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The PhD Forum will highlight work of PhD and PhD-bound Masters students, which will become the core of their thesis. It spans various topics of data mining and related fields such as machine learning, artificial intelligence, statistics, databases, information retrieval, social media analysis, and multimedia and web mining. It also spans application areas of data mining, such as bioinformatics, healthcare informatics, urban informatics, and science informatics.

presentation topics During the workshop, invited students will give long and short presentations on their work, while researchers with experience in supervising and examining doctoral students will participate and provide feedback to the participants. This year we will also have two exciting panels with well-known, successful panelists who will be discussing topics that are relevant to PhDs or PhD-bound students. Moreover, to encourage networking and help the invited students grow their professional networks, the forum will feature a (structured) networking session.

The workshop, except for the networking session, is open to anyone who is interested!

Co-chairs (bios): Danai Koutra, University of Michigan    &    Bo Jin, Dalian University of Technology


  • Student Presentations I (9-10am)

    Long Papers (15 min talk + 5 min Q&A):

    • SP34205: Development of an Interpretable Neural Network Model for Creation of Polarity Concept Dictionaries.
      Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi, Kota Tsubouchi, and Tatsuo Yamashita.
    • SP34210: Deep Learning for Pulmonary Nodule CT Image Retrieval - An Online Assistance System for Novice Radiologists.
      Daniel Perez, Joan Dayanghirang, Shengli Wang, Zezhong Zheng, Yuzhong Shen, and Jiang Li.
    Short Paper (7 min talk + 3 min Q&A):
    • SP34206: Network Embedding with Centrality Information.
      Yao Ma and Jiliang Tang.
    • SP34212: Aggregation and Disaggregation of Information : A Holistic View.
      Yuyue Chen and Chuanren Liu.

  • Student Presentations II (11:15-11:45am)

    Long Paper (15 min talk + 5 min Q&A):

    • SP34211: Crowdsourcing Data Science for Innovation
      Wangcheng Yan and Wenjun Zhou.
    Short Paper (7 min talk + 3 min Q&A):
    • SP34208: Uncovering Teamwork in Networks -- Prediction, Optimization and Explanation.
      Liangyue Li and Hanghang Tong.

  • Student Presentations III (2-3pm)

    Long Papers (15 min talk + 5 min Q&A):

    • SP34214: Dependency anomaly detection for heterogeneous time series: A Granger-Lasso approach.
      Sahar Behzadi Soheil, Katerina Schindlerova, and Claudia Plant.
    • SP34215: Deep Learning Solutions to Computational Phenotyping in Health Care.
      Zhengping Che and Yan Liu.
    Short Papers (7 min talk + 3 min Q&A):
    • SP34213: Future weight prediction: an ensemble learning approach.
      Zhiwei Wang and Jiliang Tang.


Danai KoutraDanai Koutra is an Assistant Professor in Computer Science and Engineering at University of Michigan, where she leads the Graph Exploration and Mining at Scale (GEMS) Lab. Her research focuses on methods for exploring large-scale graphs, including graph summarization, graph similarity, network alignment, and anomaly detection. She won the 2016 ACM SIGKDD Dissertation award, and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She holds one ``rate-1'' patent and has six (pending) patents on bipartite graph alignment; has multiple papers in top data mining conferences, including 2 award-winning papers; and her work has been covered by the popular press, such as the MIT Technology Review. She earned her Ph.D. and M.S. in Computer Science from CMU in 2015. She is serving as secretary of the SIAM Activity Group on Data Mining and Analytics, and has co-organized 2 tutorials on graph similarity and alignment.

Bo JinBo Jin is an Associate Professor at Dalian University of Technology. Prof. Bo Jin received his Ph.D. degree in computer science from Dalian University of Technology in 2009. He is currently an Associate Professor at the Dalian University of Technology. He has a research experience in Rutgers University with Prof. Hui Xiong. His research interests include data mining and big data analytics. He has published prolifically in refereed journals and conference proceedings, such as JMIR, ACM SIGKDD, AAAI, IEEE ICDM, and SIAM SDM. Prof. Bo Jin has served in the following conferences as Program Committee Member: IEEE ICDM (2014-2016), ACM KDD (2016), SIAM SDM (2015-2016), DASFAA (2016), etc. He served in ICDM 2017 as PhD Forum Co-chair.