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Jian Pei

Arthur S. Pearse Distinguished Professor of Computer Science
Computer Science
308 Research Drive, Durham, NC 27708

Overview


Data science, data mining, databases, information retrieval, computational statistics, applied machine learning and AI.

Current Appointments & Affiliations


Arthur S. Pearse Distinguished Professor of Computer Science · 2023 - Present Computer Science, Trinity College of Arts & Sciences
Professor of Computer Science · 2023 - Present Computer Science, Trinity College of Arts & Sciences
Chair of the Department of Computer Science · 2023 - Present Computer Science, Trinity College of Arts & Sciences
Professor of Biostatistics & Bioinformatics · 2023 - Present Biostatistics & Bioinformatics, Division of Biostatistics, Biostatistics & Bioinformatics
Professor of Electrical and Computer Engineering · 2023 - Present Pierre R. Lamond Department of Electrical and Computer Engineering, Pratt School of Engineering

In the News


Published September 3, 2024
Six Duke Scholars Embark on Leadership Journey with Ivy+ Peers
Published November 12, 2023
Five Decades of Creating History and Pushing Boundaries at Duke Computer Science
Published July 25, 2023
Duke Effort Aims to End Bottlenecks Preventing Secondary Use of Big Data

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Recent Publications


Generalizability of Large Language Model-Based Agents: A Comprehensive Survey

Journal Article ACM Computing Surveys · February 7, 2026 Large Language Model (LLM)-based agents have recently emerged as a new paradigm that extends the capabilities of LLMs beyond text generation to dynamic interaction with external environments. A critical challenge lies in ensuri ... Full text Cite

A Comprehensive Survey on Data Augmentation

Journal Article IEEE Transactions on Knowledge and Data Engineering · January 1, 2026 Data augmentation is a series of techniques that generate high-quality artificial data by manipulating existing data samples. By leveraging data augmentation techniques, AI models can achieve significantly improved applicability in tasks involving scarce o ... Full text Cite

Evaluating Large Language Models for Automated Clinical Abstraction in Pulmonary Embolism Registries: Performance Across Model Sizes, Versions, and Parameters

Conference Lecture Notes in Computer Science · January 1, 2026 Pulmonary embolism (PE) registries accelerate practice-improving research but depend on resource-intensive manual abstraction of radiology reports. We evaluated whether openly available large-language models (LLMs) can automate concept extraction from comp ... Full text Cite
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Recent Grants


Collaborative Research: AI Tools to Knowledge Discovery and Rigorous Reasoning in Polyhedral Geometry

ResearchCo-Principal Investigator · Awarded by National Science Foundation · 2024 - 2027

EAGER: End-to-End Learning of Paradoxes and Interpretations for Data Storytelling

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2023 - 2024

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Education, Training & Certifications


Simon Fraser University · 2002 Ph.D.

External Links


Jian Pei Website