About

Yiling Zhang is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Minnesota. She received her Ph.D. in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, in 2019, and her M.S. in the same field from the same university in 2015. Her undergraduate degree is in Automation from Tsinghua University in Beijing, China, earned in 2013. Her research interests include stochastic programming, integer programming, and nonlinear programming, with applications in risk analysis of energy systems, healthcare operations, and transportation systems. Her work has been published in reputable journals such as Operations Research, SIAM Journal on Optimization, and Manufacturing & Service Operations Management. She has received several awards, including Honorable Mention for the INFORMS Optimization Society Student Paper Prize, the Richard & Eleanor Towner Prize for Distinguished Academic Achievement, and the Murty Prize for Best Student Paper in Optimization.

Research topics

• Computer Science
• Psychology
• Human–computer interaction
• Medicine
• Sociology
• Artificial Intelligence
• Developmental psychology
• Audiology
• Clinical psychology
• Simulation
• Communication
• Psychiatry

Selected publications

• Age-related changes in multisensory emotional speech perception: Evidence for a dual-pathway model.

  Psychology and Aging · 2026-05-04

  articleSenior author

  = 182) completed two emotional speech perception tests: a cross-channel test pairing prosody with semantics and a cross-modal test that additionally included visual facial expressions. They were also assessed for hearing sensitivity as well as global and specific cognitive functions, including selective attention, working memory, and musical emotion discrimination. A structural equation modeling approach was applied to examine how these age-related auditory and cognitive factors influenced emotional speech perception across different communication channels. In the cross-channel test, age mediated the performance through cognitive functioning and, to a lesser degree, hearing sensitivity, with both pathways stronger for emotional prosody than for semantics. In the cross-modal test, while the indirect effect of age was enhanced and remained most pronounced in prosody compared to the other two channels, it was primarily mediated via cognitive functioning. In addition, age was found to be a significant direct predictor of perceptual performance, especially in the semantic task. Our findings delineate an integrated, dual-pathway model of age-related changes in multisensory emotional speech perception. This involves test-specific direct age effects, especially for semantic processing, and general indirect effects on prosody perception primarily via cognitive functioning and, to a lesser extent, through hearing sensitivity. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

  PublisherDOI

• Research progress on nursing students’ psychological capital

  Chinese Journal of Integrative Nursing · 2026-03-28

  articleOpen accessSenior author

  Psychological capital, as an important psychological indicator in the learning career of nursing students, reflects their personal characteristics, internal potential, and sense of happiness. This study systematically summarizes the relevant concepts of psychological capital, as well as the antecedent variables and outcome variables that affect the psychological capital of nursing students. At present, the measurement tools for the psychological capital of nursing students at home and abroad mainly include two versions of the Positive Psychological Capital Questionnaire, the Chinese revised version of the Nurse Psychological Capital Questionnaire, the Psychological Capital Scale for Male Nursing Students, and the revised version of the College Students' Psychological Capital Questionnaire. However, there are few intervention programs for the psychological capital level of nursing students in existing studies, only including psychological capital intervention programs, acceptance and commitment therapy, and group counseling positive psychological interventions. In the future, nursing educators should pay more attention to nurses' psychological capital, develop psychological capital measurement scales suitable for Chinese nursing students, strengthen the professional pertinence of intervention programs, and construct a long-term intervention mechanism to further improve the psychological capital level of nursing students. (心理资本作为护生学习生涯中重要的心理指标, 反映其个人特征, 内在潜能及幸福感。本研究系统综述心理资本的概念内涵, 梳理影响护生心理资本的前因变量与结果变量, 并总结国内外护生心理资本测量工具, 包括积极心理资本问卷、护士心理资本问卷中文修订版、男护生心理资本量表及大学生心理资本问卷修订版。当前, 针对护生心理资本的干预研究较为匮乏, 现有方案主要包括心理资本干预模型、接纳与承诺疗法及团体辅导积极心理干预。建议未来护理教育者加强对护生心理资本的重视程度, 开开发针对我国护生的心理资本测量量表, 且强化干预方案的专业针对性, 构建长效干预机制, 以进一步提升护生的心理资本水平。)

