关于我 / About Me

我于2018年获得电子科技大学自动化专业学士学位，2021年获得同校计算机科学硕士学位。目前在电子科技大学计算机科学与工程学院攻读博士学位，导师为张彦如教授。我的研究兴趣包括机器学习、联邦学习、大语言模型和智能电网。我在ACM MM等顶级会议和TKDE、TSG、TCSVT等期刊上发表了多篇论文。2023-2024年期间，我在休斯顿大学韩竹教授指导下担任访问学者。

I graduated from the Automation major at the University of Electronic Science and Technology of China (UESTC) in 2018 for my undergraduate degree, and in 2021 I obtained my Master’s degree in Computer Science from the same university. I am currently pursuing the Ph.D. degree under the supervision of Prof. Yanru Zhang with the School of Computer Science and Engineering, UESTC. My research interests include machine learning, federated learning, large language model and smart grid. I have published papers in top conferences such as ACM MM and journals such as TKDE, TSG, and TCSVT. I was a visiting scholar at the University of Houston under the supervision of Prof. Zhu Han during 2023-2024.

我的研究兴趣包括智能电网中的AI应用、推荐系统和机器学习中的多模态技术。我已发表29篇论文，总计谷歌学术引用190+次。

My research interest includes AI in smart grid, Recommendation, and Multi-modal in machine learning. I have published 29 papers with total google scholar citations 190+.

📖 教育经历 / Educations

• 2021.09 – 至今，电子信息博士，电子科技大学，成都，中国
  2021.09 – Present, Ph.D. in Electronic Information, University of Electronic Science and Technology of China (UESTC), Chengdu, China
  导师/Supervisor: 张彦如教授/Prof. Yanru Zhang

• 2023.09 – 2024.09，访问博士生，电气与计算机工程系，休斯顿大学，美国
  2023.09 – 2024.09, Visiting Ph.D. Student, Department of Electrical and Computer Engineering, University of Houston, USA
  导师/Supervisor: 韩竹教授/Prof. Zhu Han (IEEE/ACM Fellow)

• 2018.09 – 2021.06，计算机技术工程硕士，电子科技大学，成都，中国
  2018.09 – 2021.06, M.Eng. in Computer Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China
  导师/Supervisor: 周涛教授/Prof. Tao Zhou

• 2014.03 – 2018.10，自动化工学学士，电子科技大学，成都，中国
  2014.03 – 2018.10, B.Eng. in Automation, University of Electronic Science and Technology of China (UESTC), Chengdu, China

🔍 研究方向 / Research

我目前的研究兴趣主要集中在：
My research interest currently focuses on:

• 智能电网应用中的社会相关信息分析 / Social-related information analysis in smart grid applications
• 智能电网应用中的多模态和大语言模型 / Multi-modal and Large Language Models in smart grid applications
• 时间序列分析 / Time series analysis

🔥 最新动态 / News

• 2025.09:  🎉🎉 我们的两篇论文被顶级期刊录用！“Semantic Communication based on Large Language Model for Underwater Image Transmission”被IEEE Transactions on Mobile Computing (TMC) (🏆CCF A类，中科院一区)录用，“Large Language Model for Socio-Aware Load Forecasting”被IEEE Transactions on Industrial Informatics (TII) (🏆中科院一区)录用！
  Two of our papers have been accepted by top journals! “Semantic Communication based on Large Language Model for Underwater Image Transmission” accepted by IEEE Transactions on Mobile Computing (TMC) (🏆CCF A, 中科院一区), and “Large Language Model for Socio-Aware Load Forecasting” accepted by IEEE Transactions on Industrial Informatics (TII) (🏆中科院一区)!

• 2025.05:  🎉🎉 我们的论文“SocioDiff: A Socio-aware Diffusion Model for Residential Load Data Generation”被IEEE Transactions on Smart Grid (🏆顶级期刊，中科院一区)录用！[数据集和代码]
  Our paper “SocioDiff: A Socio-aware Diffusion Model for Residential Load Data Generation” has been accepted by IEEE Transactions on Smart Grid (🏆Top Journal, 中科院一区)! [dataset and code]

• 2022.04: 我们发布了一个很棒的仓库Awesome Energy LLM papers，专注于大语言模型在能源领域的应用。
  We have released a awesome repo named Awesome Energy LLM papers, focus on applications of LLMs in energy areas.

