Ramtin Tabatabaei

Human–robot interaction

Ramtin Tabatabaei

Ph.D. candidate · University of Melbourne

My research sits at the intersection of artificial intelligence, robotics, and human–robot interaction. I study what happens when robots make mistakes: how people respond, how trust changes, and how robots can recognise and recover from failure.

I explore how machine learning, vision–language models, and robot reasoning can help robots understand their actions, detect when things go wrong, and adapt to unexpected situations.

I am a Ph.D. candidate in the School of Computing and Information Systems, supervised by Wafa Johal and Vassilis Kostakos. My work is part of the Human-Computer Interaction Group and the Human-Robot Interaction Lab.

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Ramtin Tabatabaei

Research

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I combine real-robot experiments, eye tracking, and controlled user studies to understand how people notice, interpret, and respond to robot mistakes. Alongside this, I develop AI methods that combine vision–language models with robot-state monitoring to detect failures and guide recovery. My work connects human behaviour with robot intelligence to make human–robot collaboration more reliable.

Behavioural signals
Using gaze and interaction patterns to detect when something goes wrong.
Trust & recovery
Understanding how repeated failures and robot awareness shape collaboration.
Robotic systems
Building and evaluating detection and recovery methods on real robots and in simulation.

Selected publications

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Teaching & supervision

Teaching history

In Semester 2, 2026, I am a lab tutor for Intelligent Robotics (ECE4078) at Monash University and a marker for Usability Evaluation Methods (INFO20004) at the University of Melbourne. Previously, I tutored Elements of Data Processing (Semester 2, 2025 and Semester 1, 2026) and Machine Learning (Semester 1, 2026) at Melbourne.

I also supervised a master's project developing a web application for annotating ROSBag data from March to July 2024.