2023.09: Our work on "Emerging drug interaction prediction" has been accepted to Nat. Comp. Sci.
2023.09: Our work on "Hyper-parameter Optimization" has been accepted to NeurIPS-2023.
2023.08: I will serve as an Area Chair for ICLR-2024.
2023.08: Our paper on "Positive-Unlabeled Node Classification" is accepted to CIKM-2023.
2023.07: We got new funding support from Tencent AI-Lab Open Fund.
2023.07: I gave a talk on "AI4Science: Automated Graph Learning" at Southwest University.
2023.06: Group member Shiguang Wu received Excellent Graduation Thesis from Tsinghua University.
2023.06: I gave a talk on "AI4Science: Automated Graph Learning" in JSCC 2023.
2023.05: I gave a talk on "LLM for Structured-data" in penal discussion of "Academic Forum for Young Teachers".
2023.05: Two papers on "Automated Molecular Pre-training/Efficient KG Reasoning" are accepted to KDD-2023.
2023.05: I am honored to received "Aharon Katzir Young Investigator Award" (by INNS).
2023.05: I will serve as an Area Chair for ACML-2023.
2023.04: Our paper on "Graph Attack" is accepted to ICML-2023.
2023.03: I will serve as an Area Chair for NeurIPS-2023.
2023.02: I gave a talk on "Automated Graph Learning" at "Educational Development Thinking".
2023.02: Our paper on "Graph Simulation" is accepted to WebConf-2023 (social good track).
2023.01: Two papers on "Neural Architecture Search/Few-shot Learning" are accepted to WebConf-2023.
2023.01: Two papers on "Symbolic Models/Federated Learning" are accepted to ICLR-2023.
2023.01: Our paper on "benchmarking spatio-temporal prediction" is accepted to TMLR.
2023.01: Our paper on "NAS for graph pooling" is accepted to TOIS.
2022.12: I will serve as an Area Chair for ICML-2023.
2022.12: Our project on "Autonomous learning from graphs" gets supports from NSF.
2022.11: I gave a talk on "From Automated to Autonomous Machine Learning" at GAOLING School of AI, RENMING University.
2022.10: I was honored to be on the Advisory Board of ACML 2022 Workshop Weakly Supervised Learning.
2022.10: Two papers on "AutoML/Knowledge Graph/Few-shot Learning" are accepted to EMNLP-2022.
2022.09: I was appointed as a young editor of "CAAI TRIT" (JCR top ranked).
2022.09: I was invited to give a talk on "Autonomously Knowledge Graph Learning" at "CCF Task Force on Big Data" Seminar.
2022.08: Our paper introduces "NAS into scene text recognition" is accepted to TPAMI.
2022.08: I will serve as an Area Chair for ICLR-2023.
2022.08: I was elected as one of editorial member of Machine Learning journal.
2022.07: I gave an invited talk on Young Scholars Forum of CCDM-2022.
2022.07: I will serve as a Senior Program Committee (SPC) for AAAI-2023.
2022.07: Our paper TPAMI 2021 on "hyperspectral image" is recognized as "ESI highly cited paper".
2022.07: I was invited to give a talk on "Automated Knowledge Graph Learning" at RIKEN AIP Seminar.
2022.07: One paper on "NAS for Hyper-spectral Image" is accepted to ECCV-2022.
2022.07: Team member Mr. Lin Li received "Excellent Graduation Thesis of Tsinghua University".
2022.06: I gave a lecture on "Automated Machine Learning" in the "CCF Advanced Disciplines Lectures".
2022.06: Our method AutoBLM won the 1st place on OGB leadboard (ogbl-biokg).
2022.05: I was invited to give a talk at Tsinghus-USC Faculty Joint Forum.
2022.05: One paper analyzes "statistical RPCA" is accepted to ICML.
2022.05: One paper deploys "benchmark on meta-level" is accepted to Cell Patterns.
2022.05: I will serve as an Area Chair for ACML-2022.
2022.05: Our method PAR won the 1st place on OGB leadboard (ogbg-molhiv and ogbg-ppa).
2022.05: I was identified as "Global Top Chinese New Stars in Machine Learning".
2022.04: Mr.Hongyu Ren (Ph.D.@Stanford) and Ms.Meiqi Zhu (Ph.D.@BPTU) give us talks on "Graph Neural Networks".
2022.04: One paper analyzes "statistical low-rank tensor learning" is accepted to JMLR.
2022.03: I will serve as an Area Chair for NeurIPS-2022.
2022.03: One paper on "AutoML for knowledge graph" is accepted to TPAMI.
2022.02: One paper on "hyper-parameter tuning" is accepted to ACL-2022.
2022.02: We are holding "AutoGraph tutorial" in AAAI-2022.
2022.02: I was invited as a Reviewer of Transactions on Machine Learning Research (TMLR).
2022.01: One paper on "knowledge graph" is accepted to WebConf-2022.
2022.01: I was awarded as a "honorary lecturer" by 4Paradigm Inc.
