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Registration: 08.06.2026

Olena Doroshenko

Specialization: Unity AR/VR/XR Developer
— NYIT M.S. Computer Science graduate specializing in AR/VR/XR development with Unity, AR Foundation, and ARKit. — Built end-to-end mmWave radar AR system integrating 60 GHz radar, MATLAB classification, and Unity on iPhone; published paper 2026. — Developed independent iOS AR app (Virtual AR Photo Album) with real-world photo scanning, library import, and persistent storage. — Research experience in AI/CV: markerless 3D motion capture pipeline for early cerebral palsy screening (WVU Neural Engineering Lab, 2023–2024). — Published researcher: first-author NYIT paper (2026); co-author poster on bioRxiv (2024); first-author abstract at WVU conference (2024). — Proficient in C#, Python, MATLAB, Blender 3D, iOS development, and AR prototyping.
— NYIT M.S. Computer Science graduate specializing in AR/VR/XR development with Unity, AR Foundation, and ARKit. — Built end-to-end mmWave radar AR system integrating 60 GHz radar, MATLAB classification, and Unity on iPhone; published paper 2026. — Developed independent iOS AR app (Virtual AR Photo Album) with real-world photo scanning, library import, and persistent storage. — Research experience in AI/CV: markerless 3D motion capture pipeline for early cerebral palsy screening (WVU Neural Engineering Lab, 2023–2024). — Published researcher: first-author NYIT paper (2026); co-author poster on bioRxiv (2024); first-author abstract at WVU conference (2024). — Proficient in C#, Python, MATLAB, Blender 3D, iOS development, and AR prototyping.

Skills

Unity
AR Foundation
ARKit
C#
Blender
Python
MATLAB
iOS Development
3D Modeling
Computer Vision
Machine Learning
TCP Networking
Git

Work experience

Unity AR Developer
01.2026 - 05.2026 |New York Institute of Technology
Unity 6.4, AR Foundation, ARKit, C#, MATLAB, Blender 4.2, TI IWR6843AOP, TCP/Wi-Fi
● Built end-to-end mobile AR system detecting objects behind barriers using 60 GHz mmWave FMCW radar. ● Integrated radar point-cloud acquisition, MATLAB KNN classification, and TCP/Wi-Fi streaming to iPhone. ● Implemented Unity AR Foundation scene with ARKit pose tracking, world-space UI, and anchored 3D holograms. ● Created Blender 4.2 3D models of target objects (bottles and power banks); validated on 8 specimens. ● Achieved sub-50 ms classification-to-display latency with 10.5-second end-to-end detection cycle. ● Published first-author research paper with NYIT Department of Computer Science, 2026.
Unity AR Developer
2026 - 2026 |Independent
Unity, ARKit, AR Foundation, C#, iOS
● Built iPhone AR app anchoring a volumetric photo album onto real-world surfaces using ARKit plane detection. ● Implemented three photo input modes: physical print scanning, camera capture, and iPhone library import. ● Developed crop algorithm for automatic physical photograph detection and digitization. ● Added AR controls for page turning, album customization, and cloud backup via Google Drive. ● Delivered fully functional iOS AR experience with persistent storage and intuitive spatial interaction.
Research Assistant
06.2023 - 05.2024 |West Virginia University
Python, MATLAB, DeepLabCut, MiDaS, CNNs, MATLAB Simulink
● Developed markerless 3D motion capture pipeline from smartphone video for infant cerebral palsy screening. ● Built full pipeline: smartphone video → DeepLabCut 2D pose → 3D reconstruction → clinical neck-trunk angle extraction. ● Benchmarked three MiDaS depth architectures; selected DPT_Hybrid for optimal accuracy-speed tradeoff. ● Scaled biomechanical body models of infants (22 body parts, joint constraints) in MATLAB Simulink. ● Co-authored research poster published on ResearchGate; presented at NYIT 2024.

Educational background

Computer Science (Masters Degree)
2024 - 2026
New York Institute of Technology
Mathematics (Bachelor’s Degree)
2022 - 2024
West Virginia University
Mathematics (Bachelor’s Degree)
2020 - 2024
Taras Shevchenko National University of Kyiv

Languages

EnglishIntermediateUkrainianElementaryRussianIntermediate