increasing biosecurity, and developing reliable decentralized networks.

The goal of my extension program is to improve the financial and environmental sustainability of agricultural production systems. To achieve this goal, my program focuses on the implementation of best management practices related to energy efficiency, renewable energy, and nutrient management technologies. Typically, this work involves raising awareness of innovative technologies via demonstration projects and assessing the challenges to adoption of new practices.

My research emphasizes security strategies of organizations and their impact on decision making.

I am interested in how the soil and growing conditions of agriculture products influences the nutritional value of food and ultimately human health.

I develop new microbial biotechnologies as well as increase efficiency of plant-microbe interactions that support sustainable agricultural systems.

I am a macrosystems ecologist focused on landscape development, water resources and biogeochemistry, and environmental geography.

I developed and operate several web-based databases that enhance the productivity and sustainability of grape growers. One example is grapeIPM.org which is a pesticide management/decision support system where users can manage inventory, plan spray schedule, share the schedule with coworkers, print reports for WPS and EPA, and adjust spray schedule based on recent weather events and disease risks.

My focus is on creating STEM learning experiences that create career pathways into STEM careers, I started this research during my Ph.D. in Technology with Dissertation on “The use of sustained experiences in 4-H Fluid Power Education to Influence STEM Perception of Middle School Youth.” Other areas of research and engagement focuses are on vulnerable populations, girls in STEM, learner centered curriculum development, and educational technologies.

Dr. Czuba's research program extends collaboratively across multiple disciplines to advance the understanding of riverine ecosystems and their response to human and natural forces. The challenge to provide water, food, and energy for a growing population in the context of climate change is and will continue to place increasing pressure on riverine ecosystems. Dr. Czuba's research group incorporates theory, modeling, and field measurements to improve our understanding of these complex systems and better inform river management.

Over my 41-year career (16 years at VT), I have been a leader in several career paths, including creating new disciplines and pursuits, such as in forensic science and biosecurity. Most recently, I led the creation of cyberbiosecurity has rapidly become a global phenomenon and has enormous potential for CAIA and CALS.

Dr. Sarlo specializes in distributed, low-cost sensing to facilitate process monitoring and decision making.

My research interests include data analytics and visualization of high throughput biological data based on Machine Learning, computational, and statistical approaches to analyze and predict biological phenomenon of interests, polypharmacy side effects, and etc. My other research interests include smart DMBS construction and scientific software tool development that can broadly benefit the scientific research communities.

I research the effects of exercise and diet with respect to obesity and diabetes prevention. I do so with either environmental changes, exercise and diet interventions, or mineral supplementation. My research also includes studying fitness variables of athletes of all levels and ages, in particular, energy expenditure and substrate utilization.

My research focuses on the environmental and resource-use implications of agricultural production and the design of agri-environmental policy.

Application of remote sensing technologies, microbiology and machine learning to predict pathogen hot spots in agricultural environments farm to fork. Technology assisted pathogen source-tracking to limit foodborne outbreaks and recalls.

Economics and marketing research and extension activities focused on aquaculture, fisheries, and other coastal processes.

Most of my research involves economic analysis of policies and regulations affecting farmers and food consumers, including implications for markets, the environment, and human health. I use econometric and simulation approaches to study a variety of issues, including food safety, biotechnology, animal welfare, food loss and waste, and the impacts of COVID-19 on farms and international trade in food and agricultural products.

Molecular modeling, applied data science, and experiential education in the lab, classroom, and with industry partnerships. Understanding atoms with data and using data to make informed decisions while training our students to innovate at the interface.

My research program currently focuses on a) remote sensing with unmanned aerial vehicles (UAVs or drones) to monitor disease epidemics and water inefficiencies across turfgrass systems, b) field radiometry and thermal imagery for improving biological and environmental stress detection of turfgrass systems and specialty crops, c) novel strategies to reduce pesticide inputs through targeted applications, and d) fungicide performance, efficacy, and ancillary benefits.

My current research is applying Natural Language Processing (NLP) for keyword extraction from food reviews. This includes the investigation of whisky tasting notes and recipe ingredients. Overall, I work with NLP techniques for a variety of problem domains.

My research is primarily on gypsy moth management using mating disruption. I am currently participating in research aimed to develop technology for (1) aerial applications of pheromone treatments using UAVs and (2) detection of synthetic pheromones in the environment with the larger goal of developing smart technology for reliable pest detection and management using organic formulations with minimal non-target effects.

