M.Sc. Computer Science

  RWTH Aachen University, Aachen, Germany

  Email: qiang.li@rwth-aachen.de

Guten Tag! I am currently working as IT/OT & ML Senior Analyst at Accenture. Before working at Accenture, I was an IDEA Research Grant Student in Prof. Dr. Manfred Claassen Group, ETH Zürich, and obtained my Master's degree in Computer Science at RWTH Aachen University. I got my bachelor degree from the HFUT with top academic performance and received four years national scholarships. My Bachelor was majoring in IoT and I also founded the HFUT Robocup Lab. After my B.Sc. studies, I worked as a computer vision working student in Siemens AG Aachen Gas Turbine Research Center while taking the Master Informatik study at RWTH Aachen.

My research interests focus on Object Recognition, Detection and Segmentation, Deployment of ML system, Model Interpretability, Multi-Tasking, and Multi-Modality.

[Feedback from Mentor at ETH Claassen Lab]

[Feedback from Mentor at PayLuft Zürich Based Fintech Startup]

[Feedback from Mentor at Sinovation Venture AI Institute]

[Feedback from Mentor at RWTH Computer Vision Group]

Highly recommended to take a look at my work in addictive manufacturing image analysis at Siemens AG Aachen Gas Turbin Research Center, advised by Dr. Hamid Jahangir, Where I developed a software integrated with defect detection algorithm I designed. Check Expert Interview New Paths in 3D Printing, the interview and invited talk about our team and work.

Exploiting Interactivity and Heterogeneity for Sleep Stage Classification via Heterogeneous Graph Neural Network
Ziyu Jia, Qiang Li, Youfang Lin, Yuhan Zhou, Xiyang Cai, Peng Zheng, Jing Wang
Accepted by 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),Full paper, 2023.
In this paper, we propose a novel Sleep Heterogeneous Graph Neural Network (Sleep-HGNN) to employ these essential features. The SleepHGNN is a deep graph network consisting Heterogeneous Graph Transformer layers, which are composed of Heterogeneous Message Passing module for capturing the heterogeneity and Target-Specific Aggregation module for capturing the interactivity of physiological signals. The experiments conducted on two benchmark datasets show that the SleepHGNN outperforms the state-of-the-art models on the sleep stage classification task for both healthy subjects and subjects with sleep disorders. Paper Coming Soon!    Conference Website   

Continual learning on deployment pipelines for Machine Learning Systems
Qiang Li, Chongyu Zhang
Accepted by The Conference on Neural Information Processing Systems (NeurIPS), DMML Workshop, 2022.
In this work, we presented a comparison of various solutions for the deployment of machine learning systems, includes different layers of automation from highly manual model training and deployment to an automated continuous integration workflow. We proposed the evaluation metrics in practice and describe how real-world requirements differ from more academic settings. Livestream on NeurIPS2022    Poster    Paper on arxiv    ResearchGate    Workshop Website   

Explainable AI: Object Recognition With Help From Background
Raza Hashmi, Qiang Li
Accepted by The International Conference on Learning Representations (ICLR), CSS Workshop, 2022.
This work explores how backgrounds might help in object recognition tasks in depth. Our project is fascinated by the baseline work done by Xiao et al. in their noise or signal paper. Website    Blogs    Camera ready video of presentation on ICLR2022    Dataset on Kaggle   

AI Quality Next - BMW Group - Computer Vision project
Computer Vision Engineer: Qiang Li
AIQX provides a platform to integrate machine learning & deep learning algorithms for visual inspections directly into the production processes. Creation of a central standard for the implementation of AI for quality inspections in the global production system. AI provides far more robust algorithms and opens new areas of defect detection and order verification for manufacturing.
Youtube:Artificial Intelligence at the BMW Group    Youtube:BMW Factory – Integration of A.I. in the Production Line    Published materials about our AIQX Project & Usecases in News and Major Media!*   

All You Need Is Cell Attention: A Cell Annotation Tool for Single-Cell Morphology Data
Qiang Li*, Corin Otesteanu, Lily Xu
Accepted by The International Conference on Learning Representations (ICLR), Workshop on AI for Public Health, 2021.
PDF    code/software    

Cell Morphology Based Diagnosis of Cancer using Convolutional Neural Networks: CellNet
Qiang Li, Yiran Xing, Tianwei Lan, ChenYu Tian, Ying Chen
Won Challenge on Medical Track of AI in Public Healthcare of DeeCamp 2020.
website    code/models    video   

Localization and visualization of defects by PCA, KMeans, Colorspace Template Matching for Additive Manufacturing
Hamid Jahangir, Qiang Li
Invited Talk on International Conference on Additive Manufacturing (ICAM), 2020.
invited talk    slides    software   

GPT-3 industry survey and applied scenarios
Qiyi Ye, Qiang Li
Designed 3 GPT-based generative model on real scenario at Sinovation Ventures AI Institut, 2020.
code/GPT generative models    slides

Hobbies: Vloger who loves KPOP, Museum, Cooking... And you can find me in TikTok / Little Red Book(小红书)/ Wechat Channel by ‘Jonas的新鲜感’（Jonas' curiosity), We have received over millions of views and likes 👍, and thousands of followers! Have created 100+ Vlogs. Keeping Learning! Let's move on together!
I am a fan of Hackathons. It gave me valuable experiences, developed critical thinking, problem-solving, and leadership skills.