Yangruibo (Robin) Ding's Personal Website

Yangruibo (Robin) Ding

I am a Ph.D student in the Department of Computer Science at Columbia University. I am fortunate to be advised by Prof. Baishakhi Ray and Prof. Gail Kaiser.

My research, in general, focuses on Machine Learning for Automated Software Engineering. I am passionate about Source Code Modeling and Deep Learning for Program Analysis.

I am a recipient of the IBM Ph.D. Fellowship Award.

Email / Google Scholar / LinkedIn

News

Dec 2022: Check our new preprint on code generation! CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context.

June 2022: "NatGen: Generative pre-training by "Naturalizing" source code" got accepted by ESEC/FSE 2022.

May 2022: I started working as an Applied Scientist Intern at Amazon AWS AI Lab on code modeling.

May 2022: I presented our paper, REVEAL, at ICSE 2022 in Pittsburgh!

February 2022: “Towards Learning (Dis)-Similarity of Source Code from Program Contrasts” got accpeted by ACL 2022.

January 2022: “VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements” got accepted by SANER 2022.

Preprint

CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
Yangruibo Ding*, Zijian Wang*, Wasi Uddin Ahmad*, Murali Krishna Ramanathan, Ramesh Nallapati, Parminder Bhatia, Dan Roth, Bing Xiang (* equal contribution)
Arxiv

Publications

	Towards Learning (Dis)-Similarity of Source Code from Program Contrasts Yangruibo Ding, Luca Buratti, Saurabh Pujar, Alessandro Morari, Baishakhi Ray, Saikat Chakraborty ACL 2022
	NatGen: Generative pre-training by "Naturalizing" source code Saikat Chakraborty, Toufique Ahmed, Yangruibo Ding, Premkumar Devanbu, Baishakhi Ray ESEC/FSE 2022
	Deep learning based vulnerability detection: Are we there yet Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, Baishakhi Ray ICSE 2022 Journal-First, TSE
	VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail Kaiser, Baishakhi Ray SANER 2022
	CODIT: Code Editing With Tree-Based Neural Models Saikat Chakraborty Yangruibo Ding, Miltiadis Allamanis, Baishakhi Ray ICSE 2021 Journal-First, TSE
	Patching as Translation: the Data and the Metaphor Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu, Vincent J Hellendoorn ASE 2020

Service & Experiences

Teaching

Head Teaching Assistant, Fall 2021: COMS4115 Programming Language & Translators, Columbia University

Reviewer

Shadow PC Committee: MSR 2022

Program Committee: MSR 2021 Mining Challenge

Internship

2022 Summer: Applied Scientist Intern, Amazon AWS AI Lab

2021 Summer: Research Intern, IBM T. J. Watson Research Center

2020 Summer: Research Intern, IBM T. J. Watson Research Center

Profile Photo by Lingyi. Website Template by Jon Barron