Michael has extensive experience working in all aspects of design in academia, for private companies, and the Federal and State Governments. Before coming to Virginia Tech in the Fall of 2016, he was the Design Lead at the NIEHS' National Toxicology Program (NTP) in Research Triangle Park, North Carolina. He has worked with other Federal agencies including NASA, NAVSEA, and the National Parks Service - creating a variety of work spanning data visualization and information design, to graphic and interactive design projects.

Dr. Moeltner’s research program focuses on the economic valuation of environmental resources and amenities, as well as changes in the flow of these services . Within the CAIA initiative, his primary interest centers on the economic implications of a more sustainable and environmentally friendly footprint of agriculture, due to advances in smart farming and other technological innovations, and on the modern data analytical tools required to assess these benefits. He is additionally interested in using machine learning and related “big data” tools to estimate the broader economic effects of improved food systems, health services, and rural community development.

SENSOR-BASED (satellite/drones/proximal) methodologies for economically and environmentally sustainable management in farm and orchard.

I bring expertise in the theory and practice of agricultural communications and visual communications. Adoption of technologies and integration of practice relies heavily on support from stakeholder and consumer networks. My work connects human behavior to the development of new products and processes in agriculture systems.

Dr. Sherif’s lab explores novel and alternative means of improving tree fruit resiliency to both biotic and abiotic threats, including spring frost and diseases.

We are researching on manipulating Light-Emitting Diodes (LEDs) lights to help improve plant health/production under a controlled-environment.

The Wright Plant Synthetic Biology lab integrates approaches from synthetic and computational biology, protein engineering, bioinformatics, molecular evolution, and genetics to quantify signaling dynamics, genetic interactions, and functional relationships in plant signaling.

My research is focused on economic analysis and sustainability indicators of the seafood supply chain, fisheries, and aquaculture, as well as building collaboration with institutions, industry stakeholders, and communities.

My work integrates biophysical and hydrological modeling with in-situ sensing to understand the processes controlling water and chemical cycles with the ultimate goal of developing management practices and informing policy that protect natural resources.

My research in agricultural education program design and implementation focuses on purposeful efforts to include diverse identities in all aspects of the agriculture and food systems. My work intersects with the mission and vision of the CAIA program as we work collaboratively to recruit and retain a diversity of talented individuals to contribute to the creation of transformative solutions to support emerging needs in the workforce.

The central theme of my research seeks to improve the efficiency of various agricultural operations for humans in specialty crops production (e.g., harvesting) and for machines in row crops production (e.g., spraying). My research also aims at optimal management of input (e.g., nutrients) to improve agricultural production productivity and sustainability while sustaining the quality.

The overall objective of Dr. Lahne's research program is to develop new methods for the sensory evaluation and analysis of foods and to use those methods to generate knowledge in unexplored areas of sensory science. His efforts to achieve this are centered in 3 areas: an emphasis on developing novel, rapid methods and measurement tools in a variety of sensory-related fields for understanding human perceptions of food; a programmatic focus on the sensory evaluation of fermented and distilled beverages; and a commitment to bringing critical, interdisciplinary scholarship to the insular world of food-sensory science. Dr. Lahne's current projects mostly focus on understanding the sensory qualities of Virginia (and American) hard cider, the application of Natural Language Processing methodologies to unstructured consumer descriptions of food, and the critical integration of food science and food studies.

My group works on the application of computer vision systems for high-throughput phenotyping and the integration of high-throughput phenotyping data into a quantitative genetic framework.

Dr. Jacobs’ research is focused on production animal behavior and welfare. She aims to 1) validate objective measures of animal welfare, including automation and technology-based methods, and 2) identify feasible approaches to improve animal welfare in a commercial setting.

My work uses data science, machine learning, and decision analysis to make agricultural systems more resilient, productive, and sustainable, with a specific focus on irrigation and climate change.

Jennifer Van Mullekom, Director of SAIG, collaborates with researchers in all disciplines across campus. As a former practicing statistician, she brings over 25 years of collaborative team science and business experience to the table with experience in research and development, operations, marketing, supply chain, and regulatory. Her research areas include experimental design, predictive modeling, machine learning, data analytics, statistical practice, and statistical practice ethics.

