Dr. Sudip Kunwar
Langston University

Sudip Kunwar, Ph.D.

Assistant Professor · Biosystem Engineering & Precision Agriculture

Advancing sustainable farming through UAV remote sensing, AI-driven phenotyping, and genomic prediction.

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About Me

I am an Assistant Professor of Precision Agriculture at Langston University, where my research leverages UAVs, advanced sensors, and artificial intelligence to design scalable phenotyping platforms.

With over 7 years of experience in phenotypic analysis, remote sensing, genomic selection, and multi-omic predictive breeding strategies, I bring expertise in advanced statistical analysis, R and Python programming, and quantitative genetics.

My commitment is to advance agricultural technology through innovative tools that accelerate crop genetic improvement and strengthen agricultural resilience.

Research Focus Areas

Precision Agriculture Remote Sensing High-Throughput Phenotyping Quantitative Genetics Predictive Breeding Machine Learning / AI Hyperspectral Imaging Genomic Selection GWAS Crop Resilience Improvement
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Education & Experience
Aug 2021–
Aug 2025
Ph.D.

Ph.D. in Plant Breeding

University of Florida, Gainesville, FL

Specialization: Phenomics & Quantitative Genetics · Advisor: Dr. Ali Babar

Jan 2019–
May 2021
M.S.

M.S. in Horticultural Sciences

University of Florida, Gainesville, FL

Specialization: Phenotyping & Plant Physiology · Advisor: Dr. Ute Albrecht

Apr 2013–
Dec 2017
B.Sc.

B.Sc. Agriculture

Agriculture and Forestry University, Chitwan, Nepal

Aug 2025–
Present
Current

Assistant Professor

Langston University – School of Agriculture & Applied Sciences

Biosystem Engineering & Precision Agriculture

  • Apply UAV-based & proximal sensors, machine vision, and AI to advance phenotyping
  • Develop precision agriculture tools to optimize agricultural inputs
  • Lead research & teaching integrating cutting-edge remote sensing technology
Aug 2021–
Aug 2025
Ph.D.

Graduate Research Assistant

University of Florida – World Food Crop Breeding & Genetics Lab

PI: Dr. Ali Babar

  • Enhanced genomic prediction models for complex agronomic traits
  • Designed & executed wheat and oat breeding trials and selections
  • Operated UAV flights integrating hyperspectral sensors and genomic data
Jan 2019–
Aug 2021
M.S.

Graduate Research Assistant

University of Florida – Plant Physiology Lab

PI: Dr. Ute Albrecht

  • Evaluated citrus rootstock breeding trials for horticultural attributes
  • Collaborated on precision agriculture projects using UAV & machine learning
  • Conducted greenhouse research and molecular physiology experiments
Mar–Jul
2018
Analyst

Agri-Market Analyst

Prime Minister Agriculture Modernization Project, Nepal

Sweet Orange Super-zone, Sindhuli · Analyzed market data; published "Superzone Profile" booklet.

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Publications

Deciphering the genetic basis of yield components in wheat by integrating hyperspectral-based phenomes

Kunwar S., Babar MA., Ampatzidis Y., Khan N., et al.

Plant Phenomics 8(3), 100235 (2026)

Genomic prediction for stem rust resistance in the southern United States elite oat (Avena sativa) germplasm

Acharya JP., Khan N., Kunwar S., et al.

Frontiers in Plant Science 17, 1795871 (2026)

Uncovering the genetic architecture of biomass yield and related traits in Southern US oat germplasm using genome-wide association study

Adewale S., Babar MA., Khan N., Acharya JP., McBreen J., Raza I., Kunwar S., et al.

Theoretical and Applied Genetics 139(6), 168 (2026)

Optimizing biomass partitioning in wheat using UAV-based hyperspectral phenomic and genomic prediction

Kunwar S., Babar MA., Jarquin D., Ampatzidis Y., et al.

Frontiers in Plant Science 17, 1740337 (2026)

Effectiveness of low-density high-throughput marker platform and easy-to-measure traits for genomic prediction of biomass yield in oat (Avena sativa L.)

Adewale S., Babar MA., Jarquin D., Khan N., Acharya JP., Kunwar S., et al.

The Plant Genome 19(1), e70179 (2026)

Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi-kernel genomic prediction models

Kunwar S., Babar MA., Jarquin D., Ampatzidis Y., et al.

The Plant Genome 18(2), e70052 (2025)

Leveraging Multi-Omics Data with Machine Learning to Predict Grain Yield in Small vs. Big Plot Wheat Trials

McBreen J., Babar MA., Jarquin D., Ampatzidis Y., Khan N., Kunwar S., et al.

