Sruti Das Choudhury

Sruti Das Choudhury

  • Contact Information
  • My Story
  • Publications
  • Background
  • Interests
  • Grants
  • Courses Taught

Contact Information

TitleImage Analysis Specialist
Faculty RankResearch Associate Professor
Address724 South Hardin Hall
3310 Holdrege Street
Lincoln NE
68583–0987

East Campus
Phone
  • office: 402-617-0477
E-mails.d.choudhury@unl.edu
VitaeDownload file

 

Contact Preference

Email

Office Hours

Friday 10:00 - 11:00 am

My Story

I am Dr. Sruti Das Choudhury, an image analysis specialist at the rank of Research Associate Professor in the School of Natural Resources with a courtesy appointment in the School of Computing at the University of Nebraska-Lincoln, USA. With a combined expertise in computer vision, plant science, data analytics and visualization, artificial intelligence (AI), and Internet Of Things (IOT), I am committed to advancing the interdisciplinary research sectors of smart agriculture, climate sustainability and plant phenotyping for global food security. I have developed the image analysis tools for the high throughput plant phenotyping facilities at the UNL (https://ard.unl.edu/plant-phenotyping/services-we-provide/nebraska-innovation-campus-greenhouse/), which play a pivotal role in their day-to-day operations. I have gladly taken the initiative to teach AI, compute vision and data analytics to the students of any discipline and backgrounds of our university through hands-on experiences so that they can make the best use of the recent innovations in AI and imaging software packages in their research and practice by introducing a new course (NRES 416/816: Artificial Intelligence, Computer Vision, and Data Analytics for Agriculture and Natural Resources).

I believe that beyond academic accolades, it is the cultivation of diverse real-world skills that makes a life truly worthwhile. My paintings have been exhibited in the Noyes art gallery (downtown Lincoln) in the past, and recently, I showcased my artworks at the 4th telegraph district art show held in August 2025. I love playing piano. I am sports-loving and a solo traveler. I am a member of sailing club of the UNL, and regularly participate in adventure trips organized by the outdoor adventure center and International Student Fellowship (ISF). I participated in several rigorous treks in Himalayan Mountains including Hamta Pass, Har-ki-dun, Panchchulli glacier, etc. My goal is to set foot on all seven continents as a solo traveler—Africa and Antarctica are the last two still remaining.