Integration of computer learning and sensor technologies for the creation of athlete-specific diet and training programs.

My research focuses on plant-pathogen interactions, characterizing the mechanisms of disease resistance, and inheritance of disease resistance in tobacco. My extension program focuses on engaging students, teachers, and the general public in agricultural science education.

Analysis of materials from plants, animals and microbes using advanced mass spectrometry techniques. Mass spectrometry-based proteomics and metabolomics.

The Southwest AREC maintains research programs related to hair sheep and beef cattle production management, focusing on improved animal performance and health through genetic improvement and nutrition. Additional research components also focus on forages, grazing management, and supplemental animal nutrition.

Our group focuses on understanding the molecular mechanisms that drive infertility and embryo losses at the early stages of development. We work with systems genomics approaches combined with sophisticated analytical procedures to improve sustainability in cattle production.

My research focuses on parasitic plants, with emphasis on the molecular and genomic features that enable parasitism. This work provides insights into plant-plant interactions, with implications for developing innovative approaches to controlling parasitic weeds and understanding how crops and weeds respond to each other.

My research focuses on vegetable disease control through the use of 1) early detection technologies and/or 2) weather-based prediction algorithms.

Mannin leads a software development and IT operations team providing location intelligence and data management services for national forest health protection programs. He responds to wildfires and other natural disasters as a GIS Specialist with the Southern Area Incident Management Blue Team.

My research is on navigation of dynamic systems, on sensor sensor data processing, including safety monitoring for autonomous systems. I work on precision GPS, LiDARs, radars, inertial sensors for air, ground, and sea vehicles.

Livestock enterprise efficiency can be a key to profitability and sustainability. One of my passions is researching tools to balance advancements in technology with realistic producer needs. Researching avenues to increase livestock enterprise efficiency, simplify livestock data management, reduce livestock health costs, increase producers digital connection to their livestock, increase health awareness for horse owners through utilizing new technology.

Our group is broadly interested in how microorganisms interact with their environments to affect soil and water quality. In particular, we are interested in how newly available high-resolution data describing microbial diversity and function can be effectively leveraged to improve understanding and predictability of agro-ecosystems.

At VTTI, I oversee the Division of Technology Development and Deployment, which is comprised of groups responsible for IT, Mechanical Systems and Facilities Operations, Electronic Systems and Technology Innovation. I am interested in leveraging the skills and experience we have developed in the areas of transportation and mobility to contribute to achieving the goals of CAIA.

The goal of my research program is crop improvement through the use of molecular markers and the emerging genomics and bioinformatics tools.

My research on Natural Language Processing and Machine Learning can automatically process large-scale text data and construct knowledge networks to support data analysis, decision making, task performing, education and training for both agriculture and life science.

Dr. Singh works on digital agriculture and data driven technologies under Virginia Tech's Smart Farming Initiative. His team tests Unmanned Aerial Systems (UAS)/sensor-based ground vehicles and robots for weed species differentiation, herbicide-resistance detection and spray applications for precision weed management.

My research is focussed on the health of freshwater systems, with an emphasis on attenuating landscape-derived nutrients and pollutants through streams, rivers, and floodplains.

My research revolves around machine learning challenges related to data, e.g., learning with limited imperfect supervision, self-supervision, multi-modal representations, active and semi-supervised learning, adversarial training. I am interested in building intelligent task assistants that augment human intelligence, human-in-the-loop machine learning, and machine learning for sustainability and climate change.

I am the administrative leader for the Entomology department. My research and Extension experience has included work in row crops (corn, cotton, soybean, wheat), biofuels and pine forests, where my research focused on increasing reliance on beneficial organisms to help reduce pesticide inputs while increasing profitability.

My research, teaching, and outreach are focused on the interface of agriculture and data science. My team develops computational tools and machine learning methods to integrate and interpret large scale data generated by advanced genomics and sensor technologies in agricultural research. More specifically, my research program includes two broad themes. First, we use machine learning to identify gene regulatory networks in plant abiotic stress responses. Second, we develop sensing technology and computational tools for early detection of plant diseases and to collect plant phenotype data at field scale to improve crop breeding programs.

As the Coordinator for the Virginia Geospatial Extension Program (VGEP) and VirginiaView (VAView), I support the role of Virginia’s communities and other stakeholders, by engaging professionals and organizations by hosting technical training and workforce development opportunities, by developing educational resources, and through the identification and execution of geospatial applications to support data driven decisions.