🎖 荣誉奖项 / Honors and Awards

🏆 科研获奖 / Research Awards

• 2025: 📜 最佳论文奖提名 / Best Paper Award Nomination, IEEE International Conference on Communications (ICC)

🎗️ 荣誉与奖励 / Honors and Scholarships

• 2024: 🏆 最佳表现奖 / Best Performance Prize, ACM MM SMP 2024 International Challenge
• 2024: 🎓 电子科技大学一等奖学金 / First-Class Scholarship, UESTC
• 2023: 🏆 最佳表现奖 / Best Performance Prize, ACM MM SMP 2023 International Challenge
• 2023: 🎓 电子科技大学三等奖学金 / Third-Class Scholarship, UESTC
• 2022: 🏆 最佳表现奖 / Best Performance Prize, ACM MM SMP 2022 International Challenge
• 2022: � “挑战杯”国家级铜奖 / National Bronze Prize, Challenge Cup
• 2022: 🥉 “互联网+”国家级铜奖 / National Bronze Prize, Internet+ Competition
• 2022: 🎓 电子科技大学三等奖学金 / Third-Class Scholarship, UESTC
• 2021: 🌟 成电杰出学生 / Outstanding Student of UESTC
• 2021: 🎖️ 四川省优秀毕业生 / Outstanding Graduate of Sichuan Province
• 2021: 🎓 电子科技大学优秀毕业生 / Outstanding Graduate of UESTC
• 2021: 🏅 国家奖学金 / National Scholarship (China)
• 2021: 🥈 “互联网+”国家级银奖 / National Silver Prize, Internet+ Competition
• 2021: 🦏 腾讯犀牛鸟精英人才培养计划 / Tencent Rhino-Bird Elite Talent Program
• 2021: 🎓 电子科技大学一等奖学金 / First-Class Scholarship, UESTC
• 2020: 🏆 最佳表现奖 / Best Performance Prize, ACM MM SMP 2020 International Challenge
• 2020: 🥈 第二名 / 2nd Place, NeurIPS Procgen Challenge 2020
• 2020: 🥇 第一名 / 1st Place, SIGIR FinIR Challenge 2020
• 2020: 🥇 第一名 / 1st Place, ACM WSDM Cup 2020
• 2020: 🎓 电子科技大学三等奖学金 / Third-Class Scholarship, UESTC
• 2019: 🥇 第一名 / 1st Place, ACM WSDM Cup 2019

💻 工作经历 / Work Experience

• 2022.10 – 2023.09，高级算法工程师 / Senior Algorithm Engineer，TikTok (ByteDance)，北京，中国

  • TikTok.M CapCut粗排优化 / TikTok.M CapCut Coarse Ranking Optimization：对CapCut视频推荐链路进行全面分析，发现CapCut模板视频存在显著低估问题。通过调整value tree并重新设计训练链路目标，CC&TT的DAU提升10.977%，其中CapCut的DAU提升9.527%。
    Conducted comprehensive analysis of CapCut video recommendation pipeline, identified significant underestimation issues in CapCut template videos. By adjusting value tree and redesigning training pipeline objectives, boosted CC&TT DAU by 10.977%, with CapCut DAU increasing by 9.527%.

  • TikTok.MT CapCut精排优化 / TikTok.MT CapCut Fine Ranking Optimization：针对CapCut精准排序模型缺乏可靠估计的问题，在精准排序阶段引入并优化额外精排模型，调整CapCut发表目标预估准确度。最近30天发布量提升0.418%，每用户发布量提升0.457%，每用户发布计数提升1.863%。
    Addressed unreliable estimation issues in CapCut’s fine ranking model by introducing and optimizing an additional fine ranking model, adjusting prediction accuracy for CapCut publishing objectives. Achieved 0.418% increase in recent 30-day publishing volume, 0.457% increase in per-user publishing volume, and 1.863% increase in per-user publishing count.

  • TikTok.MT投稿全链路优化 / TikTok.MT Full-Pipeline Publishing Optimization：分析整个投稿链路中各步骤问题，建立ranking阶段全链路投稿目标模型，提高各环节转化效率。最近30天发布量提升0.877%，每用户发布量提升1.2%，最近7天有效发布天数提升1.816%，每用户有效观看量提升1.327%。
    Analyzed issues in each step of the entire publishing pipeline, established full-pipeline publishing objective model for ranking stage, and improved conversion efficiency at each stage. Achieved 0.877% increase in recent 30-day publishing volume, 1.2% increase in per-user publishing volume, 1.816% increase in effective publishing days in recent 7 days, and 1.327% increase in per-user effective views.

