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.

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.