Christos Mousas

About

Christos Mousas is a leading researcher at the intersection of virtual reality (VR), human-computer interaction, and intelligent systems. His work primarily explores how humans perceive and interact with virtual characters and environments, with a strong emphasis on understanding behavioral responses and designing more natural, intuitive interfaces. A key contribution is his development of a dilated convolutional neural network for predicting driver activity (29 citations), which advances the field of anticipatory systems for human-robot interaction. Mousas has also made significant strides in VR-based social cognition, investigating how a virtual character’s appearance—from mannequin to human-like forms—affects users’ avoidance movement behavior (22 citations), and how mismatches between a character’s appearance and voice impact interaction quality (11 citations). His research on rendering styles further reveals how visual fidelity shapes locomotive behavior in immersive environments. Beyond behavioral studies, Mousas created Hack.VR, an innovative programming game that teaches object-oriented coding through a node-based VR interface, blending education with immersive technology. With over 75 citations across his most influential papers, Mousas’s work is shaping the future of realistic, responsive, and educational virtual experiences.

Research Focus

Key Achievements

Top Papers

1. 1
   Dilated Convolutional Neural Network for Predicting Driver's Activity

   29 citations · 2018
2. 2
   Toward Understanding the Effects of Virtual Character Appearance on Avoidance Movement Behavior

   22 citations · 2021
3. 3
   Exploring the Appearance and Voice Mismatch of Virtual Characters

   11 citations · 2023
4. 4
   Effects of Rendering Styles of a Virtual Character on Avoidance Movement Behavior

   11 citations · 2022
5. 5
   Hack.VR: A Programming Game in Virtual Reality

   3 citations · 2020

Key Collaborators

Contact & Links