Superintelligence And Industrial Lab
Advancing AI Technologies for Systems Informatics and Data Analytics
Pioneering artificial intelligence research that bridges theoretical innovation with real-world industrial transformation through advanced machine learning, deep learning, and intelligent decision systems at Tsinghua University.
Research Excellence
Advancing superintelligence through cutting-edge AI, machine learning, and deep learning innovations
AI-Powered High-Dimensional Analytics
Leveraging advanced machine learning for effective information extraction, online change detection, and adaptive sampling in high-dimensional structured data. Our AI models handle complex patterns in real-time streaming data with unprecedented accuracy.
Deep Learning & Foundation Models
Developing next-generation deep learning architectures for time series forecasting, multimodal learning, and large language models. Our research spans functional data analysis, tensor decomposition, and specialized domain foundation models.
Intelligent Decision & Control Systems
AI-driven decision-making frameworks integrating game theory, optimization algorithms, and data-driven control for complex networked systems. Our methods combine domain knowledge with reinforcement learning.
Industrial AI Applications
Transforming industries through AI—from semiconductor manufacturing quality prediction to aircraft production optimization, urban transportation intelligence, and supply chain resilience using state-of-the-art machine learning.
Advanced Statistical Learning
Statistical modeling meets AI—developing robust monitoring frameworks for complex systems through Bayesian networks, Gaussian processes, tensor learning, and graph neural networks for anomaly detection and predictive maintenance.
Graph & Network Intelligence
Pioneering graph relational learning and network analysis using GNNs for spatiotemporal prediction, community detection in functional data networks, and intelligent modeling of metro passenger flows and traffic systems.
Explore Our Research Areas
Lab News
Latest announcements and updates from our research lab
Best Paper Award at AAAI 2025
Our paper on "Multi-Agent Causal Discovery using Large Language Models" received the Best Paper Award at AAAI 2025.
New PhD Students Join Our Lab
We welcome three new PhD students specializing in causal inference, deep learning, and time series analysis.
New Research Grant from NSF
Awarded $2.5M NSF grant for research on "Explainable AI for Industrial Systems Monitoring and Anomaly Detection".
Industry Partnership with Tesla
Established new collaboration with Tesla for advanced manufacturing quality control using AI-driven anomaly detection.
5 Papers Accepted at Top Venues
Five research papers accepted at NeurIPS 2024, ICLR 2025, and IEEE TASE, showcasing our advances in ML and AI.
Recent Publications
Highlights from our latest research contributions
12
Active Researchers
66
Top-Tier Publications
6
Elite Industry Partners
867
Total Citations
Trusted by Leading Organizations
Collaborating with world-class institutions and industry leaders to drive AI innovation forward
Ready to Collaborate?
Join our mission to advance superintelligence through cutting-edge AI research and industrial applications.
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Our Research
Building the future of superintelligence through cutting-edge AI research and innovation
Core Research Pillars
At the intersection of theoretical innovation and transformative industrial applications
Deep Learning & Neural Architectures
We pioneer advanced deep learning architectures including Graph Neural Networks (GNNs), Transformers, and Recurrent Attention Models for complex data analysis. Our innovations include spatiotemporal graph networks for cellular KPI prediction, multi-task learning frameworks for medical imaging, and deep reinforcement learning for bilevel optimization in product design.
AI-Powered Statistical Learning & Monitoring
Bridging classical statistics with modern AI, we develop intelligent statistical models for real-time monitoring, anomaly detection, and predictive maintenance. Our methods include Bayesian networks for causal inference, Gaussian processes for robust parameter design, and Thompson sampling for partially observable online change detection.
Tensor Learning & High-Dimensional Analytics
We tackle the curse of dimensionality through innovative tensor methods and functional data analysis. Our research includes tensor decomposition for weakly-dependent data on graphs, low-rank robust subspace tensor clustering for metro flow modeling, and latent tensor Gaussian processes for spatial monitoring.
