ABOUT ME

My name is Abdelhakim Amer. I am a researcher in optimal control in robotics.

Currently, I am conducting my Ph.D. research on learning-based optimal control applied to underwater robotics. More specifically, I am working on combining stochastic learning techniques like Gaussian process with model predictive control to improve performance and safety. I'm fortunate to be conducting my Ph.D. research with Aarhus University and EIVA A/S, a renowned industry leader in the field.

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Skills

Optimization Control Theory Stochastic Machine Learning Software Developement Research

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Download My Resume

Education

  • Bachelor in Mechanical Engineering - The American University in Cairo (2013-2018)
  • MSc. in Mechanical Engineering - TU Delft (2018-2021)
  • PhD in Robotics - Aarhus University (2022-Now)
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Academics

Research Areas

Stochastic Machine Learning

Stochastic Machine Learning

Gaussian process regression for system identification and model learning.

Model Predictive Control

Optimal Control

Model predictive control (MPC) for safe and optimal trajectory generation.

Model Predictive Control

Simulation

Underwater robotics simulator for autonomous navigation and control.

Graduate teaching assistant

Control Theory

Autonomous Mobile Robots

MY PROJECTS

  • All
  • Control and Path Planning
  • System Identification
  • Computer Vision
  • Bio-Inspired Design
  • Supervision
VTNMPC Project

VTNMPC Project

Description of the VTNMPC Project.

Seavis Towed ROV

Seavis Towed ROV

Description of the Seavis Towed ROV project.

Drone Building Project

Drone Building Project

Description of the Drone Building Project.

MY PUBLICATIONS

Abdelhakim Amer, Mohit Mehndiratta, Jonas le Fevre Sejersen, Huy Xuan Pham, and Erdal Kayacan. "Visual Tracking Nonlinear Model Predictive Control Method for Autonomous Wind Turbine Inspection." In 2023 21st International Conference on Advanced Robotics (ICAR), pp. 431-438. IEEE, 2023.
Abdelhakim Amer, Olaya Álvarez-Tuñón, Halil İbrahim Uğurlu, Jonas Le Fevre Sejersen, Yury Brodskiy, and Erdal Kayacan. "UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-generation Framework." In 2023 21st International Conference on Advanced Robotics (ICAR), pp. 570-576. IEEE, 2023.
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CONTACT ME

Aarhus Universitet, Bygning 5125 (Edison), Finlandsgade 22, 8200 Aarhus

abdelhakim@ece.au.dk