CV

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Contact Information

Name Arunkumar Rathinam
Professional Title Research Scientist
Email arunkumar.rathinam@uni.lu

Professional Summary

Research Scientist at SnT, University of Luxembourg, working at the intersection of computer vision and space robotics, with a focus on bridging the gap between simulation and real data for spacecraft pose estimation and autonomous relative navigation.

Experience

  • 2024 - present

    Luxembourg

    Research Scientist
    SnT, University of Luxembourg
    • Leading the DIOSSA project (ESA GSTP), a multi-phase initiative developing deep learning solutions for spacecraft pose estimation.
  • 2021 - 2024

    Luxembourg

    Research Associate
    SnT, University of Luxembourg
    • Technical Lead on industrial partnership with LMO on unsupervised domain adaptation for spacecraft pose estimation.
  • 2019 - 2021

    United Kingdom

    Research Associate
    Surrey Space Centre, University of Surrey
    • Developed deep learning algorithms for 6DoF spacecraft pose estimation under the FAIR-SPACE project.
  • 2011 - 2012

    India

    Product Engineer
    SKF Technologies Limited
  • 2007 - 2011

    India

    Design Engineer
    TATA Consultancy Services (TCS)

Education

  • 2015 - 2019

    Sydney, Australia

    PhD
    University of New South Wales (UNSW Sydney)
    Space Robotics
    • Thesis: Small Body Gravimetry using SLAM-based Autonomous Navigation.
  • 2012 - 2015

    Würzburg, Germany

    M.Sc.
    University of Würzburg
    Space Science and Technology
    • Thesis: Design and development of UWE-4 CubeSat: Integration of electric propulsion, structural analysis, and orbital heating analysis.
  • 2003 - 2007

    Chennai, India

    B.E.
    Anna University
    Mechanical Engineering
    • First Class with Distinction.

Awards

  • 2018
    Winner, Move an Asteroid Technical Paper Competition
    Space Generation Advisory Council (SGAC), Bremen

    Awarded at the Space Generation Congress for outstanding technical contribution.

  • 2017
    IAC Travel Grant / Sponsorship
    National Space Society of Australia

    Awarded to attend the International Astronautical Congress.

  • 2015
    UNSW Departmental PhD Scholarship
    University of New South Wales

    Full tuition coverage plus living stipend for the duration of PhD candidature.

  • 2013
    Erasmus Mobility Grant
    European Commission

    Competitive grant awarded for Master’s exchange year.

  • 2012
    Top Achiever Award
    SKF Technologies Limited

    Ranked 1st in performance assessment during tenure at SKF India.

Skills

Deep Learning (Expert): PyTorch, PyTorch Lightning, TensorFlow, Hydra, OpenCV, NumPy
Robotics & Simulation (Expert): ROS, PANGU (ESA), Unreal Engine 4, Blender
Programming (Expert): Python, C++, MATLAB, Julia
Embedded AI (Advanced): NVIDIA Jetson (Nano / Xavier NX), Arduino, Edge Inference Optimization
Mechanical Engineering (Advanced): Creo, CATIA V5, SolidWorks, NASTRAN, COMSOL
DevOps & Tools (Advanced): Git, Docker, Nginx, Gunicorn

Languages

English : Fluent
Tamil : Native speaker
German : Basic

Projects

  • DIOSSA (ESA GSTP)

    Multi-phase ESA-funded project developing deep learning solutions for spacecraft pose estimation. Program Lead overseeing team of researchers, work package execution, and ESA reviews.

    • Phase 1 (24 months) and Phase 2 (18 months) successfully delivered.
    • Outcomes: 3 ESA reviews passed, 5 conference publications.
  • FAIR-SPACE

    UK Research and Innovation funded project on autonomous space robotics. Developed DL algorithms for 6DoF spacecraft pose estimation and evaluated on edge hardware.

    • Developed ORVIS orbital simulation tool for training data generation.
    • Output: 2 journal publications, 1 book chapter, 2 conference publications.
  • SnT-AI4SPACE Mission

    Deployed an onboard AI anomaly detection system, validated on flight hardware.

  • AUDACITY Mission

    Developed an onboard AI algorithm for SSA spacecraft detection in collaboration with LMO.

  • UWE-4 CubeSat Mission

    Developed mechanical design for electric propulsion integration, verified via structural and orbital thermal analysis.