2022.01: I serve as an associate editor of Neural Network.
2021.12: I give an invited talk "Few-shot molecular property prediction" on BAAI Live.
2021.12: Mr. Wentao Zhang (Ph.D. student@PKU) gives us a talk on "Scalable Graph Learning".
2021.12: Dr. Shuxin Zheng (senior researcher@MSRA) gives us a talk on "Graph Transformer".
2021.12: I will serve as an Area Chair of ICML-2022.
2021.11: We are hosting "noisy label learning" and "automated graph learning" tutorial in ACML 2022.
2021.11: Dr. Guohao Dai (Assistant Researcher@EE Tsinghua) gives us a talk on "Sparse Graph Processing Framework".
2021.10: I was selected as one of Hurun China Under 30s To Watch 2021.
2021.10: I give an invited talk "automated learning from knowledge graph" in workshop of VALSE 2022.
2021.10: We are hosting "recent advance in machine learning" workshop in VALSE 2022.
2021.10: One papers on "hypergraph convolutional networks" is accepted to ICDE 2022.
2021.09: Three papers (few-shot learning / graph neural network / neural architecture search) are accepted to NeurIPS 2021.
2021.09: Dr. Muhan Zhang (Assistant Prof at PKU) gives us a talk on "Graph Neural Network".
2021.09: I was recognized as an "Outstanding Reviewer" (top 5%) of ICCV 2021.
2021.08: One paper on "Few-shot Text Classification" is accepted to EMNLP-2021.
2021.08: We are holding AutoML tutorial, noisy label learning tutorial/workshop in IJCAI-2021.
2021.08: One paper on "AutoML/NAS for GNN" is accepted to CIKM-2021.
2021.08: I will serve as a Senior Program Committee (SPC) for AAAI-2022.
2021.07: Three papers (KDD-2017, NeurIPS-2018, CSUR-2020) are marked as top cited papers (Google Scholar Metrics 2021).
2021.07: Our CSUR-2020 paper is elected as an ESI highly cited paper.
2021.07: Dr. Yangqiu Song (Assistant Prof@CSE HKUST) gives us a talk on "Federated Knowledge Graph Embedding".
2021.06: Mr. Yaodong Yu (Ph.D student at UC Berkeley) gives us a talk on "Generalization in Deep Networks".
2021.06: Mr. Xiangning Chen (Ph.D student at UCLA) gives us a talk on "Neural Architecture Search".
2021.06: I will serve as an Area Chair for ICLR-2022.
2021.06: I am moving to Department of Electronic Engineering@Tsinghua University as an Assistant Professor.
2021.05: I was invited to give a talk about AutoML at Information and Electron College@BIT.
2021.05: Two AutoML papers on "collaborative filtering" and "graph neural network" are accepted by KDD.
2021.05: Dr. Yisen Wang (Assistant Prof@PKU) gives us a talk on "Unlearnable Examples".
2021.05: I was elected as an executive area chair of VALSE in 2021.
2021.04: I was recognized as the top-3 author in WebConf 2021.
2021.04: Our AutoML method (AutoSF, ICDE 2020) for KG learning ranks 1st in OGB benchmark.
2021.04: Mr. Rex (Zhitao) Ying (Ph.D student at Stanford) gives us a talk on "Learning to simulate using GNN".
2021.04: Dr. Hengshuang Zhao (Post-doc at Oxford) gives us a talk on "Advancing Visual Intelligence via Neural System Design".
2021.04: We are hosting "Weakly-supervised Learning Special issue" on Machine Learning Journal.
2021.03: We are hosting "Weakly-supervised Learning Workshop@IJCAI-2021".
2021.03: Mr. Xuanyi Dong (Ph.D. student at UTS) gives us a talk on "Neural Architecture Search".
2021.02: I was awarded as "Best Innovator" (4Paradigm. Inc).
2021.01: Three papers on "AutoML", "knowledge graph" and "low-rank optimization", are accepted by WebConf.
2020.12: I was awarded as "Young Scientist Awards" by "Hong Kong Institution of Science".
2020.12: One paper on "Heterogeneous Information Networks" is accepted to TKDD.
2020.11: I was selected as one of "Forbes 30 Under 30" (China).
2020.11: Dr. Wenhui Yu (Ph.D., Tsinghua) gives us a talk on "Graph Convolutional Network for Collaborative Filters".
2020.11: I was invited to give a talk at "之江国际青年人才论坛".
2020.11: Dr. Hao Wang (assistant professor, CSE, Rutgers) gives us a talk on "Bayesian Deep Learning".
2020.10: Two paper on "AutoML for Graph Neural Networks" and "AutoML for Knowledge Graph" are accepted to ICDE.
2020.09: Two paper on "Robust Collaborative Filtering" and "AutoML for Knowledge Graph" are accepted to NeurIPS.
2020.09: One paper on "Hyperspectral image" is accepted to TPAMI.
