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MSUWOOD AIMississippi State University

Mississippi State University · Department of Sustainable Bioproducts

MSU Wood AI

Artificial Intelligence for Wood & Bioproducts

A research laboratory at Mississippi State University

Department of Sustainable Bioproducts

We partner with researchers and industry to turn wood and materials data into practical AI tools for classification, inspection, measurement, and decision support.

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Computer vision
Classification & detection
Wood & bioproducts
Materials intelligence
Industry partnerships
Applied research
Wood cross-section with visible growth rings used for computer-vision research
Wood science · Computer vision

Turning wood imagery into measurable data

Applied research in classification, assessment, and automated analysis

University affiliation

A research laboratory at Mississippi State University

MSU Wood AI is a research laboratory at Mississippi State University within the Department of Sustainable Bioproducts.

Mississippi State University Department of Sustainable Bioproducts

Products

AI models people can explore and try

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Image classificationAvailable to try

SYP–RO Image Classifier

Classify an uploaded image as RO or SYP.

This research prototype analyzes one image at a time and returns the model’s predicted class and confidence scores. Its output is experimental and should be interpreted alongside domain expertise.

Capabilities

  • RO/SYP classification
  • Image upload
  • Confidence scores
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Veneer gradingAvailable to try

Developing deep learning models to grade guitar veneer

Grade an uploaded guitar veneer image as 2A, 3A, or 4A.

This research prototype analyzes one guitar veneer image at a time and returns a predicted grade with scores for 2A, 3A, and 4A. Its output is experimental and should be interpreted alongside domain expertise.

Capabilities

  • 2A/3A/4A classification
  • Image upload
  • Confidence scores
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Moisture estimationAvailable to try

Wood Chip Moisture Content Estimator

Estimate wood-chip moisture content from one uploaded image.

This research prototype analyzes a wood-chip image and returns a predicted moisture content percentage. Its output is an experimental model estimate, not a laboratory measurement.

Capabilities

  • Image-based regression
  • Moisture percentage estimate
  • Image upload
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Research directions

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Featured work

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Selected publications

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A selection of recent publications by Dr. Jason Tyler Street.

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journal

Formation mechanism of few-layer graphene adjacent to nanoscale zero-valent copper nanoparticles synthesized using kraft lignin as a sustainable aromatic-rich carbon resource

Guo, S., Yan, Q., Kim, Y., Mlsna, T. E., Street, J. T., Cai, Z., Zhang, J.

Journal of Materials Chemistry A

2026

journal

MoistViT: A vision transformer model for moisture content prediction of wood chips

Marulanda, D. E., Rahman, A., Street, J. T., Marufuzzaman, M., Wang, H., Gude, V. G., Buchanan, R.

Systems and Soft Computing

2026

journal

Explainable artificial intelligence (AI)–based regression models for predicting moisture content in wood chips through transfer learning

Neupane, T., Street, J. T., Wang, H., Rahman, A., Marufuzzaman, M.

Biomass Futures

2026

People

A collaborative research community

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Dr. Jason Tyler Street, Interim Head · Associate Professor

Dr. Jason Tyler Street

Interim Head · Associate Professor

Dr. Street leads MSU Wood AI and serves as Interim Head and Associate Professor in Mississippi State University’s Department of Sustainable Bioproducts. His work spans sustainable materials, engineered wood products, artificial intelligence, transport modeling, and renewable energy systems.

  • Bio-based composites and engineered wood products
  • AI and machine learning in materials research
  • Moisture and thermal transport modeling
  • Renewable and alternative energy systems

Education

  • Ph.D. in Engineering, Mississippi State University
  • M.S. in Biological Engineering, Mississippi State University
  • B.S. in Biological Engineering, Mississippi State University
Email 662-325-5120 Room 5204, Forest Products Laboratory
Official MSU profile
Tilak Neupane, Graduate Research Assistant · PhD in Sustainable Bioproducts

Tilak Neupane

Graduate Research Assistant · PhD in Sustainable Bioproducts

Tilak Neupane is a final-year PhD student in the Department of Sustainable Bioproducts. His research applies machine learning and deep learning to assess wood properties, including wood chip moisture content and the mechanical properties of tree logs. He earned an MS in Forestry from the University of Georgia.

  • Artificial intelligence and computer vision for wood quality assessment
  • Moisture content prediction
  • Hyperspectral imaging
  • Nondestructive evaluation
Email
Profile photo placeholder for Benjamin Wiley

Benjamin Wiley

Graduate Research Assistant · M.S. in Sustainable Bioproducts and MBA

Benjamin Wiley is a graduate research assistant and dual M.S. in Sustainable Bioproducts and MBA candidate at Mississippi State University. His work examines biomass residuals for alternative-energy systems and develops machine-learning and computer-vision models to estimate biomass strength, appearance, and composition.

  • Machine learning and computer vision for biomass
  • Biomass residual utilization
  • Alternative energy systems
  • Life-cycle assessment
Email
LinkedIn
Profile photo placeholder for Madeline Gnann

Madeline Gnann

Graduate Research Assistant · M.S. in Sustainable Bioproducts

Madeline Gnann is a graduate research assistant pursuing an M.S. in Sustainable Bioproducts after earning her B.S. in Sustainable Bioproducts at Mississippi State University. Her laboratory experience includes chemical analysis and wood identification.

  • Sustainable bioproducts
  • Wood identification
  • Chemical laboratory methods
LinkedIn

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