• 2020.03 – 2022.10，算法工程师 / Algorithm Engineer，腾讯微信 / Tencent WeChat，北京，中国

  • 重排离线强化学习优化 / Reranking Offline Reinforcement Learning Optimization：利用列表优化和离线强化学习（offline-RL）提升微信平台长期用户参与度，通过历史和实时数据简化复杂在线学习过程，集成近端策略优化（PPO）特征和无监督学习解决在线偏差和训练偏差。平均用户播放时间提升9.513%，会话播放时间提升4.376%，点击率提升7.789%，参与率提升10.947%。
    Applied list optimization and offline reinforcement learning (offline-RL) to boost long-term user engagement on WeChat platform, simplified complex online learning processes through historical and real-time data, integrated Proximal Policy Optimization (PPO) features and unsupervised learning to address online bias and training bias. Achieved 9.513% increase in average user playtime, 4.376% increase in session playtime, 7.789% increase in CTR, and 10.947% increase in engagement rate.

  • 推荐链路多目标优化 / Multi-objective Optimization for Recommendation Pipeline：基于帕累托优化面提出强化学习模块，为每个用户找到合适的个性化多目标权重，奖励中考虑多个目标梯度的加权和。点击率提升1.63%，用户次日留存率提升0.24%。
    Proposed a reinforcement learning module based on Pareto optimization surface to find appropriate personalized multi-objective weights for each user, with rewards considering weighted sum of multiple objective gradients. Achieved 1.63% increase in CTR and 0.24% increase in next-day user retention.

  • 低活用户优化 / Low-activity User Optimization：针对低活跃用户实施多种策略，设计模型模块嵌入原始推荐模型以减少偏差，通过嵌入融合的MetaId增强用户画像提高模型准确性。次日用户留存率提升0.6%。
    Implemented multiple strategies for low-activity users, designed model modules embedded in original recommendation model to reduce bias, enhanced user profiles through embedding fusion MetaId to improve model accuracy. Achieved 0.6% increase in next-day user retention.

💬 受邀报告 / Invited Talks

• 2024.01, 🎤 AIGC教程：扩散模型介绍 / AIGC Tutorial: An Introduction to Diffusion Model, University of Houston, Texas, USA
  🎥 视频链接/Video Link

📝 学术论文 / Publications

📚 期刊论文 / Journal Publications

已发表 / Published

[1] Weilong Chen, Wenxuan Xu, Haoran Chen, Xinran Zhang, Zhijin Qin, Yanru Zhang, and Zhu Han, “Semantic Communication based on Large Language Model for Underwater Image Transmission”, IEEE Transactions on Mobile Computing (TMC), online. (🏆CCF A, 中科院一区)

[2] Weilong Chen, Xinran Zhang, Ling Zhu, Jian Shi, Zheng Chang, Zhu Han, and Yanru Zhang, “Large Language Model for Socio-Aware Load Forecasting”, IEEE Transactions on Industrial Informatics (TII), online. (🏆中科院一区)

[3] Weilong Chen, Xinru Liu, Xinran Zhang, Jian Shi, Han Yang, Zhu Han, and Yanru Zhang, “SocioDiff: A Socio-Aware Diffusion Model for Residential Electricity Consumption Data Generation“, IEEE Transactions on Smart Grid (TSG), online. (🏆中科院一区)

[4] Weilong Chen, Wenhao Hu, Xiaolu Chen, Weimin Yuan, Yan Wang, Yanru Zhang, “Tri-Modal Transformers with Mixture-of-Modality-Experts for Social Media Prediction“, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 35, no. 2, pp. 1897-1909, Feb. 2025. (🏆中科院一区)

[5] Weilong Chen, Shaoliang Zhang, Ruobing Xie, Feng Xia, Leyu Lin, Xinran Zhang, Yan Wang, and Yanru Zhang, “CIPPO: Contrastive Imitation Proximal Policy Optimization for Recommendation Based on Reinforcement Learning“, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 36, no. 11, pp. 5753-5767, Nov. 2024. (🏆CCF A, 中科院一区)

[6] Weilong Chen, Shengrong Bu, Xinran Zhang, Yanqing Tao, Yanru Zhang, and Zhu Han, “Semi-Supervised Federated Analytics for Heterogeneous Household Characteristics Identification“, IEEE Transactions on Smart Grid, vol. 15, no. 6, pp. 5799-5812, Nov. 2024. (🏆中科院一区)

[7] Weilong Chen, Shengrong Bu, Xinran Zhang, Yanqing Tao, Yanru Zhang, Zhu Han, “Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-Term Load Forecasting in Electricity Wholesale Markets“, IEEE Transactions on Network Science and Engineering, vol. 11, no. 5, pp. 5073-5086, Sept.-Oct. 2024. (🏆中科院一区)

