Mohammad Rahmani

E-mail	mohammad.rahmani.xyz@gmail.com
Tel	+43 677 63676105
Location	Austria
Links	Website Github Linkedin X

Summary

Multi robot systems, ROS, AI and Swarm intelligence, Data science, machine learning and
computer vision, Sensor data fusion, statistical inference. Software engineering.

Skills

• Programming & Frameworks: C++, Python, ROS, MAVROS, Gazebo, CTU-MRS framework
• UAV Systems & Middleware: MAVLink, QGroundControl (QGC), PX4, ArduPilot
• Probabilistic State Estimation: Dynamic Bayesian Networks (DBN), Kalman Filters, Particle Filters, Bayesian filtering
• Computer Vision & Perception: Visual SLAM, Visual Odometry, Sensor Fusion (LiDAR, GPS, IMU, camera)
• Machine Learning: Autoencoders for dimensionality reduction, sequential modeling for novelty detection
• Simulation & Testing: UAV simulation in ROS/Gazebo, leader–follower and confined-space scenarios, unit testing (pytest, CI/CD)
• Embedded & Real-Time Systems: UAV autopilot integration, embedded programming for sensor fusion and navigation
• Collaboration & Development: Git, Agile workflows, continuous integration, documentation in LaTeX

Languages

English: IELTS 7.5, German: B2.1, French: C1, Persian: Native

Education

PhD and Senior scientist candidate — Networked and Embedded Systems

Klagenfurt University, Austria

Research topic: “Self-awareness in multi-robot systems”. Developing an artificially intelligent framework
using which multiple robots learn incrementally how to accomplish a task by building models from sensory
data such as LIDAR and GPS sensors.

Masters’ — Computer Science

Amirkabir University of Technology, 2013-2015

Modules included: Machine learning, Clustering, Image processing, Data Mining, Logic programming,
Computer Science Theory, Theory of Computer Systems. Average Score: 17/20

Projects during master’s:

• Modeling Time Series By Means of Fuzzy Inference Systems, Advisor Prof. Dr. Adel Mohammadpour
• Tour Recommender System By Means of a Naive Bayes Classifier Driven Model, Advisor Prof. Dr. Adel Mohammadpour
• Trajectory Recommender System By Means of Multiple Linear Regression, Advisor Prof. Dr. Mehdi Ghatee
• Tour Driver Recommender System By Means of Decision Trees and Naive Bayes Classifier, Advisor Prof. Dr. Mohammad Ebrahim Shiri Ahmad Abady
• N-Queens Puzzle in Prolog Programming Language, Advisor Prof. Dr. Mohammad Ebrahim Shiri Ahmad Abady

Bachelors’ — Applied Mathematics in Computer Science

Payam-e Noor University of Shiraz, 2001-2005

Modules included: Algebra, Linear Algebra, Discrete Mathematics, Graph Theory, Mathematical Analysis,
Statistics and Probability, Programming Concepts, Data structures, Data storage and Retrieval,
Numerical Analysis, Operations Research, Differential Equations, Stochastic Processes, Complex Functions,
Time Series. Average Score: 16/20

Final Project: Complex Matrices and their applications. Supervisor Shams-al Moluk Khoshdel

Professional Experience

Advanced AI researcher and engineer

Graz university, Austria — 2025-…

Develop multiple AI models to extract, classify and generate inference and provide visual interpretations.
Tasks involve expertise from computer vision to work with different sensory data.

Senior data and sensor scientist

Klagenfurt university, Austria — 2020-…

Developed a framework that builds temporal models from multiple sensory data derived from multiple UAVs.
First used dynamic Bayesian networks to build temporal models for LIDAR and GPS sensory data mounted on two UAVs.
Then used deep learning tools such as LSTMs and CNNs and GANs. Used ROS and GAZEBO for simulation.

Senior data scientist and sensor scientist

Lumetry diagnostic GMBH, Austria — 2024-…

Developed deep and classical machine learning tools to diagnose Chronic Obstructive Pulmonary Disease (COPD)
and blood CO2 estimation with classification and regression methods using data derived from CO2 and flow sensors.
Suggested solutions achieved 98% for classification and 92% for regression.

Senior data scientist

Mavoco IoT GMBH, Austria — 2023-2024

Developed deep learning methods for automatic configuration of IoT tools using natural language.
Converted customer natural language input into suggested configurations. 98% of recommended configurations
matched users’ expectations.

Robotics researcher

Rovira i Virgili university, Spain — 2017-2020

Worked on EU Horizon 2020 project called GABLE. Used deep learning models for action prediction of disabled people
to control computer games and developed tools to automatically adjust game settings according to disability level
(e.g., object speed). Worked with Pepper robot (SoftBank): developed a machine vision tool to recognise actions
(e.g., waving) and wave back to motivate disabled people to perform physical exercises.

Projects:

• Rehabibotics: using humanoid robots to convey rehabilitation therapies to Disabled People
• Enhancing Robot Therapy with Emotion Awareness for Kids with Developmental Disorders in Clinical Settings

Noon Dreams company

Iran — 2006-2016

Founded this company and developed AI tools including:

• A content management system recommending product pages using navigation history and user similarity.
• A project management framework learning and suggesting relevant tasks; automated the process of reserving a tour
  as a project (flight/hotel booking, tour guides/drivers, itineraries), with ML-based recommendations.
• A system compiling energy consumption of building units and performing data analysis and visual graphs; applied
  and modified data mining and ML to discover inconsistencies in provided data.
• Simulation of road ramps traffic using C++ programmed DLLs for VISSIM software.

Datis Data Publishing (Shiraz University)

Iran — 2006-2008

• Development of educational games in which consciousness, attention and other cognitive factors of players were
  measured and stored in a database for analysis.
• An educational software for mining into human organs using 3D images.

Publications

1. M. Rahmani, B. Rinner, Anomaly detection in multi-robot systems exploiting self-awareness, 2023, International Conference on Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications, Athens, Greece
2. M. Rahmani, B. Rinner, Towards Self-Awareness in Multi-Robot Systems, 2022, Austrian Robotics Workshop, Villach Austria
3. Instant Measurement of the Difficulty Level of Exergames with Simple Uni-Dimensional Level Goals for Cerebral Palsy Players. Conference: JCSG2018 – Joint Conference on Serious Games. Darmstadt, Germany