Feature Stories

Selected Publications

Ivon Acosta Ramirez, Nicole M. Iverson, S. Das Choudhury, Programming-Assisted Imaging of Cellular Nitric Oxide Efflux Gradients and Directionality via Carbon Nanotube Sensors, Small Science, February 2025, doi: https://doi.org/10.1002/smsc.202400493Online
K._Chattopadhyay, D. Bhattacharjee, S. Das Choudhury, An Ensemble Model to Estimate SPAD Values from Rice Leaf Images, 6th International Conference on Frontiers in Computing and Systems, September 2025.
C. K. Tuggle, J. L. Clarke, B. M. Murdoch, E. Lyons, N. M. Scott, B. Beneš, J. D. Campbell, H. Chung, C. L. Daigle, S. D. Choudhury, J. C. M. Dekkers, J. R. R. Dórea, D. S. Ertl, M. Feldman, B. O. Fragomeni, J. E. Fulton, C. R. Guadagno, D. E. Hagen, A. S. Hess, L. M. Kramer, C. J. Lawrence-Dill, A. E. Lipka, T. Lübberstedt, F. M. McCarthy, P. S. Schnable, Current Challenges and Future of Agricultural Genomes to Phenomes in the USA, Genome Biology, 25(8), January 2024. Online
Das Choudhury S, Guadagno CR, Bashyam S, Mazis A, Ewers BE, Samal A and Awada T (2024) Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning. Front. Plant Sci. 15:1353110. doi: 10.3389/fpls.2024.1353110Online
Das Choudhury S, Guadagno CR, Bashyam S, Mazis A, Ewers BE, Samal A and Awada T (2024) Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning. Front. Plant Sci. 15:1353110. doi: 10.3389/fpls.2024.1353110Online
K. J. Bathke, Y. Ge, S. Das Choudhury, J. D. Luck, Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved Precision, 16th International Conference on Precision Agriculture, Manhatton, Kansas, USA, July 2024.
Srivastava, S., Kumar, N., Malakar, A. et al. A Machine Learning-Based Probabilistic Approach for Irrigation Scheduling. Water Resource Management 38, 1639–1653 (2024). https://doi.org/10.1007/s11269-024-03746-7
A. Das, S. D. Choudhury, A. K. Das, A. Samal, T. Awada, EmergeNet: A Novel Deep-Learning based Ensemble Segmentation Model for Emergence Timing Detection of Coleoptile, Frontiers in Plant Science, 14(2023), February 2023.Online
Das Choudhury S, Saha S, Samal A, Mazis A and Awada T (2023) Drought stress prediction and propagation using time series modeling on multimodal plant image sequences. Front. Plant Sci. 14:1003150. doi: 10.3389/fpls.2023.1003150.Online
K. T. Joseph, K. Muvva, H. Mwunguzi, A. Haake, C. Liew, A. Balabantaray, S. Behera, A. Kalra, K. K. Vattiam Srikanth, S. Pitla and S. D. Choudhury, CottonHusker: Deep Learning Enabled Cotton Picking Robot for Smart Agriculture, International Conference on Systems and Technology for Smart Agriculture (ICSTA), Kolkata, India, December 2023.
K. T. Joseph, K. Muvva, H. Mwunguzi, A. Haake, C. Liew, A. Balabantaray, S. Behera, A. Kalra, K. K. Vattiam Srikanth, S. Pitla and S. Das Choudhury, CottonHusker: Deep Learning Enabled Cotton Picking Robot for Smart Agriculture, International Conference on Systems and Technology for Smart Agriculture, Springer Nature Publishing, ISBN: 978-981-97-5156-3 (ICSTA), Kolkata, India, December 2023.
R. Quiñones, F. Munoz-Arriola, S. D. Choudhury, A. Samal, OSC-CO2: Coattention and Cosegmentation Framework for Plant State Change with Multiple Features, Frontiers in Plant Science, 14: doi: 10.3389/fpls.2023.1211409, October 2023. Online
S. D. Choudhury, C. Rosaria Guadagno,, University of Nebraska-Lincoln and University of Wyoming AutoFluorescence Dataset (UNL-UW-AFD) to facilitate stress detection and phenotype computation, and also identify genetic variation within Brassica rapa types under drought using autofluorescence imaging. https://plantvision.unl.edu/datasetOnline
Choudhury, S. D., Guha, S., Das, A., Das, A. K., Samal, A. K., Awada, T. N. (2022). FlowerPhenoNet: Automated Flower Detection from Multi-View Image Sequences Using Deep Neural Networks for Temporal Plant Phenotyping Analysis. REMOTE SENSING, 14(24).Online
Fan, X., Zhou, R., Tjahjadi, T., Das Choudhury, S., Ye, Q. (2022). A Segmentation-Guided Deep Learning Framework for Leaf Counting. Frontiers in Plant Science. Online
Bashyam, S., Choudhury, S. D., Samal, A. K., Awada, T. N. (2021). Visual Growth Tracking for Automated Leaf Stage Monitoring Based on Image Sequence Analysis. REMOTE SENSING, 13(5).Online
Quiñones, R., Munoz-Arriola, F., Das Choudhury, S., Samal, A. (2021). Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping. PLOS ONE, 16(9), 21. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257001Online
Zhou, L., Fan, X., Tjahjadi, T., Das Choudhury, S. (2021). Discriminative attention-augmented feature learning for facial expression recognition in the wild. Neural Computing and Applications. 34: 925–936.
A. Samal, S. Das Choudhury, T. Awada (2020) Image-based plant phenotyping: Opportunities and challenges, Intelligent Image Analysis for Plant Phenotyping, CRC Press, Taylor and Francis Group, pp. 3-23.
J. D. Jarquin, R. Howard, A. Xavier, S. Das Choudhury (2020) Predicting yield by modelling interactions between canopy coverage image data, genotypic and environmental information for soybeans, "Intelligent Image Analysis for Plant Phenotyping", CRC Press, Taylor and Francis Group, pp. 267-286.
S. Das Choudhury (2020) Segmentation techniques and challenges in plant phenotyping, Intelligent Image Analysis for Plant Phenotyping, CRC Press, Taylor and Francis Group, pp. 69-91.
S. Das Choudhury, A. Samal, (2020) Structural high-throughput plant phenotyping based on image sequence analysis, Intelligent Image Analysis for Plant Phenotyping, CRC Press, Taylor and Francis Group, pp. 93-117.
S. Das Choudhury, S. Goswami, A. Chakrabarti. (2020) Time series and Eigen value based analysis of plant phenotypes, Intelligent Image Analysis for Plant Phenotyping, CRC Press, Taylor and Francis Group, pp. 155-173.
S. Das Choudhury, Time Series Modeling for Bridging Phenotype-Genotype Gap and Phenotypic Prediction using Neural Networks, European Conference on Computer Vision Workshop on Computer Vision Problems in Plant Phenotyping (CVPPP), Glasgow, UK, August 2020.
Das Choudhury, D., Samal, A., and Awada, T. 2019. Leveraging Image Analysis for High-Throughput Plant Phenotyping. Frontiers in Plant Science. doi: 10.3389/fpls.2019.00508 Online
A. Paul, S. Ghosh, A. K. Das, S. Goswami, S. Das Choudhury, S. Sen, A review on agricultural advancement based on computer vision and machine learning, Emerging Technology in Modelling and Graphics: Proceedings of IEM Graph, 2018.
Das Choudhury, S., Bashyam, S., Qui, Y., Samal, A., Awada, T. (2018). Holistic and Component Plant Phenotyping using Temporal Image Sequence. Holistic and Component Plant Phenotyping using Temporal Image Sequence, Plant Methods. 14(35).Online
Das Choudhury, S., Bashyan, S., Qiu, Y., Samal, A. K., Awada, T. N. (2018). Holistic & component plant phenotyping using temporal image sequence. Holistic & component plant phenotyping using temporal image sequence, 14, 35.
Fan, X., Ye, Q., Yang, X., Das Choudhury, S. (2018). Robust Blood Pressure Estimation using a RGB Camera. Robust Blood Pressure Estimation using a RGB Camera.
Jarquin, D., Howard, R., Xavier, A., Das Choudhury, S. (2018). Increasing Predictive Ability by Modeling Interactions between Environments. Increasing Predictive Ability by Modeling Interactions between Environments, 8(4).
S. Das Choudhury, S. Goswami, S. Bashyam, A. Samal, T. Awada, Automated Stem Angle Determination for Temporal Plant Phenotyping Analysis, ICCV workshop on Computer Vision Problems in Plant Phenotyping (CVPPP), pp. 2022-2029, Venice, Italy, October 2017.
S. Das Choudhury, V. Stoerger, A. Samal, J. Schanable, Z. Liang, J-G Yu, Automated Vegetative Stage Phenotyping Analysis of Maize Plants using Visible Light Images, KDD workshop on Data Science for Food, Energy and Water (DS-FEW), San Francisco, California, USA, August 2016.
S. D. Choudhury, T. Tjahjadi, 2014. Robust View-Invariant Multiscale Gait Recognition, Pattern Recognition, 48: 798 - 811.Online
S. Das Choudhury, Y. Guan, C.-T. Li, Gait Recognition using Low Spatial and Temporal Resolution Videos, International Workshop on Biometrics and Forensics (IWBF), pp. 1-6, Valletta, Malta, March 2014.
S. D. Choudhury, T. Tjahjadi, 2013. Gait Recognition Based on Shape and Motion Analysis of Silhouette Contour, Computer Vision and Image Understanding, 117: 1770-1785.Online
Y. Guan, C.-T. Li, S. Das Choudhury, Robust Gait Recognition from Extremely Low Frame-Rate Videos, International Workshop on Biometrics and Forensics (IWBF), pp. 1-4, Lisbon, Portugal, April 2013.

