Kateřina Vodičková

Led the design and execution of qualitative and quantitative research studies for corporate clients, generating data-driven insights to inform strategic decision-making.

Conducted thematic analysis of collected data using Miro, identifying critical organizational challenges and proposing actionable solutions that improved operational efficiency.

Supported the successful implementation of research findings into company practices, ensuring practical application of insights and measurable improvements in business outcomes.

Contributed to a systematic literature review on digital interventions for mental health support, synthesizing key findings to inform research direction and evidence-based practices.

Supported the DigiWELL_Excellent research project, focusing on digital technologies and well-being, enhancing the scientific foundation for future studies.

Designed intuitive user interfaces for applications in Figma, progressing from low-fidelity wireframes to high-fidelity prototypes, enhancing visual and functional design.

Conducted comprehensive user testing and iterative design cycles, incorporating user feedback to refine designs and improve overall product usability and satisfaction.

Collaborated closely with development teams throughout the design process, ensuring seamless integration and technical feasibility of UI/UX solutions.

Led research and usability analysis for Self-Sovereign Identities in academic settings, developing a robust methodology to improve user adoption and experience.

Performed heuristic analysis and user research (focus groups, Maze platform) for the PERUN interface, informing the creation of a new, user-centric design system in Figma.

Managed experimental sessions for participants in virtual reality (VR) environments, ensuring adherence to research protocols for cognitive characteristic testing.

Administered pre- and post-exposure questionnaires to participants, accurately collecting critical data for analysis of VR's impact on cognitive functions.

Led experimental sessions for a study on speech production under stress, overseeing data collection from 79 participants using multimodal methods (STAI-Y2, NASA-TLX questionnaires, ECG).

Assisted in the segmentation and preparation of complex physiological and psychological datasets, ensuring data integrity and readiness for machine learning analysis.

Co-authored a research publication, contributing to the dissemination of findings on multimodal analysis of speech under stress, enhancing the project's scientific output.

Conducted experimental testing of user aspects for a mobile fitness application, gathering qualitative and quantitative data on user interaction and pain points.

Analyzed collected data to derive actionable insights, leading to concrete recommendations for improving application usability and overall user experience.