Jing Zhu

About Me

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

News

[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 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

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, Nonlinear Proximity Matrix Embedding (NPME) that includes both proximity-preserving and structural embeddings.

Selected Awards

CSE fellowship, University of Michigan. 2021-2022
Rackham Travel Grant, University of Michigan. Nov. 2021.
SDM Travel Award, Society for Industrial and Applied Mathematics. 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.

Projects

Deep Fuzzy Graph

Advisor: Qiaozhu Mei

Research project, Foreseer Group

Reproduced DeepGraph in Pytorch.

Optimized DeepGraph using multiple Gaussian Functions which mean and variance can be learned by Convolutional Neural Network.

On the Transferability of NeRF Representations

Jing Zhu, Daniel Geng, Sarah Jabbour, Jung Min Lee

Instructor: David Fouhey

Course Project, EECS 542, 2020 Fall.

We investigated if NeRF representations learned from one scene can be helpful to learning presentations for similar scenes

Twitter Semantic Analysis for COVID-19

Yuhang Zhou, Jing Zhu

Instructor: Danai Koutra

Course Project, EECS 476, 2020 Winter.

Hydrated tweets related to COVID-19 from Twitter API. Applied emotion recognition for each tweet and analyzed sentiments in each twitter community.

[report]

Misc

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