M.Sc. Researcher in Mechatronics & AI

Mehdi Sadeghian

Autonomous Systems & Deep Reinforcement Learning Researcher

I am a graduate researcher with a strong background in Mechatronics and Control Theory. My research focuses on developing intelligent, safety-aware decision-making algorithms for autonomous vehicle navigation, multi-agent trajectory forecasting, and deep generative computer vision in dynamic urban environments.

TMU Logo
IUT Logo
Research Profile
M.Sc. in Mechatronics Engineering Tarbiat Modares University • 2024 – Present
B.Sc. in Electrical Engineering (Control) Isfahan University of Technology • 2018 – 2023
Core Research Focus
Safe Autonomous Navigation & Control
Hybrid Reinforcement & Imitation Learning
Multi-Agent Trajectory Forecasting
Computer Vision (ViTs & YOLOv11)

Academic Background

Formal academic training in Mechatronics Engineering, Control Theory, and Machine Learning.

Tarbiat Modares University Logo

M.Sc. in Mechatronics Engineering

2024 — Present
Tarbiat Modares University, Tehran, Iran
Thesis Proposal: "Safe Navigation and Control of Autonomous Vehicles in Dynamic Urban Environments Based on a Hybrid Reinforcement Learning and Imitation Learning Approach"
Supervisor: Prof. Vahid Johari Majd
Graduate Coursework
Advanced Robotics Reinforcement Learning Neural Networks Sensors & Actuators
Isfahan University of Technology Logo

B.Sc. in Electrical Engineering (Control Theory)

2018 — 2023
Isfahan University of Technology (IUT), Isfahan, Iran
B.Sc. Dissertation: "Autonomous Driving Control Using End-to-End Deep Learning"
Supervisor: Prof. Maryam Zekri
Core Disciplines
Intelligent Control Modern Control Theory Linear Algebra Computational Methods Signal Processing

Research Areas & Expertise

Developing robust algorithms for perception, multi-agent forecasting, and optimal decision-making in dynamic environments.

Safe Autonomous Navigation & Control

Designing hybrid Reinforcement Learning (RL) and Imitation Learning formulations with safety guarantees for vehicle motion planning and obstacle avoidance in unstructured dynamic urban traffic.

Multi-Agent Trajectory Forecasting

Modeling crowd interactions and social dynamics using Spatio-Temporal Graph Convolutions (ST-GCNN) paired with Conditional VAEs and Gaussian Mixture Model latent spaces.

Computer Vision & Generative AI

Object detection with YOLOv11, unpaired image-to-image translation with CycleGAN, and generative text-to-video experiments.

Medical Image Analysis & ViTs

Comparative histopathology image classification using Vision Transformers (ViT) and Deep Residual Networks (ResNet), with careful evaluation of model behavior and limitations.

Featured Research & Engineering Repositories

Open-source implementations, experiments, visual results, and technical documentation across AI, robotics, and control.

Technical Skills & Frameworks

Proficiency in deep learning libraries, robotics tools, software engineering, and mathematical foundations.

Deep Learning & AI

PyTorch Reinforcement Learning (DQN / PG) Gymnasium / OpenAI Gym Model-Based RL (Dyna-Q) LLM Prompt Optimization Graph Neural Networks (GNNs) Computer Vision (OpenCV) YOLOv11 Vision Transformers (ViT) Generative AI (GANs / Diffusion)

Robotics & Control

Autonomous Navigation Control Theory (Modern & Optimal) Trajectory Planning MATLAB / Simulink Sensors & Actuators

Engineering & Deployment

Docker Containerization Linux / Bash Git / GitHub SQL / PostgreSQL Data Pipelines

Languages & Mathematics

Python C / C++ Linear Algebra Probability & Statistics C#

Teaching & Industry Experience

Academic teaching assistantships and machine learning engineering experience.

Tarbiat Modares University Logo

Teaching Assistant

Fall 2026
Tarbiat Modares University (TMU)
Graduate teaching assistant for advanced courses under Prof. Vahid Johari Majd:
Neural Networks (Prof. Majd) Reinforcement Learning (Prof. Majd)
Isfahan University of Technology Logo

Teaching Assistant

2021 — 2023
Isfahan University of Technology (IUT)
Conducted recitation sessions, problem-solving workshops, and lab instruction across multiple core courses:
Intelligent Control (Prof. Zekri) Modern Control (Prof. Izadi) Industrial Process Control (Prof. Ghaisari) Applied Linear Algebra (Prof. Mojiri) Computational Methods in EE (Prof. Izadi) Fundamentals of Programming (C/C++) (Prof. Zahabi)
PayamPardaz Logo

Machine Learning Engineer Intern

Summer 2022
PayamPardaz • Isfahan, Iran
Researched sandbox automation and engineered machine learning classification pipelines (Random Forest, SVM, MLP, Decision Trees) for automated behavioral malware detection and threat analysis.
Behavioral ML Classification Sandbox Automation Python Pipelines

Research & Academic Inquiries

I am always open to discussing novel research directions, exchanging ideas on Autonomous Systems & Deep Learning, and actively exploring prospective Ph.D. positions and academic collaboration opportunities.