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| | short_description: Ambitious, Virtuous, Profoundly learned and Serve the People |
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| | # Beijing University of Chemical Technology (BUCT) |
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| | [](https://www.buct.edu.cn) |
| | [](https://www.shanghairanking.com/institution/beijing-university-of-chemical-technology) |
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| | > "To be ambitious, virtuous, profoundly learned and to serve people" |
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| | > (宏德博学 化育天工) |
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| | ## 🏛️ About Us |
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| | **Beijing University of Chemical Technology (BUCT)**, established in 1958, is a high-level national university directly affiliated with the Ministry of Education of China. We are a key member of the national **"Project 211"** and the **"985 Project Innovation Platform"**, actively leading in China's **"Double First-Class"** university construction plan. |
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| | With a legacy of over 60 years, BUCT has evolved into a multi-disciplinary research university with a formidable reputation in science and engineering. We rank **6th globally in Chemical Engineering** (ARWU) and host world-class faculties in Materials Science, Intelligent Process Engineering, and Life Sciences. |
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| | ### 🌟 Our Mission: Synthesizing Nature through Intelligence |
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| | We are dedicated to bridging the gap between fundamental molecular science and advanced artificial intelligence. This organization serves as the digital nexus for our open-source contributions, fostering a global community where chemistry meets computation (AI for Science). |
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| | ## 🔬 Research Pillars: AI for Science (AI4S) |
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| | Our open-source initiatives are organized around four strategic pillars where BUCT possesses unique domain expertise: |
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| | ### 1. AI for Materials & Chemistry (AI4Mat) |
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| | Leveraging the **Materials Genome Initiative**, our researchers in the *College of Materials Science and Engineering* and the *State Key Laboratory of Organic-Inorganic Composites* are revolutionizing material discovery. |
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| | - **Polymer Informatics:** Graph Neural Networks (GNNs) for predicting thermal, mechanical, and degradation properties of complex polymers. |
| | - **Supramolecular Intelligence:** Generative models for designing self-assembling photosensitizers and nano-diagnostic agents for precision medicine. |
| | - **Crystallography & DFT:** AI-assisted phase identification from XRD patterns and Neural Force Fields for accelerating Density Functional Theory (DFT) calculations. |
| | - **Green Catalysis:** Deep learning frameworks for optimizing catalytic pathways in sustainable chemical processes. |
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| | ### 2. Intelligent Process Systems (Industrial AI) |
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| | Led by the *Engineering Research Center of Intelligent Process Systems Engineering*, we focus on the safety and efficiency of large-scale industrial systems. |
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| | - **Fault Detection & Diagnosis:** Robust models benchmarked on the Tennessee Eastman (TE) process for identifying anomalies in complex chemical plants. |
| | - **Soft Sensing:** Virtual sensors driven by machine learning to estimate hard-to-measure process variables in real-time. |
| | - **Industrial IoT & Edge AI:** Lightweight models optimized for FPGA and embedded systems, enabling real-time monitoring in hazardous environments. |
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| | ### 3. Robotics & Autonomous Perception |
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| | The *College of Information Science and Technology* and the *Heke Autonomous Driving Team* push the boundaries of embodied AI. |
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| | - **Autonomous Driving:** Multi-modal fusion perception models (LiDAR + Vision) for unmanned vehicles in complex urban and industrial scenarios. |
| | - **Specialized Robotics:** Control algorithms for underwater robots and unmanned surface vehicles (USVs) designed for environmental monitoring. |
| | - **Vision-Language Models:** Large-scale models adapted for visual reasoning in dynamic physical environments. |
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| | ### 4. Bioinformatics & Digital Life |
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| | Integrating biology with big data, the *School of Life Science and Technology* pioneers computational solutions for health and synthesis. |
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| | - **Synthetic Biology (SynBio):** AI-driven pathway design for microbial synthesis of high-value chemicals (e.g., 2-phenylethyl alcohol), building on our iGEM successes. |
| | - **Precision Medicine:** Deep learning models for identifying cancer biomarkers (e.g., in kidney renal clear cell carcinoma) and predicting drug-target affinity. |
| | - **Microbial Omics:** Tools for analyzing complex microbiome data in fermentation and environmental contexts. |
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| | ## 🎓 Education & Community Resources |
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| | We believe in empowering the next generation of engineers and scientists. |
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| | - **(https://github.com/the-ccsn/BUCTthesis):** The official LaTeX templates for bachelor, master, and doctoral theses. |
| | - **Algorithm Training:** Resources and datasets from our ACM/ICPC training camps. |
| | - **Student Innovation:** A showcase of student-led projects, including iGEM competition repositories and undergraduate AI research. |
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| | ## ⚖️ Governance & Licensing |
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| | ### Open Science Commitment |
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| | BUCT is committed to the principles of Open Science. Unless otherwise specified in the model card, all public models and datasets in this organization are released under the **CC-BY-NC 4.0** license (Attribution-NonCommercial). |
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| | ### Responsible AI & Ethics |
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| | We adhere to strict ethical guidelines, particularly concerning the dual-use potential of chemical and biological AI models. |
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| | - **Chemical Safety:** Models provided here must not be used for the design or synthesis of illicit drugs, chemical weapons, or other hazardous materials. |
| | - **Data Privacy:** All medical and industrial datasets hosted here have undergone rigorous anonymization and ethical review. |
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| | ### Contact |
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| | - **Academic Collaboration:** Please contact the principal investigator (PI) listed in the specific model card. |
| | - **General Inquiries:** `opensource [at] buct.edu.cn` (Replace with actual contact) |
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| | This organization is maintained by the community of Beijing University of Chemical Technology. |