Cyber-physical security; operation of autonomous and automated systems in uncertain and adversarial environments; physical-layer attacks and defenses.

I am interested in food and flavor chemistry of food products, focusing on quality, shelf life, and consumer acceptability.

My research program focuses on development of applied fruit fermentation strategies that take into account fruit biodiversity in production of value-added products from fruit. Recent projects have focused on interactions between the chemical composition and fermentation of apples, grapes, and cacao.

Reliable, secure, and resilient smartfarms.

Research on irrigation management and culture practices on vegetable production systems.

The purpose of my program is employing modern molecular detection and quantification technologies like digital PCR with the goal of elucidating plant pathogen biology, ecology, management and population dynamics. Recent projects focused on commercial introduction of novel cloud-based disease prediction models for tree fruit, quantitative parameters of survival of fire blight bacterium Erwinia amylovora in fruit tree hosts, identification of Colletotrichum species that cause apple bitter rot, and development of new or improvement existing strategies for disease management. Future projects will explore new hyper-spectral visual tools for efficient disease management options on tree fruit such as apple, pear and peach.

Research (and Related Outreach) using intelligent autonomous systems to improve crop performance, yields, inventory and prediction/response to abiotic and biotic stressors.

My research centers on environment, development, and agriculture, with a focus on how advances in remote sensing and machine learning can help equitably and efficiently enhance environmental compliance in the US and improve programs to manage weather risk around the globe.

Brian helps connect researchers in the Sanghani Center to internal and external collaborators to propose and execute impactful research.

Developing and applying new sensing techniques to measure environmental processes in agricultural and other systems; building data-driven and physics-informed models for these processes.

I bring expertise in leadership development and stakeholder involvement that can help CAIA achieve its vision "to foster informed decisions" through broader application of collective leadership and leadership-as-practice. My work includes engagement with agriculture workforce training programs, including those in formal educational settings (e.g., community colleges) and nonformal professional learning programs (e.g., Virginia Cooperative Extension).

Weather impacts and farm household vulnerability.

My research interest is in developing computational and statistical tools for processing and analyzing large-scale data. Currently we are developing machine learning models for predicting soil adsorption rates of various chemicals with possible application to smart agriculture.

Dr. Ross has advanced the state-of-the-art in the analysis and visualization of environmental transport. He initiated the use of atmospheric transport barriers in understanding the biological invasion of microorganisms, particularly plant diseases of agricultural crops. He has done field work and Lagrangian transport computations analyzing the dispersal of hazardous material in aquatic environments, including lakes and oceans and harmful algal blooms.

My research focuses on a new field of engineered living materials in which microbes are engineered to produce functional material for various applications. I want to apply this new field to multiple aspects of agriculture.

I am an energy and environmental economist interested in policy evaluation, policy design, and incentive mechanisms to promote conservation and sustainability to combat the climate change. I am particularly interested in studying policies to improve the economic and environmental well-being of disadvantaged populations. In my research, I combine different theoretical and empirical strategies, such as general equilibrium modeling, optimal control theories, randomized control trials, and natural or policy experiments.

My research is focused on Biotic and abiotic crop stress management| Remote sensing of crop and soils: ground, aerial, and satellite-based| Internet-of-things enabled cloud and edge computing systems| Machine vision and 3D point cloud data analytics| Variable and alternate spray technologies: ground and aerial| Agricultural machinery systems: autonomous and semi-autonomous.

Data-driven decision making, multi-agent systems, cyber-security.

My research focuses on data analytics using empirical and simulation approaches to understanding general equilibrium impacts of agricultural market structures and welfare analysis of agricultural technologies.

Leveraging data science to improve precision farming and animal breeding.

I conduct research on weed biology and management in horticultural crops, as well as overseeing turfgrass research at the HRAREC.

Dr. Ali’s lab focuses to develop next-generation biosensors enabled by microfabrication and 3D printing to monitor livestock health, food safety and agriculture parameters. Further, his research lab is also aiming to integrate advanced biosensors with wearable platforms which can bridge the gap between on-site testing with real-time data acquisition and analysis, and achieve improved detection, prediction, and treatment of animal diseases and sustainable agriculture.

