I am Jing Zhu, an incoming second year PhD student at the University of Michigan. My advisor is Danai Koutra. My primary research interest lies in knowledge graphs.

• CV

News

• [2022/09] "Touch and Go: Learning from Human-Collected Vision and Touch is accepted at Neurips'22!
• [2022/08] "CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment is accepted at CIKM'22!
• [2021/11] I will join the DGL group as an applied scientist intern in the upcoming summer!
• [2021/08] "NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases is accepted at EMNLP'21!
• [2020/12] "Node Proximity Is All You Need: A Unified Framework for Proximity-Preserving and Structural Node and Graph Embedding." is accepted at SDM'21!

Publications

Touch and Go: Learning from Human-Collected Vision and Touch. [link]

Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu, Wenzhen Yuan, Andrew Owens

Neural Information Processing Systems (Neurips 22 Dataset and Benchmark)

We propose Touch and Go: a multimodal visuo-tactile learning dataset which tries to associate sight with touch to understand material properties

CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment. [link]

Jing Zhu, Danai Koutra, Mark Heimann

International Conference on Information and Knowledge Management (CIKM 22)

We propose CAPER, a multilevel alignment framework that improves upon existing alignment algorithms by enforcing alignment consistency across multiple graph resolutions.

NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases. [link]

Tara Safavi, Jing Zhu, Danai Koutra

The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 21, acceptance rate 25.6%)

We propose NegatER, the first Unsupervised framework that ranks potential negatives in commonsense KBs using a contextual language model (LM).

Node Proximity Is All You Need: A Unified Framework for Proximity-Preserving and Structural Node and Graph Embedding. [link]

Jing Zhu*, Xingyu Lu*, Mark Heimann, Danai Koutra

SIAM International Conference on Data Mining (SDM 21, acceptance rate 21%)

We present the first unified framework of node embedding (PhUSION) that includes both proximity-preserving and structural embeddings.

Selected Awards

• CIKM Travel Award, SIGIR. Oct. 2022
• KDD Travel Award, SIGKDD. Aug. 2022
• CSE fellowship, University of Michigan. 2021-2022
• Rackham Travel Grant, University of Michigan. Nov. 2021.
• SDM Travel Award, SIAM. Apr. 2021.
• James B. Angell Scholar, University of Michigan. Mar. 2021.
• Jackson and Muriel Lum Scholarship, University of Michigan. 2019-2021
• Excellent Undergraduate Scholarship, Shanghai Jiao Tong University. Nov. 2018, Nov. 2019.

Teaching

• EECS476 Data Mining, University of Michigan. 2021 Winter.
• EECS496 Major Design Experience-Professionalism, University of Michigan. 2020 Fall.
• VV285 Honors Mathematics III, Shanghai Jiao Tong University. 2019 Summer.
• VV186 Honors Mathematics II, Shanghai Jiao Tong University. 2018 Fall.

Misc

• I would love to help minority students in CS research. Feel free to reach out if you need anything.