Graph Intelligence & Network Analysis
Advancing graph relational learning and network science through AI. We develop graph regularized tensor latent Dirichlet allocation for individualized passenger travel patterns, functional data edged networks for metro station clustering, and multi-view clustering based on functional data.
Intelligent Decision Systems & Optimization
Creating AI-driven decision frameworks that integrate game theory, optimization, and reinforcement learning. Our research spans deep reinforcement learning for bilevel optimization, data-driven control of complex networked systems, and intelligent decision-making with domain knowledge integration.
Industrial AI & Smart Manufacturing
Transforming industries through practical AI deployments. Our applications span semiconductor manufacturing, aircraft manufacturing, urban transportation, supply chain management, and financial systems. We deploy AI solutions at scale with industry leaders including Huawei, Tencent, Alibaba, Baidu, ByteDance, and Meituan.
Research Impact
Our research has resulted in 70+ publications in premier venues including IEEE Transactions (Medical Imaging, Knowledge and Data Engineering, Automation Science and Engineering, Industrial Informatics), IISE Transactions, Technometrics, Journal of Quality Technology, and top-tier AI conferences including KDD, IJCAI, AAAI, and ECML-PKDD.
We collaborate extensively with industry leaders, deploying AI solutions that impact millions of users daily in transportation, manufacturing, e-commerce, and telecommunications sectors.
Recent Publications
Latest research contributions from our lab
Publications
Our research contributions in AI, machine learning, and intelligent systems
Research Publications
Peer-reviewed articles in top-tier journals and conferences
Filter by Research Topics:
2025 Publications
2024 Publications
2023 Publications
2022 Publications
2021 Publications
2020 Publications
2019 Publications
2018 Publications
2017 Publications
2016 Publications
Publication Impact
Research metrics and achievements
66
Total Publications
11
IEEE Transactions
17
H-Index
867
Total Citations
Key Publication Venues
IEEE Transactions
- Automation Science and Engineering
- Computational Social Systems
- Engineering Management
- IEEE Robotics and Automation Letters
Top Journals
- INFORMS Journal on Data Science
- International Journal of Intelligent Systems
- International Journal of Production Economics
- Journal of Energy Storage
Top Conferences
- AAAI Conference on Artificial Intelligence
Our Team
Meet the researchers advancing AI and data analytics
Dr. Chen Zhang
Associate Professor & Principal Investigator
Department of Industrial Engineering, Tsinghua University
Research Interests
- Statistical modeling and monitoring for complex systems
- Machine learning and data mining for large-scale systems
- Online learning and real-time monitoring for streaming data
Education
- Ph.D. in Industrial Systems Engineering, National University of Singapore (2017)
- Visiting Student, Georgia Institute of Technology (2016)
- B.E. in Electronic Science and Technology, Tianjin University (2012)
Contact
- Email: zhangchen01@tsinghua.edu.cn
- Office: Room 602, Shunde Building, Tsinghua University
- Tel: +86-10-62796135
Research Fellows
Ph.D. in Management Science and Engineering from Tianjin University. Research focuses on supply chain resilience, bi-level programming, and deep reinforcement learning.
Postdoctoral research in advanced machine learning methodologies and their applications to complex systems.
Ph.D. from Beijing University of Posts and Telecommunications. Focuses on deep learning-based time series and functional data analysis.
Ph.D. from Capital University of Economics and Business. Research in deep learning, complex networks, and financial risk management.
PhD Students
Research focuses on change point detection, functional data analysis, tensor data analysis, and causal inference.
Working on multimodal large language models and time-series anomaly detection.
M.S. from Wuhan University. Research in optimization algorithms, game theory, and data-driven control of complex networked systems.
Research in advanced machine learning and statistical methodologies.
M.S. from Tsinghua University. Focuses on deep learning foundation models, large language models, and time series foundational models.
Research Assistants
Supporting research in data analytics and machine learning applications.