Integration of farm management with data analytics.

The overall goal of my research is to improve crop performance in controlled environment agriculture, with a focus on utilizing beneficial microbes to improve crop health.

Using sensors systems to monitor animal health and improve early disease detection in livestock animals.

John is working with technology adoption through the Graze 300 program and on integrated agrophotovoltaic systems.

I am a Sociologist who studies rural communities in the context of hazards and disasters.

My research is in applied econometrics. I focus on applications at the intersection of labor, health, regional economics, and rural development. I am the Director of the Data Science for the Public Good Program in the Department of Agricultural and Applied Economics, which houses the Data Analytics in Agriculture, Community, and Rural Economics (DATA-ACRE) Research and Extension Experience for Undergraduates.

I have an ongoing interest in the department's Data Science for the Public Good project, which links Extension, Applied Research, and student training to inform local and regional decision making with data. My research interests are in the application and use of nonlinear time series models for prediction.

My work focuses on food access, food security and the food environment. My work supports the CAIA mission to leverage science to support food systems and communities in the Commonwealth and beyond.

soybean breeding and genetics

I am a structural biologist and biophysicist who can collaborate with CAIA members by providing molecular studies of proteins.

Translating data into actionable decisions is central to research in agriculture and the life sciences and the Center for Advanced Innovation in Agriculture. Applied economics and analytics facilitate and accelerate the profitability and sustainability of technological advances.

My research interests center on plant compounds of importance to human and animal health, and how stresses or cultural practices modulate these compounds in plants. I use an interdisciplinary approach, using a variety of tools from biochemistry to remote sensing, and collaborate with colleagues in different disciplines. The ultimate goal of my research program is to improve crop quality and yield, food security, and human health and nutrition.

My work related to the CAIA centers on understanding and developing people, groups, and communities to promote the creation, implementation, and evaluation of effective solutions.

Advance AI-aided material discovery & optimization for food processing and packaging; Develop intelligent, active & connected packaging.

My research interests relate to applications and implications of nanoscale science and engineering in environmental and agricultural systems.

My research program has two foci: 1) developing crop disease forecast models by integrating large datasets generated by multi-comics and environmental sensing technologies, and 2) harnessing plant microbiome to promote crop health.

I use big data and various computational skills to answer questions related to agricultural and food policies.

My expertise is intelligent wireless sensor nodes to monitor animals, soils, crops, plants, forests, and others.

Establishing an effective integrated pest management (IPM) program relies on timely detection of pest conditions. We used advances in imaging and remote sensing technology for early-detection, pest monitoring, and successful implementation of IPM in our regional agroecosystems.

I investigate IPM strategies for managing invasive insects. I also examine hurdles associated with IPM adoption among different stakeholders.

My research interests are driven by production limitations resulting from plant diseases and are broadly categorized as the optimization of pesticides applications, disease diagnostics and early detection, and the advancement of novel and integrated disease management tactics.

My research focuses on applied econometrics in the area of rural and regional development. My research program broadly focuses on labor, health, and education including disparities by gender, race, or disadvantaged individuals. I use several causal inference tools such as natural/policy experiments and randomized control trials.

My research program focuses on the extraction of lignocellulosic biomass from agricultural and food byproducts and also the structural modification of these compounds to improve their health benefits using innovative food processing methods.

Research drinking water contaminants in private wells and spring including microorganisms, arsenic, contaminants of emerging concern (pharmaceuticals, PFAS), lead and household water access and equity.

My research is focused on improving agricultural sustainability and food safety through a lens of microbial ecology and evolution.

Maria Balota is a Professor with two-way appointment in the School of Plant and Environmental Sciences (SPES) covering 50% research and 50% extension. She resides at the Tidewater Agricultural Research and Extension Center (TAREC) in Suffolk, VA, where serves as the leader of the multi-state Peanut Variety and Quality Evaluation (PVQE), which is the pipeline for Virginia-type peanut cultivar development for Virginia and the Carolinas. In this capacity, Balota has expertise in stress physiology of field crops and aerial high-throughput phenotyping for indirect crop selection.

