Academic & Research Experience:

Assistant Professor, Department of Bioproducts and Biosystems Engineering, University of Minnesota Twin Cities
St. Paul, MN
Aug 2026 - Present

  • Lead an interdisciplinary research program focused on Data Science in Agricultural and Ecosystem Sustainability.
  • Develop and apply artificial intelligence, machine learning, advanced sensing, and data analytics to challenges in sustainable agriculture, environmental systems, bioenergy, and natural-resource management.
  • Investigate multimodal sensing, hyperspectral and spectroscopic data analytics, trustworthy and uncertainty-aware AI, and intelligent decision-support systems for agricultural and ecosystem applications.
  • Develop data-driven approaches for precision agriculture, sustainable bioresource utilization, food security, environmental monitoring, and resource recovery.
  • Teach and mentor undergraduate and graduate students while building collaborations across engineering, agriculture, environmental science, and data science.

 

Postdoctoral Associate, Department of Analytical Chemistry and Characterization, Idaho National Laboratory
Idaho Falls, ID 
May 2024 – Aug 2026

  • Conducted interdisciplinary research integrating artificial intelligence, machine learning, hyperspectral imaging, near-infrared spectroscopy, and advanced sensing for energy, agricultural, and environmental applications.
  • Developed AI-assisted approaches for biomass characterization and sorting to support improved utilization of biomass resources for bioenergy and bioproduct applications.
  • Contributed to the development of AI-enhanced hyperspectral sensing and sorting platforms for rapid material characterization and intelligent decision-making.
  • Investigated sensing and data-driven approaches for the identification of rare earth elements and critical materials in complex waste streams.
  • Applied machine learning and advanced sensing techniques to problems related to food safety, food security, sustainable agriculture, and resource recovery.
  • Collaborated with multidisciplinary teams across national laboratories, universities, government programs, and industry.

 

Industry & Applied Research Experience:

Statistical Scientist Intern, Bayer Crop Science R&D, Chesterfield, Missouri
Feb 2023 - Jun 2023

  • Applied advanced statistical learning and machine-learning methods to characterize soil environments and identify factors associated with crop productivity.
  • Developed clustering frameworks using Gaussian Mixture Models, spectral clustering, BIRCH, and K-means to identify high-performing soil-environment groups.
  • Applied dimensionality-reduction and feature-selection techniques to determine key environmental and soil variables affecting crop yield.
  • Evaluated interactions between soil environments, agricultural treatments, and crop performance using statistical and machine-learning models.
  • Identified characteristics associated with underperforming environments and provided data-driven recommendations for future experimental and agronomic strategies.

 

Research Intern, Texas A&M AgriLife Research and Extension Center, Corpus Christi, Texas
May 2022 – Aug 2022

  • Developed machine-learning and time-series approaches for analyzing multi-year agricultural datasets with discontinuous and non-stationary observations.
  • Created data-integration methods using clustering and Dynamic Time Warping to harmonize crop-growth measurements collected across cultivation seasons of different durations.
  • Developed deep-learning models for predicting in-season crop growth indicators, including canopy cover, canopy height, and Excess Green Index.
  • Evaluated architectures including LSTM, bidirectional LSTM, CNN-LSTM, ConvLSTM, and encoder-decoder models for agricultural forecasting.
  • Developed statistical time-series models for forecasting crop-development characteristics throughout the growing season.
  • Applied machine-learning approaches to crop-yield prediction for cotton, wheat, and forage systems.

Teaching Experience:

Graduate Assistant Lecturer & Teaching Assistant, Senior Capstone Design – ECEN 403/404, Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas
Aug 2019 - Aug 2024

  • Served in instructional roles across 10 semesters of senior engineering capstone design.
  • Mentored multidisciplinary student teams developing engineering systems involving embedded systems, microcontroller programming, PCB design, databases, predictive analytics, web development, and application development.
  • Guided students through the complete engineering design process, from problem formulation and system architecture to prototyping, debugging, integration, validation, and final demonstration.
  • Provided technical guidance for hardware, software, and data-analysis components and helped teams troubleshoot subsystem and system-level integration challenges.
  • Supported the development of students' engineering design, technical communication, teamwork, and project-management skills.

Earlier Professional Experience:

Data Scientist, ABCO Digital, Bhubaneswar, India
Jun 2016 - Jul 2017

  • Analyzed large datasets from television and broadband service providers to identify customer patterns and similarity relationships using statistical and clustering techniques.
  • Developed data visualizations, including three-dimensional density and contour analyses, to interpret complex customer and operational datasets.
  • Integrated technical data analysis with business and financial considerations to support operational decision-making.
  • Worked with digital-media and communications workflows involving satellite communications, video transcoding, data processing, and encryption technologies.