[8] Xinran Zhang, Zheng Chang, Tao Hu, Weilong Chen, Xin Zhang, Geyong Min, “Vehicle Selection and Resource Allocation for Federated Learning-Assisted Vehicular Network“, IEEE Transactions on Mobile Computing (TMC), vol. 23, no. 5, pp. 3817-3829, May 2024. (🏆CCF A, 中科院一区)

[9] Xinran Zhang, Weilong Chen, Hui Zhao, Zheng Chang, Zhu Han, “Joint accuracy and latency optimization for quantized federated learning in vehicular networks“, IEEE Internet of Things Journal, vol. 11, no. 17, pp. 28876-28890, 1 Sept.1, 2024. (中科院二区)

[10] Xinran Zhang, Dan Wang, Yifei Zhu, Weilong Chen, Zheng Chang, Zhu Han, “Zero-Trust Based Robust Federated Learning against Betrayal Behaviors”, IEEE Transactions on Mobile Computing (TMC), online. (🏆CCF A, 中科院一区)

[11] Dingwen Pan, Weilong Chen, Jian Shi, Chenye Wu, Dan Wang, Choong Seon Hong, and Zhu Han, “Bayesian Inference-Aided Large Language Model Agents in Infinitely Repeated Games: A Dynamic Network View”, IEEE Transactions on Network Science and Engineering, online. (中科院二区)

[12] Yu Bai, Yan Wang, Dayuan Qiang, Xin Yuan, Jiehui Wu, Weilong Chen, Sai Zhang, Yanru Zhang, and George Chen, “Identification of nanocomposites agglomerates in scanning electron microscopy images based on semantic segmentation”, IET Nanodielectrics, vol. 5, no. 2, pp. 93–103, 2022.

🎓 会议论文 / Conference Publications

已发表 / Published

[1] Weilong Chen, Jian Shi, Yixin Liang, Ling Zhu, Zheng Chang, Yanru Zhang, and Zhu Han, “Privacy-preserving Socio-Aware Short-Term Residential Load Forecasting”, IEEE International Conference on Communications (ICC), Montreal, Canada, May 2025. (🏆UESTC Class A)

[2] Wenhao Hu, Weilong Chen, Weimin Yuan, Xiaolu Chen, Han Yang, Yanru Zhang, Zhu Han, “Feature Disentangling Dual-stream Network for User Bias Alleviation in Social Media Prediction“, ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India, 2025, pp. 1-5. (CCF B)

[3] Wenhao Hu, Weilong Chen, Weimin Yuan, Yan Wang, Shimin Cai, Yanru Zhang, “Dual-Stream Pre-Training Transformer to Enhance Multimodal Learning for Social Media Prediction“, ACM MM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia, Melbourne VIC, Australia, 2024, pp. 11450–11456. (🏆CCF A)

[4] Xinran Zhang, Dan Wang, Yifei Zhu, Weilong Chen, Zheng Chang and Zhu Han, “When Zero-Trust Meets Federated Learning“, GLOBECOM 2024 - 2024 IEEE Global Communications Conference, Cape Town, South Africa, 2024, pp. 794-799. (🏆UESTC Class A)

[5] Hui Zhao, Xinran Zhang, Weilong Chen, Xiaobin Xu, Li Wang and Zheng Chang, “Multi-dimensional Resource Allocation in HAP-assisted UAV Wireless Networks for IoRT Data Collection”, IEEE Global Communications Conference (GLOBECOM), Cape Town, South Africa, Dec. 2024. (🏆UESTC Class A)

[6] Xiaolu Chen, Weilong Chen, Chenghao Huang, Zhongjian Zhang, Lixin Duan, Yanru Zhang, “Double-Fine-Tuning Multi-Objective Vision-and-Language Transformer for Social Media Popularity Prediction“, ACM MM 2023 - Proceedings of the 31st ACM International Conference on Multimedia, Ottawa ON, Canada, 2023, pp. 9462–9466. (🏆CCF A)

[7] Weilong Chen, Chenghao Huang, Weimin Yuan, Xiaolu Chen, Wenhao Hu, Xinran Zhang, Yanru Zhang, “Title-and-tag contrastive vision-and-language transformer for social media popularity prediction“, ACM MM 2022 - Proceedings of the 30th ACM International Conference on Multimedia, Lisboa, Portugal, 2022, pp. 7008–7012. (🏆CCF A)

