The lab of Dr. Eshwar Ravishankar. We grow food and energy from the same sunlight through agrivoltaics, engineer controlled-environment farms, and build the sensors and machine learning that run them.
The California Energy Commission has selected our project for a $2.1M EPIC award under its SPLINT program (Solar PV Located in Non-Traditional Terrain), ranked 2nd of 19 proposals.
Meeting California's goal of 100% clean electricity by 2045 could take solar on half a million to a million acres, much of it farmland. Our project, Scalable Agrivoltaics in California: Field-Validated Co-Optimization of Solar Generation, Battery Dispatch, and Crop Production, builds the tool that shows when panels, batteries, and crops can share the same acre, and what each one gives up.
We will extend the lab's published ray-tracing and crop model with battery dispatch and multi-objective optimization, map agrivoltaic suitability across the service territories of California's three investor-owned utilities, and test the model against field measurements at five sites. The validated engine will be released as open-source software, and HARVEST California will bring it to growers through bilingual workshops and statewide outreach.
A mechanical engineer who fell for plants, and now builds the systems where the two disciplines meet.
Trained through a Ph.D. in Mechanical Engineering at NC State, I spent years engineering semitransparent organic solar cells that let a greenhouse generate its own electricity while the crops beneath still thrive. That question became my research program: how do you divide one photon budget between a harvest and a kilowatt-hour?
Today, as Assistant Professor of Plant Science, Graduate Program Coordinator, and a CEMaST Faculty Scholar at Cal Poly Pomona, I direct a lab that works across agrivoltaics, controlled-environment agriculture, and precision remote sensing. We build real hardware, sensor it heavily, and wrap it in energy–water–plant models that tell growers what to do next. In 2026 the Huntley College of Agriculture named me its Outstanding Faculty Advisor.
Every project shares one idea: treat sunlight, water, and land as a shared budget, then engineer the system that spends it best.
Sharing sunlight between panels and plants: from spectral beam-splitters modeled with ray-tracing and crop models, to field-validated co-optimization of solar generation, battery dispatch, and crop production across California.
Net-zero-energy greenhouses roofed in semitransparent organic solar cells, balancing crop yield against on-site power, validated with genomics and global techno-economics.
A container vertical farm, a mushroom production room, and automated hydroponic benches on a custom-built controller: IoT-sensed, energy-aware, and designed for the city.
UAV multispectral imaging, GIS, and ground robots turning fields into daily data, including telling panel shade apart from real crop stress.
An eight-crop simulation engine coupling photosynthesis to greenhouse energy and water balances runs a full production year in about ten seconds, with a machine-learning surrogate trained on 168,000 simulations. It is now an open web tool and a Cal Poly Pomona invention disclosure.
Behind every system is a real person deciding how to spend a scarce resource: a beam of light, an acre of land, a kilowatt of power. We build the tools that help them decide.
Keep land in production and add clean power on the same acre, with field-validated numbers on exactly what yield trades for what energy.
Drive the energy bill toward net-zero by turning the roof itself into a power source, without giving up the crop underneath.
Grow reliable local food in cities and on marginal land with automated, energy-aware controlled-environment systems.
Train students on the drones, sensors, and models that modern sustainable agriculture actually runs on, hands-on from week one.
A 12 kW off-grid array of elevated, fixed-tilt solar panels over working crop beds, with romaine lettuce growing in their shade.
At Cal Poly Pomona's Spadra Farm, we run replicated romaine trials beneath the panels, comparing regenerative and conventional fertility. Across three crop cycles and 2,805 harvested plants, the panels cost 12–27% of seasonal yield, and regenerative fertility raised absolute yield without closing that shading gap. Flagged plots, drip lines, and drone flights turn the whole array into a dataset. The site is also a study site for the FFAR Seeding Solutions project led by Pitzer College, and the template for our CSU ARI work and our California Energy Commission SPLINT project.
We build indoor grow systems that sense, decide, and act, down to the milliliter of nutrient.
Our controlled-environment platform pairs a custom-designed Raspberry Pi hydroponic controller board with an open-source Mycodo stack. It reads pH, EC, CO₂, temperature, and VPD on a 30-second cadence, then drives a phase-gated flood-and-drain cycle, climate control, and automated pH and nutrient dosing: the same framework re-tuned for microgreens, lettuce, and mushrooms. Students use it to run real crop trials, and the first M.S. thesis built on it was completed in 2026.
