Experiences

London, UK
Aug 2021 – Aug 2025

Postgraduate Researcher

Imperial College London

  • Designed and fabricated a flexible sensor system for real-time shape estimation in robot-assisted surgery.
  • Developed machine learning models (FFN, LSTM, GRU) to interpret time-series data from soft sensors.
  • Applied domain adaptation and transfer learning techniques to enable generalization across variable surgical conditions.
  • Built and validated a data acquisition and preprocessing pipeline, including denoising, normalization, and feature extraction.
  • Conducted and analyzed results from multiple experimental trials simulating clinical environments.
  • Engineered a robotic system to classify tissue stiffness using sensor fusion and machine learning.
  • Automated the end-to-end data processing pipeline for model training and evaluation.
  • Deployed recurrent neural networks for accurate classification based on tactile feedback.
  • Designed experiments to collect labeled data and statistically evaluate model performance.
Hong Kong
Feb 2024 – July 2024

Robotics R&D Engineer (Visiting)

Multi-scale Medical Robotics Centre

  • Executed ex vivo and in vivo trials to validate a soft robotic endoscope in clinical settings.
  • Developed real-time hardware-software interfaces for synchronized sensor and imaging data acquisition.
  • Assembled multi-modal datasets (C-arm, MRI, sensor data) to support algorithm development and model training.
  • Collaborated with clinical teams to ensure translational impact and regulatory compliance.
Tehran, Iran
Sep 2017 – Sep 2020

Research Assistant

Amirkabir University of Technology

  • Developed adaptive-sliding mode controllers for nonlinear dynamic systems.
  • Simulated control strategies in MATLAB/Simulink to assess performance under external disturbances.
  • Designed a co-operative manipulation system using soft grippers and real-time vision feedback.
  • Integrated serial communication between MATLAB and Arduino for control loop validation.