M.S. from University of Hong Kong. Research in video anomaly detection, medical image analysis, and medical large language models.
Supporting advanced research projects in machine learning and data analytics.
Notable Alumni
Ph.D. 2025. Research in functional data analysis, tensor decomposition, and Gaussian processes. Multiple awards including ICQSR, INFORMS-DMDA.
M.Eng. 2025. Focus on communication network operations and spatiotemporal data modeling with deep learning.
Research in transportation applications, urban flow prediction, and anomaly detection.
M.S. from Carnegie Mellon University. Research on adaptive sampling in deep learning frameworks.
M.S. from Georgia Tech. Focus on deep reinforcement learning and multi-modal data fusion.
Ph.D. from Tsinghua. Research in Bayesian networks, discrete event prediction, and ontology modeling.
M.S. in Statistics from Rice University, B.S. in Actuarial Science and Economics from University of Delaware. Research in time series, spatial-temporal data, and stochastic process modeling.
Ph.D. and B.E. in Industrial Engineering from Tsinghua University. Research in adaptive sampling, high dimensional data monitoring, and reinforcement learning.
Ph.D. in Industrial Engineering from Tsinghua University, B.S. in Control Science and Engineering from Shandong University. Research in maintenance strategies optimization for networked systems.
Associate Professor at School of Mechanical Engineering, Guizhou University. Research in statistical modeling and monitoring for complex systems, intelligent maintenance and health management.
Industry Partners
Collaborating with leading technology companies to drive AI innovation
Collaborative Research
We partner with industry leaders to tackle real-world challenges through innovative AI solutions
Huawei Technologies
Collaboration on communication network operations, optimization algorithms, and AI-driven system monitoring for next-generation telecommunications infrastructure.
Meituan
Research in urban logistics optimization, delivery network analysis, spatiotemporal data modeling, and intelligent transportation systems for on-demand services.
Tencent
Joint research on large-scale machine learning, real-time data analytics, intelligent systems, and AI applications in social media and gaming platforms.
Alibaba Group
Collaborative work on supply chain optimization, e-commerce analytics, cloud computing solutions, and AI-powered recommendation systems for retail.
Baidu
Partnership in AI research, autonomous systems, deep learning applications, natural language processing, and intelligent search technologies.
ByteDance
Research collaboration on recommendation systems, content analytics, multimodal learning, and AI applications in short-video and social media platforms.
Partnership Opportunities
Building bridges between research and industry
Industry-Scale Projects
We collaborate on large-scale data science projects addressing real-world industrial challenges in manufacturing, logistics, and technology sectors.
Technology Transfer
Our research methodologies are designed for practical implementation, with ongoing technology transfer to industry partners for real-world deployment.
Joint Innovation
We work closely with partners to co-develop innovative solutions that bridge academic research and industrial applications through collaborative R&D programs.
Contact Us
Get in touch with our research group
Research Opportunities
Join us in advancing AI and data analytics research
Address
Room 602, Shunde Building
Tsinghua University
Beijing, 100084, China
Phone
+86-10-62796135
Open Positions
We're actively recruiting at all levels
PhD Students
- → Strong mathematical background
- → Programming proficiency (Python, R, MATLAB)
- → Research passion in ML/AI
- → Self-motivated learner
✓ Fully Funded Positions Available
Postdoctoral Fellows
- → Advanced ML research experience
- → Industry collaboration interest
- → Strong publication track record
- → Independent research capability
✓ Fully Funded Positions Available
Research Associates
- → Data science project experience
- → Industry-scale system knowledge
- → Strong coding skills (Python, Java, C++)
- → Team collaboration experience
✓ Fully Funded Positions Available
Open Source Projects
Explore our research implementations and contributions
Discover the code behind our cutting-edge research in artificial intelligence, machine learning, and industrial applications. All our projects are open source and available for the research community.
Our Repositories
Browse through our open source projects, from research implementations to practical tools.
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