Elliott Wen
The University of Auckland
I am a lecturer at the University of Auckland. My research interests include metaverse, software enginerring, and mobile computing.
I have a keen passion for both indulging in and reverse-engineering classic games from the past, such as MapleStory and Red Alert 2. Additionally, I enjoy the intricate process of constructing operating system kernels and developing network devices.
I am actively seeking highly motivated Ph.D. students and Research Assistants. Our focus is on advancing research in the fascinating field of VR gaming. Yes, you read it correctly – gaming. We would like to do more research on motion sickness, physical safety, and content moderation in VR applications.
news
Oct 10, 2024 | Our paper “KernelVM: Teaching Linux Kernel Programming through a Browser-Based Virtual Machine” was accepted in ACM SIGCSE TS 2025. |
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Oct 10, 2024 | Our paper “BinEq–A Benchmark of Compiled Java Programs to Assess Alternative Builds” was accepted in SCORED 2024. |
Sep 10, 2024 | Our paper “Keep Me Updated: An Empirical Study of Proprietary Vendor Blobs in Android Firmware” was accepted in IEEE ICPADS 2024. |
Apr 8, 2024 | I gave an invited talk at Hong Kong PolyU. Hooray to 50-year anniversary of Department of Computing in PolyU. |
Mar 17, 2024 | Our paper “VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research” was selected as the best paper in IEEE VR 2024. |
selected publications
- Improving the domain adaptation of retrieval augmented generation (RAG) models for open domain question answeringTransactions of the Association for Computational Linguistics, 2023
- VRhook: A Data Collection Tool for VR Motion Sickness ResearchIn Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, 2022
- SecretHunter: A Large-scale Secret Scanner for Public Git RepositoriesIn 2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2022
- VR. net: A Real-world Dataset for Virtual Reality Motion Sickness ResearcharXiv preprint arXiv:2306.03381, 2023