2020.09: Dr. Ruiming Tang (Senior Researcher, Huawei Noah's Ark Lab) gives us a talk on "Recommendation System".
2020.09: One paper on "Negative sampling for knowledge graph" is accepted to VLDBJ.
2020.08: Dr. Bo Han (Assistant Professor, CSE, HKBU) gives us a talk on "Trustworthy Representation Learning".
2020.08: I will serve as a Senior Program Committee for AAAI-2021.
2020.08: I will serve as an Area Chair for IJCAI-2021.
2020.07: Dr. Yisen Wang (Ph.D, Tsinghua) gives us a talk on "Min-max problem in Adversarial Learning".
2020.07: Mr. Xiangning Chen (Ph.D. student, UCLA) gives us a talk on "robustness in NAS".
2020.07: One paper on "NAS for text recognition" is accepted to ECCV.
2020.06: Mr. Weihua Hu (Ph.D. student, CSE, Stanford) gives us a talk on "Learning from Complex Relational Data".
2020.06: We are holding "KDD 2020 Tutorial: Advances in Recommender Systems", welcome to attend!
2020.06: Two papers on "AutoML in Noisy Label Learning" are accepted to ICML.
2020.05: I give a tutorial on AutoML at deep learning course (post-graduate level) in Peking University.
2020.05: Prof. Xinggang Wang (Asso. Prof, ECE, HUST) gives us a talk on "Object detection".
2020.04: We are hosting KDD Cup 2020 AutoGraph Challenge, welcome to join and play.
2020.03: One survey on "few-shot learning" is accepted to ACM CSUR.
2020.02: We are organizing "Tensor Network Representations in Machine Learning@IJCAI-2020", welcome to attend.
2020.02: One paper is accepted by ICDE: "AutoML for Knowledge Graph Embedding".
2020.01: Dr. Tongliang Liu (Assistant Professor, CSE, University of Sydney) gives us a talk on "Weakly-supervised Learning".
2020.01: Two papers are accepted by WWW: "AutoML for Collaborative Filtering" and "Generalizing Knowledge Graph Completion".
2020.01: Mr. Zhitao (Rex) Ying (Ph.D. student, CSE, Stanford) gives us a talk on "Graph Neural Network".
2020.01: I will serve as a Senior Program Committee for IJCAI-2020.
2019.12: Prof.Chuan Shi (CSE, BUPT) gives a talk on "Heterogeneous Information Network".
2019.12: I give an invited talk at "Young Scientist Forum @ Annual Meeting of China's Artificial Intelligence".
2019.11: Our faster optimization algorithm for neural architecture search (NAS) is accepted to AAAI-2020.
2019.11: We are organizing Weakly-supervised and Unsupervised Learning Workshop@SDM20, welcome to attend.
2019.10: Our intern Hansi's work receives Best Paper Awards on WSL Workshop@ACML19.
2019.10: I receive Wunwen Jun Prize for Excellence Youth of Artificial Intelligence (issued by CAAI).
2019.10: I give an invited talk at NJUTS on "AutoML for Knowledge Graph Embedding".
2019.09: We are organizing AutoML competition on Weakly-supervised Learning@ACML19, welcome to play.
2019.09: I will serve as a guest editor of "AutoML Special Issue on TPAMI".
2019.09: We are organizing Weakly-supervised Learning Workshop@ACML19, welcome to attend.
2019.08: Our paper "MPGCN" which uses GCN for the traffic prediction is accepted to ICDE-2020.
2019.08: I will serve as a Senior Program Committee for AAAI-2020. Thanks for the invitation.
2019.07: Assistant Prof. Yangqiu Song (CSE, HKUST) gives a talk on "Knowledge graph".
2019.07: Our group receives a new member. Welcome, Dr. Huan Zhao.
2019.07: Our intern Xiangning's work on collaborative filtering receives "Excellence undergraduate thesis" from Tsinghua University.
2019.06: Dr. Yisen Wang gives a talk on "Adversarial Machine Learning".
2019.06: Our paper on "robust semi-definite programming" is accepted to IJCAI-2019.
2019.06: Our paper on "cross-organizational diabetes prediction (with a differential privacy guarantee)" is accepted to IJCAI-2019.
2019.05: I received Ph.D. Research Excellence Award (1st runner) from HKUST.
2019.05: Fengli Xu (Ph.D. student@Tsinghua) gives a talk on "Privacy-preserving Spatiotemporal Big Data Analytic".
2019.05: Our paper "SparseHMM" modeling trajectory sequence is accepted to KDD-2019 (research track).
2019.05: Our paper "AutoCross" which proposes AutoML techniques in feature engineering is accepted to KDD-2019 (industrial track).
2019.05: Our paper "NORT" (studies the fundamental tensor regularization techniques) is accepted to ICML-2019.
2019.03: Our paper "NGMeet" is accepted to CVPR-2019 by oral presentation; try our new model for hyper-spectral image.
2019.02: Our paper "NSCaching" is accepted to ICDE-2019; try our new negative sampling method for knowledge graph embedding.