A major focus of our research is on developing smart technologies for improving feed utilization efficiency in ruminants and facilitating efficient bioconversion of food and agriculture wastes to value added materials. In both cases anaerobic microbial consortia are the work horses and complex syntrophic and redox processes dictate their fates and metabolic outputs. We are investigating the intricacies of these complex systems employing wet bench and computational approaches with the goal of identifying the precise means for manipulating the consortia towards the most desirable metabolic actions - optimal digestion of the feed in ruminants and efficient conversation of food wastes of highly variable composition to natural gas.

My research is about valuable resource recovery in the forms of chemicals and energy from wasted materials such as food waste, wastewater, municipal solid wastes, agricultural residues, etc.

My research focuses on natural language processing and text mining for massive text data analysis at scale. It aligns with CAIA in facilitating the interpretation of large data sets for advancing the use of new technologies in agriculture.

Our soybean breeding program aligns with the CAIA research platform on SmartFarm Innovation Network. Specifically, we provide solutions to current soybean and edamame production challenges.

CAIA requires a sociotechnical security approach. This work offers an opportunity to seek expertise from different partners when building new solutions. Innovation also requires ethical and professional thinking, as well as community and leadership engagement.

Our lab evaluates precision animal agriculture technologies for ruminants and equines in a wide range of applications, including health monitoring, behavior tracking, and pasture management.

I am the Platform Leader for the Controlled Environment Agriculture Innovation Center. I conduct research in controlled environment agriculture with a focus on the production of crops such as lettuce, herbs, medicinal plants and strawberry in soilless and hydroponic systems in greenhouse, factories and vertical farms.

Dr. Oakes has expertise in using aerial imagery from UAVs in agronomic management and high-throughput phenotyping in agronomic crops. He is a member of the CAIA Faculty Leadership Group and is the platform leader for SmartTechnologies for Crop and the Green Industries.

Our lab conducts research at the interface of animal agriculture, sustainable food production, technology, and data analytics, leveraging sensors and animal monitoring technologies to improve efficiency and sustainability of animals-source food production.

My work related to the CAIA revolves around evaluation of cyberbiosecurity efforts and education and training that can help stakeholders in agriculture identify vulnerabilities in their systems and mitigate before an attack.

My scholarship includes the intersection of agriculture, disability, and technology. I am also interested in the politics and ethics of sociotechnology for sustainable food systems.

Advancement of Controlled Environmental Agriculture towards advancement of food safety, security, and sustainability, and integration with SmartFarm technologies via machine learning and Artificial intelligence.

Biological Systems Engineering, CAIA Stakeholders Committee, Sustainable Precision animal agriculture, Smart Technologies for crop and Green Industries, Data Analytics. "CAIA timely and relevant platforms are designed to innovate and apply new technologies in support of Agriculture and life sciences industries."

Vernon is the Assistant Dean of Advancement and oversees the fundraising, alumni relations, and communications and marketing areas of the college. Through these efforts he and the advancement staff interact with alumni, stakeholders, and corporate partners to engage them more closely with the Center for Advanced Innovation in Agriculture, the SmartFarm Innovation Network™, the college and Virginia Cooperative Extension.

My research explores using reproductive technologies in ways that will improve fertility and optimize calf production in dairy and beef cattle. The laboratory's current work focuses on identifying ways to improve early embryo survival and to generate heifer calves from high genetic merit cows using ovum pickup and in vitro fertilization.

As a researcher with expertise in designing and developing intelligent user interfaces, I am excited to apply my skills to the field of agriculture at the Center for Advanced Innovation in Agriculture. While I may be new to this area of research work, I bring a strong background in understanding target users' barriers and needs across various domains. I am eager to adapt my experience to the unique challenges faced by farmers, agronomists, and educators in agriculture. My approach involves ideating and designing innovative solutions tailored to the needs of the agricultural community, and evaluating these solutions through user studies. I look forward to contributing to the ongoing transformation of agricultural processes and technologies and expanding my knowledge in this vital center.

My research program focuses on developing imaging and sensor based techniques to monitor seafood quality and safety, as well as sustainable processing strategies to process value-added products.

The goal of my forage research and extension programs is to provide unbiased information through applied research that relays applicable technology and management strategies to support our forage and livestock producers; leading to an improvement of their production efficiency, increase the profitability of their operation, and enhancing forage, livestock, and environmental quality.

Zhenshan's research involves bringing in high-quality large datasets and tailoring novel statistical methods based on specific research questions. His most recent research focuses on farmers' values and acceptance regarding Agrivoltaics - the dual-use of farmland for agriculture and solar energy.

