About me.
Currently, I am working in Shanda AI team as an AI scientist, focusing on solving the application and research of large models in AI medical care. This is a continuation of my doctoral project, hoping to contribute my own strength to digital health.
I got my Ph.D. degree in the School of Electrical and Electronic Engineering at Nanyang Technology University (NTU), Singapore. I completed my Bachelor's degree at the School of Electronics and Information Engineering, Harbin Institute of Technology, China.
My PhD research focused on developing AI systems to understand human behaviors, including voice, language, facial expressions, and body movement from audio-video recordings. For six years, I worked on a psychiatric project to automatically diagnose and assess mental illness patients in collaboration with NTU and IMH Singapore.
Previously, I was a AI Research Scientist at Minsigns Health, a startup company using machine learning for long-term monitoring of people with mental disorders. I then joined HUAWEI 2012 laboratory as a Senior AI Engineer, working on multi-modal search and recommendation, large language models, and multimodal model research.
Publications.
Long Term Memory: The Foundation of AI Self-Evolution
X Jiang, F Li, H Zhao, J Wang, J Shao, S Xu, S Zhang, W Chen, X Tang, et al.
arXiv preprint arXiv:2410.15665, 2024
Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning
S Xu, Y Luo, W Shi
The 2nd Workshop on Large Generative Models Meet Multimodal Applications, 2024
LGM3A '24: the 2nd Workshop on Large Generative Models Meet Multimodal Applications
S Xu, Y Luo, J Dauwels, A Khong, Z Wang, Q Chen, C Cai, W Shi, et al.
Proceedings of the 2nd Workshop on Large Generative Models Meet Multimodal Applications, 2024
Fashion-GPT: Integrating LLMs with Fashion Retrieval System
Q Chen, T Zhang, M Nie, Z Wang, S Xu, W Shi, Z Cao
Proceedings of the 1st Workshop on Large Generative Models Meet Multimodal Applications, 2023
LGM3A'23: 1st Workshop on Large Generative Models Meet Multimodal Applications
Z Wang, C Long, S Xu, B Gan, W Shi, Z Cao, TS Chua
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Identifying psychiatric manifestations in schizophrenia and depression from audio-visual behavioural indicators through a machine-learning approach
S Xu, Z Yang, D Chakraborty, YHV Chua, S Tolomeo, S Winkler, et al.
Schizophrenia 8 (1), 92, 2022
Automated lexical analysis of interviews with individuals with schizophrenia
S Xu, Z Yang, D Chakraborty, Y Tahir, T Maszczyk, YHV Chua, J Dauwels, et al.
9th International Workshop on Spoken Dialogue System Technology, 2019
Automated verbal and non-verbal speech analysis of interviews of individuals with schizophrenia and depression
S Xu, Z Yang, D Chakraborty, YHV Chua, J Dauwels, D Thalmann, et al.
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
Prediction of negative symptoms of schizophrenia from objective linguistic, acoustic and non-verbal conversational cues
D Chakraborty, S Xu, Z Yang, YHV Chua, Y Tahir, J Dauwels, et al.
International Conference on Cyberworlds (CW), 2018
Automatic Verbal Analysis of Interviews with Schizophrenic Patients
S Xu, Z Yang, D Chakraborty, Y Tahir, T Maszczyk, YHV Chua, J Dauwels, et al.
23rd International Conference on Digital Signal Processing (DSP), 2018
