Mykola Maslych

schoolUniversity of Central Floridabar_chart#1731 Global Rank

Total Papers

HCI Rank

#1731

Research Areas

Years Active

Recent Publications

From One World to Another: Interfaces for Efficiently Transitioning Between Virtual Environments

Personal computers and handheld devices provide keyboard shortcuts and swipe gestures to enable users to efficiently switch between applications, whereas today's virtual reality (VR) systems do not. In this work, we present an exploratory study on user interface aspects to support efficient switching between worlds in…

CUI '251st AuthorSocial & Collaborative VR +1

Mitigating Response Delays in Free-Form Conversations with LLM-powered Intelligent Virtual Agents

We investigated the challenges of mitigating response delays in free-form conversations with virtual agents powered by Large Language Models (LLMs) within Virtual Reality (VR). For this, we used conversational fillers, such as gestures and verbal cues, to bridge delays between user input and system responses and evalu…

CHI '244th AuthorFull-Body Interaction & Embodied Input +1

Unlocking Understanding: An Investigation of Multimodal Communication in Virtual Reality Collaboration

Communication in collaboration, especially synchronous, remote communication, is crucial to the success of task-specific goals. Insufficient or excessive forms of communication may lead to detrimental effects on task performance while increasing mental fatigue. However, identifying which combinations of communication…

CHI '231st AuthorAutomated Driving Interface & Takeover Design +1

Effective 2D Stroke-based Gesture Augmentation for RNNs

Recurrent neural networks (RNN) require large training datasets from which they learn new class models. This limitation prohibits their use in custom gesture applications where only one or two end user samples are given per gesture class. One common way to enhance sparse datasets is to use data augmentation to synthes…

CHI '222nd AuthorHand Gesture Recognition +1

The Voight-Kampff Machine for Automatic Custom Gesture Rejection Threshold Selection

Gesture recognition systems using nearest neighbor pattern matching are able to distinguish gesture from non-gesture actions by rejecting input whose recognition scores are poor. However, in the context of gesture customization, where training data is sparse, learning a tight rejection threshold that maximizes accurac…

CHI '204th AuthorHand Gesture Recognition +2

Moving Toward an Ecologically Valid Data Collection Protocol for 2D Gestures In Video Games

Those who design gesture recognizers and user interfaces often use data collection applications that enable users to comfortably produce gesture training samples. In contrast, games present unique contexts that impact cognitive load and have the potential to elicit rapid gesticulations as players react to dynamic cond…

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