Ruocheng Guo

rguo12 at asu dot edu

Ruocheng Guo (Chinese ) is a final year Ph.D. student @ Arizona State University, now he is affiliated with Data Mining and Machine Learning Lab, under supervision of Prof. Huan Liu.

Research Interests: Causal Inference, Machine Learning, and Data Mining.

Actively looking for tenure-track faculty and industrial reseacher positions.

[CV]

[Research Statement]

[Teaching Statement]

[Diversity Statement]

Interested in Causal Inference? Please check out our survey and algorithm/data repositories!

Biography

Ruocheng is an AI resident @ X, the moonshot factory working on a confidential early stage project during 2020 fall.

Ruocheng was a research intern @ Microsoft Research working with Emre Kiciman and Pengchuan Zhang during 2020 summer. The project is on learning causal features for out-of-distribution predictions.

Ruocheng was a research intern @ Etsy Data Science working with Liangjie Hong , Xiaoting Zhao and Adam Henderson during 2019 summer. The intern project leads to the KDD 2020 paper "Debiasing Grid-based Product Search for E-commerce".

Before joining ASU, Ruocheng received M.Sc degree in Electronic Engineering from Hong Kong University of Science and Technology in Hong Kong, China and

B.Eng degree in Electrical Engineering from Huazhong University of Science and Technology in Wuhan, China.

News

  • [Nov 2020] Invited to serve as a PC of SIGKDD 2021.

  • [Nov 2020] Invited to serve as a SPC of IJCAI 2021.

  • [Oct 2020] Two papers accepted to WSDM 2021. We propose novel frameworks to (1) relax the strong assumptions for estimating long term causal effect and (2) learning latent confounders from network data in a dynamic environment. Credits to the female first authors Lu and Jing!

  • [Oct 2020] Invited to serve as a PC of AISTATS 2021.

  • [Aug 2020] Ruocheng started his AI residency at X, the moonshot factory. He is working on a confidential early stage project.

  • [Aug 2020] Invited to serve as a PC of AAAI 2021.

  • [Aug 2020] Invited by Dr. Jiang Zhang (BNU), Ruocheng gave a talk to members of a summer camp (集智-凯峰研读营) on the connections between Causality and ML.

  • [Aug 2020] Finished the internship @ Microsoft Research, many thanks to my colleagues.

  • [May 2020] The paper "Debiasing Grid-based Product Search for E-commerce" is accepted by KDD2020 ADS track!

  • [May 2020] Invited by Mr. Ming Ding, Ruocheng gave a talk to students of Tsinghua University on causality and ML [slides]!

  • [May 2020] Ruocheng passed the proposal defense and became a Ph.D. Candidate!

  • [April 2020] Invited to present at INFORMS 2020 on e-commerce search and recommendation at Etsy.

  • [April 2020] Ruocheng will intern at MSR+AI this summer. Ruocheng will work with Dr. Emre Kiciman and Dr. Pengchuan Zhang.

  • [April 2020] The paper "A Survey of Learning Causality with Data: Problems and Methods" is accepted by ACM Computing Surveys (CSUR)!

  • [April 2020] A paper is accepted to IJCAI 2020 (AI in Fintech Track, Acc Rate 19.3%).
    A novel representation balancing method is proposed for causal effect estimation with networked observational data.

  • [March 2020] Invited to serve as a PC of ECML-PKDD 2020.

  • [March 2020] Invited to serve as a PC of AACL-IJCNLP 2020.

  • [March 2020] Invited to serve as a PC of NeurIPS 2020.

  • [March 2020] Received Doctoral Fellowship from ASU CIDSE.

  • [Dec 2019] Two papers are accepted by SDM 2020.

  • [Dec 2019] Code and data for our WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data, are available on github .

  • [Nov 2019] Invited to serve as a PC of IJCAI-PRICAI 2020.

  • [Nov 2019] A paper is accepted by ACM Transaction of Social Computing.

  • [Nov 2019] Invited to serve as a PC of ICML 2020.

  • [Oct 2019] Two papers are accepted by WSDM 2020.

  • [Aug 2019] Two papers are accepted by Bench 2019.

  • [Aug 2019] Finished my internship @ Etsy Data Science, many thanks to my colleagues.