Agronomy 15(6), 1315 (2025)

Field performance of 'Valencia' orange trees on diploid and tetraploid rootstocks in HLB-endemic conditions

Kunwar S., Meyering B., Grosser J., Gmitter F.G., Castle W.S., Albrecht U.

Scientia Horticulturae 309, 111635 (2023)

Determining leaf nutrient concentrations in citrus trees using UAV imagery and machine learning

Costa L., Kunwar S., Ampatzidis Y., Albrecht U.

Precision Agriculture 23(3), 854–875 (2022)

Crop diversification for improved weed management: A review

Sharma G., Shrestha S., Kunwar S., Tseng TM.

Agriculture 11(5), 461 (2021)

Field performance of 'Hamlin' orange trees grown on various rootstocks in huanglongbing-endemic conditions

Kunwar S., Grosser J., Gmitter FG., Castle WS., Albrecht U.

HortScience 56(2), 244–253 (2021)

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Awards & Scholarships

2024

Gerald O. Mott Award

Crop Science Society of America

2024

Bayer B4U Mentorship Program

Selected for Bayer University Mentorship Program

2023–25

William C. & Bertha M. Cornett Fellowship

UF/IFAS College of Agricultural and Life Sciences

2023–24

NAPB Borlaug Scholarship

National Association of Plant Breeders

2024

First Place – Oral Presentation

8th Annual Plant Breeding Retreat, University of Florida

2024

First Place – Poster Competition

8th Annual Plant Science Symposium, UF

2024

Dr. Elaine Turner Plant Breeding Scholarship

University of Florida

2024

Plant Breeding Top-up Award

University of Florida

2023

Travel Grant – CSSA

Western Society of Crop Science, Hawaii

2022

Travel Scholarship

Society of Organic Seed Professionals, West Virginia

2022

Student Speaker Award

Plant Science Council Symposium, UF

2021

Second Place – Best Student Paper

Florida State Horticultural Society

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Scientific Presentations

Invited talks & conference presentations

Deciphering the genomic regions influencing the hyperspectral-based phenome correlated with yield associated traits in wheat

UF Plant Breeding Retreat 2025

📍 Daytona, FL

Enhancing wheat yield potential: integrating genomic and phenomic approaches for biomass partitioning optimization

3rd International Wheat Congress 2024

📍 Perth, Australia

Integrating remote sensing with genomics to enhance agronomic trait prediction in wheat

UF Plant Breeding Retreat 2024

📍 Daytona, FL

Integrating remote sensing data for phenomic and genomic prediction of agronomic traits in wheat

UF Plant Science Symposium 2024

📍 Gainesville, FL

Optimizing genomic prediction models to predict HI, yield, and biomass partitioning traits in wheat

LSU Plant Science Symposium 2023

📍 Baton Rouge, LA

Determining yield, harvest index, and biomass partitioning traits using UAV-based hyperspectral sensor and machine learning

Western Crop Science Society (WCSSA) Annual Meeting 2023

📍 Honolulu, Hawaii

Potential use of UAV-based remote sensing tools for indirect assessment of harvest index and biomass partitioning traits

AI Conference 2023

📍 Orlando, FL

Estimation of harvest index and biomass partitioning traits using UAV-based remote sensing and genomics

Student Organic Seed Symposium 2022

📍 Morgantown, WV

Evaluating citrus rootstocks for high-density plantings in HLB-endemic conditions

ASHS Annual Conference 2021

📍 Denver, CO

Field performances of 'Hamlin' orange trees on diploid and tetraploid rootstocks in HLB-endemic conditions

Florida State Horticultural Society (FSHS) Annual Meeting 2020

📍 Florida

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Technical Skills

Programming & Data Analysis

RPython Statistical ModelingGenomic AnalysisGIS / QGIS

Machine Learning & AI

Deep LearningRandom Forest / XGBoost Multi-Kernel ModelsRRBLUP / GBLUPBayesian Methods

Remote Sensing & UAV

UAV Operation (FAA Part 107)Hyperspectral Imaging Multispectral SensorsAgisoft Metashape Pix4DQGISENVI / Spectral Analysis

Plant Science & Breeding

Quantitative GeneticsGWAS Genomic SelectionField Trial Design Phenotyping PipelinesMolecular Markers
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Contact
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Phone

(405) 466-3220

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Office

100 Success Ave., Holloway Bldg.
Langston, OK 73050