Mohsen Raoufi | Portfolio

About Me

Hey there!

I am an AI Engineer and Robotics Specialist interested in learning, designing, control, and dynamics of complex systems. I am driven by a simple belief: to truly understand a system, you have to build it yourself. This principle has shaped my decade-long practice of designing, implementing, and deploying intelligent systems, from high-performance controllers and decentralized learning algorithms to embodied robotic collectives. With a background in dynamics, state estimation, and control, I specialize in the full lifecycle of intelligent systems: from mathematical modeling and data-driven simulation to real-world deployment.

These days, I am extending my expertise into AI-driven automation and full-stack development. My focus is on managing the entire development cycle—integrating data science backend logic with functional front-end interfaces and testing frameworks. I have become the person people go to for solving intricate challenges end to end.

Skills

Engineering & Dynamical Systems

State Estimation

Sensor Fusion

Model-Based Design

Robotic Systems Integration

Gazebo

Webots

Embedded Systems

Matlab & Simulink

AI, Learning & Optimization

Optimization Algorithms

Bayesian Methods

Reinforcement Learning

Artificial Neural Networks

TensorFlow

PyTorch

Systems Programming & Interactive Tools

Python

C++

Julia

CUDA

Qt

D3.js

Interactive Dashboards

Data, Modeling & Scientific Computing

Data Analysis & EDA

Statistical Modeling

Agent-Based Modeling

SQL & BigQuery

System-Level Perspectives & Concepts

Collective Intelligence

Multi-Agent Systems

Control Theory

Network Science

Complexity Science

DevOps, Infrastructure & Tooling

Docker

CI/CD

Git & GitHub

Node.js

Hardware- and Software-in-the-loop

Generative AI & Agentic Systems (Learning ...)

Gemini CLI

Claude Code

n8n

RAG

MCP

Selected Projects

2021-2024 • Berlin, Germany • SCIoI

<LARS>: Light Augmented Reality System

Augmented Reality
Human-Robot Interaction
Software Development
Robotics
Collective Systems
C++
Qt
CUDA
Computer Vision
End-to-End System Design
OpenCV
Data Analysis

LARS (Light Augmented Reality System) is a standalone framework engineered to provide seamless interaction between physical collectives and virtual environments. As an end-to-end pipeline, it integrates high-speed detection, real-time tracking, and dynamic projection into a single, cohesive architecture. Built on a robust Model-View-Controller (MVC) pattern, the system enables researchers to bypass complex hardware setups and jump straight into experimentation. The core of LARS lies in its marker-free tracking engine.

2024 • Berlin, Germany • SCIoI

Leveraging Uncertainty in Collective Opinion Dynamics

Network Science
Multi-Agent Systems
Python
Complex Systems

This research introduces a Bayesian framework for opinion dynamics, moving beyond static weights to model dynamic uncertainty in heterogeneous groups. By treating opinions as Gaussian distributions, agents adaptively weigh social influence against their own beliefs. Published in Scientific Reports (Nature), this work reveals how the interaction between network centrality and information quality determines the accuracy and speed of collective consensus.

2025 • Berlin, Germany • SCIoI

Breaking Echo Chambers with Messengers

Agent-Based Modeling
Python
Complex Systems

This research addresses the persistence of echo chambers in social systems. By introducing a novel class of agents—Messengers—governed by stochastic dichotomous noise, we demonstrate how to break metastable polarization. Published in npj Complexity (Nature), this work combines agent-based modeling with statistical physics to identify the critical thresholds for reaching global consensus in fragmented networks.

2025 • Berlin, Germany

TrustMyETA: Routing ETA Uncertainty Quantification

React
TypeScript
Tailwind CSS
Node.js
Monte Carlo Sim
Geospatial Analysis
System Architecture

TrustMyETA is a travel time prediction system that calculates a 'Trust Score' for any given route, providing a probabilistic arrival time range based on risk factors like weather, traffic, incidents, and route geometry. It is currently at a prototype stage.

2011-2015 • K. N. Toosi University of Technology

KN2C: Robotics Team

Robotics
Multi-Agent Systems
C++

The KN2C Small Size League (SSL) project features a group of mobile robots designed for robotic soccer competition. Integrating omnidirectional drive systems, low-latency vision processing, and multi-agent strategy, the system operates in a dynamic environment where robots must execute precise ball handling and tactical plays at high speeds.