About

Xiaofei Lu is the George C. and Jane G. Greer Professor of Applied Linguistics and Asian Studies at The Pennsylvania State University, within the Department of Applied Linguistics. He holds a PhD in Linguistics from The Ohio State University, an MA by research in English Language from the National University of Singapore, and a BA in English from Nankai University. His research interests encompass corpus linguistics, second language writing, English for Academic Purposes, computer-assisted language learning, and second language acquisition. Much of his work focuses on computational and quantitative analyses of linguistic complexity in reading materials, second language production, and academic writing. Currently, his research explores sense-aware measurements of linguistic complexity that consider the specific meanings of polysemous linguistic forms in context, mappings between linguistic forms and rhetorical/pragmatic functions in language production, and their applications in corpus-based genre pedagogy, as well as applications of large language models and generative AI in language teaching and assessment. Professor Lu's research has been recognized globally; the August 2025 data update for "Updated science-wide author databases of standardized citation indicators" ranked his research #48 for single-year impact and #164 for career-long impact among the top 2% most-cited scientists in the Languages & Linguistics subfield worldwide. He and his collaborators received the 2023 Ken Hyland Best Paper Award from the Journal of English for Academic Purposes. He serves as an Associate Editor of the Journal of Second Language Writing and is on the advisory board of the Studies in Corpus Linguistics book series. Additionally, he serves on the editorial boards of numerous professional journals related to applied linguistics and language education. Professor Lu has developed several computational tools and corpus resources resulting from his research, which are made available through his university webpage.

Research topics

• Computer Science
• Natural Language Processing
• Artificial Intelligence
• Linguistics
• Sociology
• Psychology
• Medicine
• Mathematics education
• Cognitive psychology
• Communication
• Surgery
• Anesthesia
• Philosophy

Selected publications

• State-of-the-art vegetation models overestimate gross primary productivity responses to drought

  Atmospheric and Oceanic Science Letters · 2026-01-01

  articleOpen access
  PublisherDOI

• An auto-parallel training method for deep learning models with extracting model structural features

  Applied Soft Computing · 2026-05-14

  article
  PublisherDOI

• Bridging the function-form gap: a multidimensional move analysis of English research article introductions in applied linguistics by L1 English and L1 Chinese scholars

  IRAL - International Review of Applied Linguistics in Language Teaching · 2026-01-19

  articleSenior author

  Abstract Combining move analysis with multidimensional analysis (MDA), this study investigates salient linguistic co-occurrence patterns (“dimensions”) as well as linguistic variations in the rhetorical moves of English research article introductions (RAIs) in applied linguistics written by L1 English and L1 Chinese scholars. Our MDA of a corpus of move segments of RAIs from thirteen applied linguistics journals identifies five functionally interpretable dimensions: grounded evaluation, criticism with caution, stated purposes, author-involved narration of current study versus existing knowledge, and research- versus non-research-related information density. A comparative analysis reveals systematic variation in the linguistic features of specific moves between the RAIs written by L1 English and L1 Chinese scholars. Our findings have useful implications for research and pedagogy of English for academic purposes.

  PublisherDOI

• Development of syntactic complexity in Chinese EFL learners across two proficiency levels and two written genres

  Journal of Second Language Writing · 2026-01-14 · 1 citations

  articleSenior author
  PublisherDOI

• Overlooked health and ecotoxicological effects of PFOS alternatives: Evidence from wheat in soil

  Environmental Research · 2026-01-22

  article
  PublisherDOI

• The Corpus Linguistics Approach to Second Language Acquisition

  2026-04-27

  book-chapter1st authorCorresponding

  This chapter introduces the corpus linguistics approach to second language acquisition (SLA), i.e., the use of native and learner corpora as data sources, automated and semi-automated tools for corpus annotation, as well as the range of methods, measures, and tools for analyzing language data in various ways applicable to basic and applied SLA research. Specifically, it systematically reviews how corpus linguistics may inform four key areas of SLA research: (1) variation in L2 use as affected by learner- and task-related variables, (2) L2 processing and production as influenced by different input factors, (3) group-level longitudinal developmental trajectories of L2 learners, and (4) individual variability in L2 development. Particular attention is devoted to the composition of corpora used or compiled as well as the tools and methods utilized for corpus annotation or language analysis, including their underlying rationales, in such research. In so doing, the chapter aims to highlight the methodological appropriateness and contributions of corpus linguistics for unraveling various SLA phenomena and issues.

  PublisherDOI

• MemOpt: a memory optimization method for deep learning model training based on dual intelligent reinforcement learning

  The Computer Journal · 2026-01-28

  article

  Abstract In recent years, with the rapid growth in the scale of datasets and neural network models, there has been a significant imbalance between the memory requirements during model training and the memory resources available on training devices. Existing memory optimization techniques like recomputation, memory swapping, and their adaptive combinations do not fully consider the structural information of the model and overlook the impact of application costs and timing on training efficiency. Addressing this issue, this paper proposes a memory optimization method called MemOpt, which uses dual-agent reinforcement learning to dynamically search for appropriate memory optimization strategies and execution timing based on model structure and device information. It can optimize memory without compromising accuracy while minimizing additional overhead. Experimental results show that the MemOpt method significantly increases the maximum batch size for model training by up to 8.7% and training throughput by up to 42.3% compared with baseline methods. In the future, this method may find better applications in large-scale neural networks.

  PublisherDOI

• Revisiting Emotional Effects Under Lexical Control in L2 Auditory Word Recognition Memory

  Journal of Psycholinguistic Research · 2026-03-18 · 1 citations

  articleSenior author
  PublisherDOI

• Generative <scp>AI</scp> in the English Composition Classroom: Practical and Adaptable Strategies.New York: Routledge, 2025. pp. xv + 220. ISBN 9781032831367

  TESOL Quarterly · 2025-08-13

  articleSenior authorCorresponding

  The author reports no conflict of interest regarding this review.

  PublisherDOI

• The Dissemination and Reception of the English Translation of Wolf Totem in the United States

  Studies in English Language Teaching · 2025-10-04

  articleOpen access1st authorCorresponding

  This study adopts quantitative and empirical methods, focusing on the English translation of Jiang Rong’s novel Wolf Totem translated by Howard Goldblatt, to explore its dissemination and reception in the United States. By analyzing data from the World Cat, as well as reader ratings and reviews on Amazon and Goodreads, it reveals that Wolf Totem has achieved widespread circulation and favorable acceptance among American readers, with particular attention drawn to its ecological themes and the cultural symbolism of the wolf. These findings provide valuable reference for contemporary Chinese literary works to more effectively reach a global audience and further achieve the transition from merely “going out” to “reaching in”.

  PublisherOA PDFDOI

Frequent coauthors

• Jian Liao

  Chongqing University

  40 shared

• Katherine A. Masters

  Pennsylvania State University

  37 shared

• Zhi Zhou

  Pennsylvania State University

  37 shared

• J. Elliott Casal

  10 shared

• Yingying Liu

  8 shared

• Tan Jin

  South China Normal University

  8 shared

• Daniel I. Sessler

  Cleveland Clinic

  6 shared

• Eva Rivas

  Hospital Clínic de Barcelona

  6 shared

Education

• Ph.D., Linguistics

  The Ohio State University

  2006