[8] Chenghao Huang, Weilong Chen, Xiaoyi Wang, Feng Hong, Shunji Yang, Yuxi Chen, Shengrong Bu, Yanru Zhang, “DearFSAC: A DRL-based Robust Design for Power Demand Forecasting in Federated Smart Grid”, IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 2022. (🏆UESTC Class A)

[9] Weilong Chen, Feng Hong, Chenghao Huang, Shaoliang Zhang, Rui Wang, Ruobing Xie, Feng Xia, Leyu Lin, Yanru Zhang, Yan Wang, “Curriculum Learning for Wide Multimedia-Based Transformer with Graph Target Detection”, ACM International Conference on Multimedia (MM), Seattle, WA, Oct. 2020. (🏆CCF A)

[10] Weilong Chen, Peng Wang, Jipeng Li, Yuanshuai Zheng, Yan Wang, Yanru Zhang, “Ferryman at SemEval-2020 Task 12: BERT-Based Model with Advanced Improvement Methods for Multilingual Offensive Language Identification”, 13th International Workshop on Semantic Evaluation (SemEval), Barcelona, Spain, Dec. 2020.

[11] Weilong Chen, Yan Zhuang, Peng Wang, Feng Hong, Yan Wang, Yanru Zhang, “Ferryman as SemEval-2020 Task 5: Optimized BERT for Detecting Counterfactuals”, 13th International Workshop on Semantic Evaluation (SemEval), Barcelona, Spain, Dec. 2020.

[12] Weilong Chen, Jipeng Li, Chenghao Huang, Wei Bai, Yanru Zhang, Yan Wang, “Ferryman at SemEval-2020 Task 7: Ensemble Model for Assessing Humor in Edited News Headlines”, 13th International Workshop on Semantic Evaluation (SemEval), Barcelona, Spain, Dec. 2020.

[13] Weilong Chen, Xin Yuan, Sai Zhang, Jiehui Wu, Yanru Zhang, Yan Wang, “Ferryman at SemEval-2020 Task 3: Bert with TFIDF-Weighting for Predicting the Effect of Context in Word Similarity”, 13th International Workshop on Semantic Evaluation (SemEval), Barcelona, Spain, Dec. 2020.

[14] Weilong Chen, Shuaipeng Liu, Wei Bao, Huixing Jiang, “An effective approach for citation intent recognition based on BERT and lightGBM”, Web Search and Data Mining Cup, WSDM CUP’2020.

[15] Wei Bao, Weilong Chen, Wei Bai, Yan Zhuang, Mingyuan Cheng, Xiangyu Ma, “Will_go at SemEval-2020 Task 9: An Accurate Approach for Sentiment Analysis on Hindi-English Tweets Based on Bert and Pesudo Label Strategy”, Proceedings of the Fourteenth Workshop on Semantic Evaluation, Semeval’2020, Barcelona, 2020.

[16] Wu Qi, Weilong Chen, Wei Bao, Jipeng Li, Peikai Pan, Qiyao Peng, Pengfei Jiao, “Tree-based model with advanced data preprocessing for large scale hard disk failure prediction”, AI Ops Competition, 2020.

[17] Qidi Xu, Haocheng Xu, Weilong Chen, Chaojun Han, Haoyang Li, Wenxin Tan, Fumin Shen, Heng Tao Shen, “Time-aware Session Embedding for Click-Through-Rate Prediction”, ACM International Conference on Multimedia (MM), Nice France, 2019. (*Equal contribution) (🏆CCF A)

📈 统计 / Statistics: 已发表期刊论文 12 篇，会议论文 17 篇
Total: 12 published journal papers, 17 published conference papers

📊 更多论文请访问 Google Scholar / More papers available on Google Scholar

📝 留言板 / Guestbook

欢迎在这里留言！无论是学术交流、合作咨询，还是简单的问候，我都很乐意收到您的消息。我会定期查看留言并尽快回复。

Welcome to leave your message here! Whether it’s academic exchange, collaboration inquiry, or just a simple greeting, I’m happy to receive your message. I will check messages regularly and reply as soon as possible.

📮 如何联系我 / How to Contact Me

• 📧 邮箱 / Email: chenweilong921@gmail.com
• 🎓 Google Scholar: 我的学术主页 / My Academic Profile
• 💻 GitHub: github.com/chenweilong915

💬 留言须知 / Message Guidelines

• 请保持友善和尊重的态度 / Please maintain a friendly and respectful attitude
• 学术交流和合作咨询都很欢迎 / Academic exchanges and collaboration inquiries are welcome
• 留言会在审核后显示 / Comments will be displayed after moderation
• 我会通过邮件回复重要的留言 / I will reply to important messages via email