Benchmarking Spectrum-Splitting Agrivoltaics Using Spectrally Resolved Ray-Tracing and Crop Modeling for Yield–Microclimate–Energy Balance Across Arid and Humid Climates
Ravishankar, E., Vitoshkin, H., Kribus, A., Mittelman, G., Rozenstein, O., Hernández, R.
Agrivoltaics Can Add Value to High Tunnels in a Subtropical Environment
Field, R., Abernathy, B., Ravishankar, E., Cassity-Duffey, K., Vaughn, J.
Achieving Net-Zero-Energy Greenhouses by Integrating Semitransparent Organic Solar Cells
Ravishankar, E., Booth, R.E., Saravitz, C., Sederoff, H., Ade, H.W., O'Connor, B.T. · Cover feature
Organic Solar-Powered Greenhouse Performance Optimization and Global Economic Opportunity
Ravishankar, E., Booth, R.E., Hollingsworth, J.A., Ade, H.W., Sederoff, H., DeCarolis, J.F., O'Connor, B.T.
Balancing Crop Production and Energy Harvesting in Organic Solar-Powered Greenhouses
Ravishankar, E., Charles, M., Sederoff, H., Ade, H.W., O'Connor, B.T., et al. · Highly Cited Paper
Emergent Molecular Traits of Lettuce and Tomato Grown Under Wavelength-Selective Solar Cells
Charles, M., Edwards, B., Ravishankar, E., et al.
Environmental and Economic Impacts of Solar-Powered Integrated Greenhouses
Hollingsworth, J.A., Ravishankar, E., O'Connor, B.T., Johnson, J.X., DeCarolis, J.F.
Economic Potential of Open-Field Agrivoltaics with Planar Spectral Beam Splitting
Mittelman, G., Atiya, V., Vitoshkin, H., Hernández, R., Ravishankar, E., Kribus, A.
When the Controller Becomes the Predictor: Lessons from Machine Learning in Hydroponic Lettuce
Gutierrez, G., Mattia, S., Kosaraju, S.C., Ravishankar, E.
Machine Learning Identifies Non-Destructive Indicators of Crop Response to Agrivoltaic Shading
Imtiaz, A., Kelly, M., Kuhn, E., Phillips, S., Fox, A., Olivas, R., Kosaraju, S.C., Ravishankar, E.
From Agricultural Machine Learning to Field Decisions: Interpretable Rules, Sensor Requirements, and Failure Modes
Cao, J., Green, C., Corrales, L., Le, N., Ravishankar, E., Kosaraju, S.C.
In August 2026 our graduate and undergraduate researchers gave eight oral presentations at the American Society for Horticultural Science Annual Conference, across agrivoltaics, controlled-environment ag, and machine learning. Want us at your event? Get in touch.
Interpretable Support Vector Machine Modeling Identifies Environmental–Physiological Disease Transition Zones in Tomato
Carson Green presented · with Corrales, Mattia, Ravishankar & Kosaraju
Machine Learning-Based Crop Recommendation Using Environmental and Edaphic Variables: A Comparative Analysis of Random Forest, SVM, and Neural Network Classifiers
Joshua Cao presented · with Le, Green, Mattia, Ravishankar & Kosaraju
Evaluating the Predictive Limits of Environmental Variables for Plant Disease Detection and Health Monitoring Using Machine Learning
Nikki Le presented · with Cao, Corrales, Green, Mattia, Ravishankar & Kosaraju
Nonlinear Machine Learning Reveals Temperature Thresholds in Rice Yield
Joshua Cao presented · advised by Ravishankar
Seasonal Yield and Physiological Response of Romaine Lettuce Under Fixed-Tilt Agrivoltaics in a Semi-Arid System
Megan Kelly presented · with Kuhn, Connelly, Campbell Freire, Duong, Briceno, Fox, Cesena Olivas & Ravishankar
Beyond Mean Yield: Machine Learning Reveals Within-Plot Uniformity as a Key Classifier of Agrivoltaic Lettuce Production
Areesha Imtiaz presented · with Kelly, Kuhn, Connelly, Campbell Freire, Duong, Briceno, Fox, Cesena Olivas, Kosaraju & Ravishankar
Fixed-Tilt Agrivoltaic Panels Restructure Soil Fungal Communities and Enrich Plant-Pathogenic Genera in a Semi-Arid Romaine Lettuce System
Areesha Imtiaz presented · with Kelly, Kuhn, Connelly, Campbell Freire, Duong, Briceno, Fox, Cesena Olivas & Kosaraju
Integrating Low-Cost Adaptive Nutrient Control with Time-Series Modeling to Improve Growth Prediction and Resource Efficiency in Indoor and Greenhouse Lettuce Production
