I am a Ph.D. student in computer science at Stanford University working on machine learning and computational biology. I am very fortunate to be advised by Aaron Newman and Emma Lundberg. My research focuses on the intersection of deep learning, single-cell and spatial genomics, transcriptomics and proteomics. My aim is to build computational tools to investigate molecular and cellular compositions of human tissues and cells, and understand disease mechanisms, and ultimately apply these tools and insights in pharmaceutical and clinical settings. Previously I have also worked on graph representation learning, natural language processing and regulatory genomics with Jure Leskovec and Anshul Kundaje.

Before Stanford, I was an AI Resident at Google Research working with Michael Collins on pretraining multimodal vision+language models. I was also a research intern at Google Research in summer 2019 working with Dan Roth and Ian Tenney on probing pretrained language models.

I received my B.S. in computer science at UIUC in 2019. I did research with Jiawei Han on data mining and heterogenous graph representation learning.

xikunz2@cs.[university].edu Google Scholar Profile Resume GitHub LinkedIn Twitter

Selected Publications

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering
Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D Manning, Jure Leskovec
ICLR 2022 (Spotlight, Top 5%)
PDF Abstract Bibtex Code Video

On the opportunities and risks of foundation models
Rishi Bommasani, …, Xikun Zhang, …, Percy Liang (116 authors)
arXiv 2021
PDF Abstract Bibtex Website

Do Language Embeddings Capture Scales?
Xikun Zhang*, Deepak Ramachandran*, Ian Tenney, Yanai Elazar, Dan Roth (*equal contribution)
Findings of EMNLP 2020
EMNLP BlackboxNLP workshop 2020

PDF Abstract Bibtex Code Blog

Predicting Embedding Trajectories for Temporal Interaction Networks
Srijan Kumar, Xikun Zhang, Jure Leskovec
KDD 2019 (Oral, Top 9%)
PDF Abstract Bibtex Code Website Video

Other Publications

Deep Bidirectional Language-Knowledge Graph Pretraining
Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang*, Jure Leskovec* (*equal contribution)
NeurIPS 2022
AAAI DLG workshop 2023 (Best Paper Award)

PDF Abstract Bibtex Code

CLEVRER-Humans: Describing Physical and Causal Events the Human Way
Jiayuan Mao*, Xuelin Yang*, Xikun Zhang, Noah Goodman, Jiajun Wu (*equal contribution)
NeurIPS Datasets and Benchmarks Track 2022
PDF Abstract Bibtex Code Website

Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery
Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han
PDF Abstract Bibtex Code

TruePIE: Discovering Reliable Patterns in Pattern-Based Information Extraction
Qi Li*, Meng Jiang*, Xikun Zhang, Meng Qu, Timothy Hanratty, Jing Gao, Jiawei Han (*equal contribution)
KDD 2018 (Long Presentation, Top 11%)
PDF Abstract Bibtex Code Video

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