Joya Chen

Research Intern Seed at ByteDance

Singapore
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Summary

👤
Senior
🎓
Top School
Joya Chen is a final-year Ph.D. candidate at NUS and a research intern at ByteDance Seed specializing in large multimodal models for video, with nine years of research and engineering experience across industry leaders like Meta and TikTok. Her work spans data scaling, model architecture, pre- and post-training, and benchmarking, with contributions to streaming-capable systems and interactive demos (Seed1.5-VL) and live streaming VideoLLM research. She has co-authored projects presented at top venues (CVPR) and helped build large-scale datasets and processing pipelines such as Ego-Exo4D and LiveCC. Comfortable at the intersection of academic rigor and production-facing research, she repeatedly focuses on online and streaming multimodal problems that bridge real-time interaction and world modeling. Based in Singapore and graduating summer 2026, she is actively pursuing industrial research roles and welcomes collaboration and contact via email. An intriguing personal touch: her GitHub bio—“Hopes never die”—hints at a resilient, long-term commitment to ambitious research goals.
code10 years of coding experience
bookMaster's degree, Computer Science, Master's degree, Computer Science at University of Science and Technology of China
bookBachelor's degree, Vehicle Engineering, Bachelor's degree, Vehicle Engineering at 武汉理工大学
bookDoctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at National University of Singapore
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Github Skills (75)

transformers10
python10
vehicle-detection10
deep-learning10
gpu10
compression10
gemma10
gpu-acceleration10
glm10
multimodal10
detectron10
video-understanding10
numpy10
audio10
face-recognition10

Programming languages (5)

C++CJupyter NotebookMATLABPython

Github contributions (5)

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chenjoya/ai-bibtex

Sep 2020 - Nov 2022

Contributions:7 commits, 40 pushes in 2 years 2 months
showlab/Q2A

May 2022 - May 2022

[ECCV 2022] AssistQ: Affordance-centric Question-driven Task Completion for Egocentric Assistant
Contributions:17 commits, 35 pushes, 1 branch in 29 days
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