Baichuan Zhang (张百川)


About Me

I am a Research Scientist at Facebook HQ. I obtained my PhD degree from Computer Science Department in Purdue University, West Lafayette. I am fortunately advised by Professor Mohammad Al Hasan and Professor Christopher W. Clifton. My research interest includes developing novel data mining and machine learning algorithms for applications in various domains, such as distributed representation learning on textual and graph units, information retrieval, recommendation system, and data privacy. Before that, I got my Bachelor degree in Electrical Engineering from East China University of Science and Technology in May 2012.




Recent News
  • 09/2018: I am invited to serve in the Program Committee of SDM'19, ICWSM'19
  • 08/2018: One full paper got accepted in CIKM'18 industry track
  • 07/2018: I am invited to serve in the Program Committee of AAAI'19
  • 04/2018: I am invited to serve in the Program Committees of CIKM'18
  • 02/2018: I joined Facebook HQ as a research scientist with machine learning and ranking focuses
  • 01/2018: I am invited to serve in the Program Committees of KDD'18 (Research Track), SIGIR'18 (Application Track), IJCAI'18, ICWSM'18
  • 12/2017: Paper titled "Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications" accepted to Social Network Analysis and Mining
  • 11/2017: I successfully defended my PhD thesis
  • 08/2017: Paper titled "Name Disambiguation in Anonymized Graphs using Network Embedding" accepted in CIKM 2017 as a research track full paper
  • 05/2017: Started summer internship in Facebook Seattle with ads ranking team
  • 04/2017: Paper titled "Feature Selection for Classification under Anonymity Constraint" accepted in Transactions on Data Privacy
  • 01/2017: My work of online name disambiguation has been featured by Yahoo Technology. Media coverage is available from here

Publications

(Google Scholar)

    

  • Vachik Dave, Baichuan Zhang, Mohammad Al Hasan, Khalifeh Al Jadda, Mohammed Korayem: A combined representation learning approach for better job and skill recommendation, in CIKM 2018
      • Vachik Dave, Mohammad Al Hasan, Baichuan Zhang, Chandan Reddy: Predicting Interval Time for Reciprocal Link Creation using Survival Analysis, in Social Network Analysis and Mining, 2018.
      • Pin-Yu Chen, Baichuan Zhang, and Mohammad Al Hasan: Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications, in Social Network Analysis and Mining, 2017, PDF
      • Baichuan Zhang, and Mohammad Al Hasan: Name Disambiguation in Anonymized Graphs using Network Embedding, in CIKM 2017 Proceedings of the 26th ACM International Conference on Information and Knowledge Management, Singapore. Research Track Full Paper. Research track full paper acceptance rate=20% (171 out of 855) PDF
      • Baichuan Zhang, Noman Mohammed, Vachik Dave, and Mohammad Al Hasan: Feature Selection for Classification under Anonymity Constraint, in Transactions on Data Privacy, 2017, PDF
      • Baichuan Zhang, Murat Dundar, and Mohammad Al Hasan: Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams, in CIKM 2016 Proceedings of the 25th ACM International Conference on Information and Knowledge Management, Indianapolis, IN. Research Track Full Paper. Research track full paper acceptance rate=22.8% (160 out of 701) PDF
      • Sutanay Choudhury, Khushbu Agarwal, Sumit Purohit, Baichuan Zhang, Meg Pirrung, Will Smith, and Mathew Thomas: NOUS: Construction and Querying of Dynamic Knowledge Graphs, IEEE International Conference on Data Engineering (ICDE) 2017, PDF
      • Pin-Yu Chen, Baichuan Zhang, Mohammad Al Hasan, and Alfred Hero: Incremental Method for Spectral Clustering of Increasing Orders, in KDD Workshop on Mining and Learning with Graphs (MLG 2016), San Francisco, CA.  PDF
      • Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan, Xia Ning, Khushbu Agarwal, Sumit Purohit, and Paola Pesntez Cabrera: Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs, in SDM Workshop on Mining Networks and Graphs (MNG 2016), Miami, FL. PDF
      • Murat Dundar, Qiang Kou, Baichuan Zhang, Yicheng He, and Bartek Rajwa: Simplicity of Kmeans versus Deepness of Deep Learning: A Case of Unsupervised Feature Learning with Limited Data, in IEEE International Conference on Machine Learning Applications, 2015, Miami, FL. PDF
      • Baichuan Zhang, Tanay Kumar Saha, and Mohammad Al Hasan: Name Disambiguation from link data in a collaboration graph using temporal and topological features, in Social Network Analysis and Mining, 2015, PDF
      • Baichuan Zhang, Tanay Kumar Saha, and Mohammad Al Hasan: Name Disambiguation from link data in a collaboration graph, in 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM Beijing, China. Research Track Short Paper. PDF

      Industrial Experience

      • 02/2018 - Present: Research Scientist, Facebook HQ, Menlo Park CA
      • 05/2017-08/2017: Software Engineering PhD Intern, Ads Ranking Team, Facebook, Seattle WA
      • 05/2016-08/2016: Big Data Engineer Intern, Apache Spark Team, Hortonworks, Santa Clara CA
      • 05/2015-08/2015: Research Intern, Pacific Northwest National Laboratory, Richland WA


      Professional Service

      • Program Committee Member: AAAI'19, SDM'19, ICWSM'19, CIKM'18, KDD'18, SIGIR'18, IJCAI'18, ICWSM'18, WWW-BigNet'18, IEEE Big Data-BigGraphs'17
      • Invited Journal Review: TKDE, TKDD, KAIS, TIST, TWEB, DMKD, SADM, SNAM, TBD, JCST

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