In our research, we map honey bee foraging by observing their waggle dances (see for example foraging in the row crops of the Tidewater AREC: https://youtu.be/UYe-gNlzjZc). We hope that this will tell us where the landscape is healthy for pollinators in general. Furthermore, we are interested in developing methods to map species distribution from airborne environmental DNA (eDNA). Such mapping would have implications for ecological studies, conservation, and pest management.

Creation of chemical sensing and biosensing technology (e.g., biosensors and chemical sensors) and data analytics for smart and secure agriculture.

My primary interests are in farm management, agricultural financial management, entrepreneurship, and personal financial management.

Grassland Ecology, Forage Science

Climate-smart agricultural water management and modeling; Food-energy-water nexus assessment.

I apply mathematical rigor and high performance computing to numerically solve problems in agriculture, engineering, and science. Mathematical modeling and multidisciplinary collaboration characterize my work.

Social implications of emerging digital technologies in agriculture.

My research interests include the application of sensory and consumer science as well as the application of food and flavor chemistry to guide sustainable development and production of high-quality food crops, new foods and beverages with economic benefit for local farmers and business. I am also interested in cyberbiosecurity efforts to protect farms and food businesses from cyber attacks.

My research on open-world machine learning can automatically process spatial-temporal data and support data analysis, decision making, anomaly detection, risk management, and predicitve mantainance for both agriculture and life science.

Research focusing on new technologies and cultural practices to improve ornamental and edible greenhouse crop production.

My research focuses on ecological engineered technologies, such as treatment wetlands and subsurface bioreactors, for remediation of agricultural and urban pollutants (nutrients, pathogens, etc.). My lab investigates the relationships between environmental and hydraulic conditions and biogeochemical processes to better understand remediation mechanisms and inform resilient designs of these technologies.

My research program facilitates the understanding of key components of the genomic, molecular, biochemical and physiological responses to abiotic stress in critical crop species with the goal to develop climate resilient crops. My research uses computational and molecular tools, and be enhanced by the use of digital agriculture.

My research aims to improve the sustainability of vegetable cropping systems through the use of interdisciplinary data modelling and new developments in precision agriculture.

My research profile is closely aligned with the mission of CAIA at Virginia Tech. My research interests and background primarily focus on sustainable food technology, bioprocessing, alternative proteins, food science, and functional foods, which directly contribute to CAIA's goals of finding technological solutions to enhance food production efficiencies and promote sustainability in agriculture. I am enthusiastic about collaborating with CAIA to advance research in these critical areas.

I study how bacteria are move and survive in agro-ecosystems with a goal to develop strategies to improve food safety and quality.

My research focuses on multi-scale understanding the environmental occurrence, fate, and impact of anthropogenic organic contaminants in aquatic and soil systems. I bring expertise in trace level organic contaminant analysis of complex environmental matrixes. I am actively engaged in developing undergraduate teaching curriculum that infuses data science into environmental science.

Dr. Rhoads’ research involves investigating aberrations in metabolic and/or endocrine profiles of multiple livestock species (primarily dairy/beef cattle, swine) with special interests in interactions between fertility, metabolism and environmental stress. Her lab has recently been exploring opportunities to apply artificial intelligence in aspects of livestock research.

My laboratory group focuses on insect behavior in agroecosystems. Our research questions are aimed at developing insect pest management solutions that are founded on ecological principles, and reduce grower reliance on insecticides.

I am a regional scientist and environmental economist with an interest in land use and local economic development. I am also involved with the Data Science for the Public Good program.

My research focuses on management and use of agricultural, municipal, and industrial byproducts (e.g., animal manures, biosolids, composts, biochar etc.) and studying the impacts of their land application on soil, water, and air quality while integrating advanced and smart precision techniques.

My lab's research interest is at the interface of physical and life sciences. We use our mechanical science and engineering knowledge to discover the physical underpinnings of living systems’ behaviors and to pioneer innovative solutions to address grand challenges in human health and food, air, and water security. Our current research interests include the development of distributed mobile sensor networks and bio-inspired microrobotic systems to monitor plants and pests to increase crop yield and minimize environmental impact.

Development of fibrous environments to mimic natural arthropod locomotion and force exertion. Understanding the prey-predator interactions and developing smart robotic technologies for pest mitigation.