Background

Education

DegreeMajorInstitutionYear Awarded
Doctorate of PhilosophyComptuer Science EngineeringUniversity of Warwick, United Kingdom2013
Master of ScienceComptuer Science and ApplicationUniversity of Calcutta, India2009
Bachelor of ScienceInformation TechnologyWest Bengal University of Technology, India2005

 

Awards

TitleAwarded byYear Awarded
Faculty Inclusive Excellence (Holling Family Teaching Excellence Awards)College of Agricultural and Natural Resources | UNL2024
Honorable mention, Outstanding Postdoctoral ScholarUniversity of Nebraska-Lincoln, USA2017
Postdoctoral Research AssociateDepartment of Computer Science and Engineering, UNL2016
IPPN Travel Grant4th International Plant Phenotyping Symposium2016
KDD-DSFEW Travel AwardKDD Data Science for Food Energy and Water Workshop2016
AusPheno2016 Travel Award5th International Controlled Environment Conference2016
Early Career Research FellowshipInstitute of Advanced Study, University of Warwick2014

 

Websites

 

SNR Program Areas

  • Environmental Science

Areas of Interest/Expertise

  • Computer vision
  • Artificial Intelligence
  • Data analytics and data visualization
  • Data storytelling
  • High-throughput plant phenotyping
  • Behavioral biometrics

Grants

Currently this page only displays grants that were awarded on 1/1/ 2009 to the present. If a grant was awarded prior to 1/1/ 2009 and is still active, it will not be displayed on this page.

Grant TitleEvent-Based Plant Phenotyping using Deep Learning, Algorithms, Tools and Datasets
Starting Date06/07/2022

Investigator(s)

Ending Date01/31/2023
Funding Level$50,000.00
Funding AgencyIowa State University

 

Grant Title3-D image-based Plant Phenotyping
Starting Date10/01/2017

Investigator(s)

Ending Date09/30/2018
Funding Level$5,000.00
Funding AgencyIowa State University

 

Courses Taught

Course NumberCourse TitleFall Even YearsFall Odd YearsSpring Even YearsSpring Odd YearsSummer SessionCross Listing
NRES 416/816Artificial Intelligence Tools for Agricultural Image AnalysisXX
NRES 498/898Computer Vision and Artificial Intelligence Challenges in AgricultureXX