Yangruibo (Robin) Ding's Personal Website

Bio: I am an Assistant Professor in the Department of Computer Science at University of California, Los Angeles.

I completed my Ph.D. in Computer Science at Columbia University, advised by Prof. Baishakhi Ray and Prof. Gail Kaiser (an overview of my doctoral research can be found in this video). Previoulsy, I have also had wonderful experiences at Google DeepMind, AWS Agentic AI, and IBM Research.

Research: My research focuses on Large Language Models and Agentic AI for Software Engineering. Most recently, I am interested in building efficient, collaborative, and trustworthy agentic systems for complex software engineering and cybersecurity tasks.

🎯 I am actively looking for students to join my research group @ UCLA CS. Solid coding skills and experiences in large language models pre-/post-training, agentic systems, program analysis and verification, or software security are strongly preferred.

🤝 If you are interested in working with me, drop me an email with (1) your CV and (2) a brief introduction of your research interests and background.

Recent Works (Full Paper List)

	SWE-Spot: Building Small Repo-Experts with Repository-Centric Learning Jinjun Peng, Magnus Saebo, Tianjun Zhong, Yi-Jie Cheng, Junfeng Yang, Baishakhi Ray, Simin Chen, Yangruibo Ding Preprint
	To Defend Against Cyber Attacks, We Must Teach AI Agents to Hack Terry Yue Zhuo, Yangruibo Ding, Wenbo Guo, Ruijie Meng Preprint
	OpenSage: Self-programming Agent Generation Engine Hongwei Li, Zhun Wang, Qinrun Dai, Yuzhou Nie, Jinjun Peng, Ruitong Liu, Jingyang Zhang, Kaijie Zhu, Jingxuan He, Lun Wang, Yangruibo Ding, Yueqi Chen, Wenbo Guo, Dawn Song Preprint
	DevOps-Gym: Benchmarking AI Agents in Software DevOps Cycle Yuheng Tang, Kaijie Zhu, Bonan Ruan, Chuqi Zhang, Michael Yang, Hongwei Li, Suyue Guo, Tianneng Shi, Zekun Li, Christopher Kruegel, Giovanni Vigna, Dawn Song, William Yang Wang, Lun Wang, Yangruibo Ding, Zhenkai Liang, Wenbo Guo ICLR 2026
	Co-PatcheR: Collaborative Software Patching with Component(s)-specific Small Reasoning Models Yuheng Tang, Hongwei Li, Kaijie Zhu, Michael Yang, Yangruibo Ding, Wenbo Guo NeurIPS 2025
	SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning Yangruibo Ding, Jinjun Peng, Marcus J. Min, Gail Kaiser, Junfeng Yang, Baishakhi Ray NeurIPS 2024
	Vulnerability Detection with Code Language Models: How Far Are We? Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David Wagner, Baishakhi Ray, Yizheng Chen ICSE 2025
	CYCLE: Learning to Self-Refine Code Generation Yangruibo Ding, Marcus J. Min, Gail Kaiser, Baishakhi Ray OOPSLA 2024
	Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail Kaiser, Suman Jana, Baishakhi Ray ICLR 2024
	TRACED: Execution-aware Pre-training for Source Code Yangruibo Ding, Ben Steenhoek, Kexin Pei, Gail Kaiser, Wei Le, Baishakhi Ray ICSE 2024

Honors and Awards

IBM Ph.D. Fellowship Award. 2022-2024
ACM SIGSOFT Distinguished Paper Award. 2023
IEEE TSE Best Paper Award Runner-up. 2022
Ph.D. Service Award, Columbia CS. 2025
NSF Travel Award. 2022, 2023
ACM SIGSOFT CAPS Travel Grant. 2023

Industry Experiences

May 2024 - Dec 2024: Student Researcher @ Google DeepMind - Learning4Code Team, working with Pengcheng Yin, Miltos Allamanis, Disha Shrivastava, Kensen Shi, Hanjun Dai, and Charles Sutton.
May 2022 - Sep 2022: Applied Scientist Intern @ AWS AI Labs - Code Whisperer Team, working with Zijian Wang and Wasi Ahmad.
May 2021 - Sep 2021: Research Intern @ IBM Research - AI for Code Team, working with Saurabh Pujar and Luca Buratti.
June 2020 - Aug 2020: Research Intern @ IBM Research - AI for Code Team, working with Sahil Suneja and Alessandro Morari.

Recent Talks

Feb. - Apr. 2025: "From Code Generation Towards Software Engineering: Advancing Code Intelligence w/ Language Models" @ UW, UMD, CMU, UCLA, UTD, JHU, Georgia Tech, Stony Brook, Dartmouth, NUS.
Oct. 2024: "Training Code Language Models with Comprehensive Semantics Reasoning" @ UIUC.
Oct. 2024: "Semantic-aware Source Code Modeling" @ UMD, NCSU, ASE'24.
Aug. 2024: "Training Code Language Models with Comprehensive Semantics Reasoning" @ Google DeepMind.
Apr. 2024: "Vulnerability Detection with Code Language Models: How Far Are We?" @ Columbia SSS Seminar.

Recent Works (Full Paper List)

Honors and Awards

Industry Experiences

Recent Talks

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