Gerardo Gutierrez presented · with Mattia, Kosaraju & Ravishankar
Vertical Farming Show
Orange County, CA
Smart Agriculture Summer Camp, Wayne State University
Recorded talk for a USDA-funded high-school program: from Raspberry Pi sensor builds to a full-scale container farm
Mt. San Antonio College
Next generation greenhouses can be fully solar powered
Orange County Rare Fruit Growers
Lecture and demonstration
CEAg World Conference
Raleigh, NC · Using predictive planning systems and environmental data to predict yield and energy in controlled-environment agriculture
Plant Science Initiative, NC State University
Raleigh, NC
AgriVoltaics World Conference
Denver, CO
ASHS Annual Conference
Honolulu, HI
National Adaptation Forum
St. Paul, MN
Since 2023: 23 competitive awards, 15 as Principal Investigator, led by a $2.1M California Energy Commission award to scale agrivoltaics across California.
My courses put drones, Raspberry Pi sensors, live crops, and real data in students' hands from week one.
Students take a crop from seed to harvest, work out the math of a hydroponic nutrient solution, and compare lighting, climate control, and energy use across the campus container farm and research greenhouse. Formerly Plant Science 1.
Precision agriculture, remote sensing, IoT, and AI. Students build Raspberry Pi crop sensors, run GPS/GIS and LANDSAT/NDVI mapping, and complete a real project at the AgriScapes farm.
Mushroom cultivation from substrate and aseptic culture to fruiting, with IoT climate control and automation, in an indoor production room built for the course. Revived and first offered in Spring 2026.
Redesigned for Fall 2026 as a Python edition: experimental-design theory paired with code-along labs on real agricultural data, fourteen scaffolded checkpoints, and a strict reproducibility standard.
A new course in curriculum review: FAA Part 107 knowledge, safe UAV operation, and precision-ag imagery, with generative AI use built in and assessed. An NDAA-compliant teaching fleet is in procurement.
A new GIS course co-developed with Dr. Miranda Aiken and Dr. Guadalupe Maldonado Andrade, now in curriculum review.
Two of these courses, PLT 3020 and PLT 4210, earned Cal Poly Pomona's PolyX polytechnic-signature-experience designation for their build-and-operate design, and PLT 4210 was featured in the 2025 PolyX Faculty Spotlight. Thirteen instructional and student-research awards, including three SPICE classroom-innovation grants, have equipped these courses, and 60 paid micro-internships let student teams build the container farm, the mushroom room, and a greenhouse plug-production system. With Computer Science, Spadra drone imagery now powers programming assignments in CS 1400.
An interactive teaching tool I built: students adjust light, CO₂, and temperature and watch a live photosynthesis model respond. Free to use in class.
Engineers, biologists, and builders who like to make things grow. Here's who you'd be working alongside.
Mechanical engineer turned plant scientist; builds the systems where food and energy meet.
Plant Science · Spadra Farm agrivoltaics.
Mechanical Engineering · Spadra Farm agrivoltaics.
Mechanical Engineering, minor in Computer Science · AgriScapes greenhouses. Oscar Perlaza President's Scholar.
Computer Science · AgriScapes greenhouses.
Plant Science · Spadra Farm agrivoltaics.
B.S. Plant Science · AgriScapes greenhouses.
B.S. Plant Science · AgriScapes greenhouses.
B.S. Computer Science · agrivoltaic machine learning; ASHS 2026 speaker.
Papers, grants, and milestones as they happen. Send me your latest talks, awards, and new members to keep this current.
I mentor students who like to build things that grow. Whether you come from engineering, biology, computer science, or the soil itself, there's a bench for you.