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PurpCorn 2026

Team PurpCorn

We are committed to building high-performance software agents and code models grounded in the principles of safety, security, and trustworthiness. By integrating interdisciplinary expertise, we strive to create AI systems that faithfully serve human goals: generating reliable code, acting helpfully when requests are legitimate, exercising restraint when they are not, and proactively identifying and mitigating potential risks. Our mission is to expand the frontier of intelligent software systems while ensuring they remain aligned with human values and practical needs.

By University of Illinois at Urbana-Champaign
3 min read
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Team leaders

Yifeng Ding (2026)

PhD candidate at UIUC researching LLMs for code generation and repair. Focuses on improving LLM reasoning for software engineering tasks through pre- and post-training. Collaborates with Google and Amazon; published at ICML, NeurIPS, ACL, and EMNLP.

Nirav Diwan (2025)

PhD student at UIUC focusing on Security and ML, particularly practical attacks on large language models. Published in ACL, IEEE S&P, USENIX Security, and ICWSM. Actively collaborates with industry including LG AI Research and TCS Research.

Muntasir Wahed (2025)

PhD student in Computer Science at UIUC. Research focuses on Robust ML, Multimodal ML, and Self-Supervised Learning. Extensive industry experience with three research internships at IBM Research Almaden Lab.

Jiawei Liu (2025)

PhD candidate at UIUC. Research focuses on assuring software quality of machine learning systems and LLM-based code generation. Published at ASPLOS, FSE, OOPSLA, NeurIPS, and COLM. Winner of ACM SIGSOFT Distinguished Paper Award and Distinguished Artifact Award.

Team members

Yuxiang Wei (2025-26)

Works on building code intelligence and training code agents. Leads development of Magicoder, StarCoder2-Instruct, Self-Play SWE-RL, and Meta's Code World Model, garnering 405k+ downloads and 2.1k+ GitHub stars. Techniques adopted by Meta, Google, IBM, and Snowflake.

Zhe Wang (2025-26)

Research focuses on AI for code and LLM post-training. Contributed to the Magicoder project's OSS-INSTRUCT methodology, enabling a 7B parameter model to outperform 16B models. Work accepted at ICML 2024, NeurIPS, and ACL. Previously graduated from Tsinghua University with B.S. in Mathematics and Physics.

Haoyu Zhai (2025-26)

Research focuses on machine learning security, large language models, and AI for security. Examines security of image anonymization techniques using diffusion models and works on adversarial attacks against Code LLMs. Published at IEEE S&P, NeurIPS, and SOUPS.

Xiaona Zhou (2025-26)

Research focuses on cross-modal information retrieval, data-centric machine learning, and time-series anomaly detection. Year-round research intern at Sandia National Laboratories.

Xinzhuo Li (2026)

Electrical and Computer Engineering Master's student at UIUC. Research focuses on reliable AI and vision language models, including mitigating hallucinations in reasoning segmentation models and detecting vulnerabilities in large-scale OS systems.

Hadjer Benkraouda (2025)

PhD student at UIUC. Research interests include system security, binary analysis, and ML, exploring the intersection of language processing and program analysis. Published at IEEE S&P, USENIX Security, ACM CHI, and CoNext.

Tianjiao (Joey) Yu (2025)

Computer Science PhD at UIUC. Research aims to create AI models that understand and respond to natural language as effectively as humans, advancing interpretability and trust in multimodal and embodied AI systems.

Yinlin Deng (2025)

PhD student at UIUC working on LLM4Code, including automated testing, program synthesis, and program repair. Research led to automatic discovery of 350+ bugs in ML frameworks. Collaborated with Google DeepMind, Fujitsu Research, and Microsoft.

Kiet Nguyen (2025)

PhD student in Computer Science at UIUC, specializing in multimodal deep learning with focus on Large Vision-Language Models (LVLMs) for pixel-grounded reasoning. Extensive experience designing, implementing, and training LVLMs.

Faculty advisors

Gang Wang (2025-26)

Associate Professor of Computer Science at UIUC. Research focused on security and machine learning. Recipient of NSF CAREER Award, Amazon Research Award, Google Faculty Research Award, and Best Paper awards at IMWUT, ACM CCS, and SIGMETRICS. Part of NSF ACTION AI Institute and LDOS Expedition Project.

Lingming Zhang (2025-26)

Associate Professor of Computer Science at UIUC. Research at intersection of Software Engineering and Machine Learning. Group has released multiple open code LLMs with millions of downloads worldwide; training techniques widely adopted by leading AI companies. Recipient of ACM SIGSOFT Early Career Researcher Award, NSF CAREER Award, and research awards from Alibaba, Google, Kwai, Meta, and Sams.

Ismini Lourentzou (2025-26)

Assistant Professor in School of Information Sciences at UIUC and director of Perception and LANguage (PLAN) Lab. Research focuses on multimodal machine learning, particularly generative modeling, vision-language models, and multimodal reasoning. Previously Assistant Professor at Virginia Tech where she received Outstanding New Assistant Professor Award.

About the Author
University of Illinois at Urbana-Champaign

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