Sathish Samiappan
I build artificial intelligence and multi-sensor remote sensing to help us see, understand, and protect agricultural and natural systems. My work spans the full sensing stack (hyperspectral, multispectral, LiDAR, and satellite imagery) and the full pipeline from foundational algorithms and foundation models to the low-cost, edge-AI instruments that put those models to work in the field. I apply these tools to soil and plant health, water quality, forest and ecosystem health, invasive species, and land conservation.
The classroom and the lab matter to me just as much: I teach because I believe the objective of education is learning, not teaching, and I measure my success by the students who leave able to build what they once thought impossible.
I build foundational AI and multi-sensor remote sensing, from hyperspectral to satellite, to detect and predict threats to agricultural and natural systems, contributing new algorithms and sensors, not just new applications.
I teach for learning: I build ideas from simple foundations into elegant structures, ground theory in hands-on work, and mentor students into independent, confident learners.
- In my lab I am currently working through questions :
- How can foundation models and compressive sensing make hyperspectral imaging practical from the leaf to the landscape?
- Can low-cost, edge-AI sensors deliver real-time monitoring of crop stress, pollinator health, and water quality in the field?
- What can satellite, spatio-temporal data tell us about soil health, soil carbon, crop yield, and land-cover change?
- How can remote sensing detect and forecast threats to agricultural and natural systems (invasive species, plant disease, and harmful algal blooms)?
- How do we turn AI-driven sensing into explainable, trustworthy decision-support tools that growers and agencies can act on?
2506 E J Chapman Drive
Knoxville, TN 37996
- PhD, Electrical and Computer Engineering, general, Mississippi State University, 2014
- MSE, Computer Science and Engineering, Amrita University, India, 2006
- BE, Electrical, Electronics and Communications Enginee, Bharathiar University, India, 2003
- Dipl, Electrical, Electronics and Communications Enginee, Kongu Polytechnic, India, 2000
Sathish Samiappan
2506 E J Chapman Drive
Knoxville, TN 37996
- PhD, Electrical and Computer Engineering, general, Mississippi State University, 2014
- MSE, Computer Science and Engineering, Amrita University, India, 2006
- BE, Electrical, Electronics and Communications Enginee, Bharathiar University, India, 2003
- Dipl, Electrical, Electronics and Communications Enginee, Kongu Polytechnic, India, 2000
I build artificial intelligence and multi-sensor remote sensing to help us see, understand, and protect agricultural and natural systems. My work spans the full sensing stack (hyperspectral, multispectral, LiDAR, and satellite imagery) and the full pipeline from foundational algorithms and foundation models to the low-cost, edge-AI instruments that put those models to work in the field. I apply these tools to soil and plant health, water quality, forest and ecosystem health, invasive species, and land conservation.
The classroom and the lab matter to me just as much: I teach because I believe the objective of education is learning, not teaching, and I measure my success by the students who leave able to build what they once thought impossible.
I build foundational AI and multi-sensor remote sensing, from hyperspectral to satellite, to detect and predict threats to agricultural and natural systems, contributing new algorithms and sensors, not just new applications.
I teach for learning: I build ideas from simple foundations into elegant structures, ground theory in hands-on work, and mentor students into independent, confident learners.
- In my lab I am currently working through questions :
- How can foundation models and compressive sensing make hyperspectral imaging practical from the leaf to the landscape?
- Can low-cost, edge-AI sensors deliver real-time monitoring of crop stress, pollinator health, and water quality in the field?
- What can satellite, spatio-temporal data tell us about soil health, soil carbon, crop yield, and land-cover change?
- How can remote sensing detect and forecast threats to agricultural and natural systems (invasive species, plant disease, and harmful algal blooms)?
- How do we turn AI-driven sensing into explainable, trustworthy decision-support tools that growers and agencies can act on?