Robin Eshraghi

I’m Mohammad Amir, and I go by Robin in daily life!

I’m an Researcher and Engineer with a background in Artificial Intelligence, Robotics, and Electronics. I’m currently interested in intelligent autonomous machines that sense and adapt to advance embodied intelligence in agriculture.

Education

• Ph.D. Student, Agricultural Engineering,

• M.Eng. in Artificial Intelligence
  Oregon State University (OSU), OR, USA | Graduate Research Assistant
  

• M.Sc. in Digital Electronic Systems
  University of Science and Technology (IUST) | First-rank GPA Scholarship
  

• B.E | A.E. in Electronic Engineering
  Technical and Vocational University
  

Experiences

• Graduate Research Assistant, Oregon State University (OSU),
  - Embodied AI Engineer: Dynamic Robotics and Artificial intelligence Lab (DRAIL) | Spot Robot Perception System
  - Computer Vision Engineer: Percision Agriculture Lab | Weed Detection System
  

• Project Intern, Oregon State University (OSU),
  - Robotic Software Engineer: Agricultural Robotics Lab | Path Planning in Harvasting Agricultre Robot UR5
  

• Research Assistant, University of Science and Technology (IUST),
  - Computer Vision Engineer: Machine Vision Lab | AI-based Medical Detection Systems
  

• Research Collaborator, Beheshti University of Medical Science,
  - Computer Vision Software Engineer: Hematology Research Group and Radiology Research Group | AI-based Mobile Application in Medical Challenges
  

Research and Projects

• [2026] Object Grounding in Spot
  • Developed AI modules enabling the Spot to detect, label, and localize household objects in 3D space to build a semantic world map for language-guided navigation.
  • Designed multimodal pipelines, maintain simulation environments, and conduct testing/debugging for milestone-based research progress.
  • Usecase in Agriculture Automations and sensing
  • 
• [2025] Path Planning and Trajectory Generation for Robotic Arm in Apple Harvesting
  • Developed a simulation-based framework for planning and executing collision-free trajectories for a UR5 robotic arm for autonomous apple harvesting.
  • Built RRT/RRT-Connect modules with collision checking, reachability analysis, and visibility constraints. Integrated the full pipeline in ROS and PyBullet with environment setup, kinematics, and testing routines. Enabled smooth trajectory generation for reproducible experiments in agricultural robotic manipulation.
  • Links: [GitHub] [Demo]
    
• [2024-2026] Weed Detection System in Percision Agriculture
  • Developed an object detection system processing high-resolution drone orthomosaics through a custom computer vision pipeline to detect weeds and generate GIS coordinates to support autonomous sprayer tractors to perform targeted herbicide application [GitHub]
    </ul>
  • [2023] Blood Cell Mobile Application
    • Developed a smartphone-based AI system for detection and staging of leukemia from microscopic blood cell images.
    • Links: [Paper] [GitHub] [Dataset]
      
  ## Others:
  • [2021-22] AI-based Covid-19 Diagnosis Systems
    • (1) COV-MobNets framework: Combined lightweight CNN and ViT models for X-ray classification
    • Links: [Paper] [GitHub] [Kaggle]
      
    • (2) Dual-phase CNN-based framework: Modified ResNet and DenseNet models. Utilized image augmentations
    • Links: [Paper] [GitHub] [Data_Kaggle]
      
  • Fun
    • Advanced Line-Following Robot [GitHub]
      
  ## Gallery