  PublisherDOI

• 水利工程监理现状对施工阶段监理控制措施的影响

  工程管理与技术探讨 · 2026-01-01

  articleOpen access1st authorCorresponding

  随着国家对水利基础设施建设的投入持续加大，水利工程规模不断扩大、技术复杂度日益提升，其建设 质量与效益备受关注。本文围绕水利工程监理现状与施工阶段监理控制措施的关联展开研究，先阐述水利工程监理 在确保工程质量、控制进度、合理把控投资及保障施工安全方面的重要性，再深入分析监理现状对施工阶段四大控制 措施的具体影响，如质量检验不严格、进度计划审核不严谨、工程计量不准确、安全检查不到位等问题，最后从规范 监理市场环境、提高监理人员素质、严格执行监理制度三个维度提出改进措施，旨在为优化水利工程施工阶段监理工 作、提升工程建设水平提供参考。

  PublisherOA PDFDOI

• Hard constraints and soft learning dual-graph anomaly detection for industrial processes

  Engineering Applications of Artificial Intelligence · 2026-04-27

  article
  PublisherDOI

• Dynamic Reweighting of Acoustic Cues Across Linguistic Hierarchies in Speech and Emotion

  2026-04-27

  articleOpen accessSenior author

  Temporal envelope (ENV) and fine structure (TFS) are two key acoustic cues for speech communication, yet their roles in tone and affective processing across linguistic levels remains poorly understood. We present a unified framework examining these dependencies across sub-lexical (tone), lexical (word emotion), and supra-lexical (sentence emotion) levels using a speech-chimera paradigm with logarithmically increasing spectral gradient (1 to 64 bands). ENV and TFS were orthogonally manipulated to assess cue trade-offs. As spectral resolution increased, performance shifted toward more reliance on ENV and reduced dependence on TFS. Critically, TFS dominated tone identification and lexical emotion perception, whereas ENV contributed more to sentence-level affective inference. This pattern held across categorization and rating tasks. These findings support a dynamic, level-sensitive architecture in which acoustic cue weighting is flexibly tuned to linguistic context, with implications for optimizing hearing technologies and clinical interventions.

  PublisherDOI

• 水利工程监理工作中的质量控制方法

  水利电力技术与应用 · 2026-01-01

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• TCMHP: a large language model for traditional Chinese medicine health preservation

  2025-07-24

  article

  Traditional Chinese Medicine (TCM) health preservation embodies the millennia-old wisdom of "preventive treatment" in Chinese culture. However, its complex theoretical system and lack of professional data have constrained the development of intelligent applications. To address this, this paper introduces TCMHP, the first large language model for TCM health preservation. The model systematically integrates data from TCM classics, health preservation encyclopedic entries, and knowledge graphs, employing a two-stage "question-answer" dialogue generation technique to construct a high-quality domain-specific dataset of 180,000 conversation pairs, covering core scenarios including diet, exercise, medicine, and acupuncture. Additionally, the model utilizes the Lora parameter-efficient fine-tuning method to achieve precise transfer from general large language models to the TCM health preservation domain. Evaluation results demonstrate the model's significant advantages across four core areas of TCM health preservation. Compared to baseline models such as BianCang-Qwen2.5, MedChatZH, and HuatuoGPT-II, in the dietary health preservation domain, the model achieves state-of-the-art performance in single-choice (80.2%), multiple-choice (52.0%), and true/false (84.4%) tasks. In exercise-related health preservation, its performance is even more remarkable, with accuracy rates reaching 83.4% (single-choice), 59.2% (multiple-choice), and 84.8% (true/false). The model also demonstrates excellent results in medicinal and acupuncture-massage health preservation domains. Compared to the base model Qwen-2.5-Instruct, TCMHP shows a 4-12 percentage point advantage in complex multiple-choice evaluations, reflecting its comprehensive understanding of TCM health preservation concepts.

  PublisherDOI

• Beyond Categorical Perception: Gradient Lexical Tone Processing Revealed by Visual Analog Scale

  Preprints.org · 2025-10-23

  preprintOpen accessSenior author

  Purpose: While the Visual Analog Scale (VAS) has revealed gradient perception in segmental speech sounds, its application to lexical tones, a critical yet understudied suprasegmental feature, has been absent. This study investigated lexical tone categorization using VAS, directly comparing it with traditional two-alternative forced-choice (2AFC). Method: Eighty-four native speakers categorized an 11-step F0 continuum from Mandarin Tone 1 to Tone 2 in both tasks. Four-parameter logistic functions yielded slope (categorization sharpness) and response variability. Within-category sensitivity (Δ) was quantified from VAS responses.Results: Paired Wilcoxon signed-rank tests showed significantly shallower slopes (p < .001, r = .76) and lower variability (p < .001, r = .87) in VAS versus 2AFC. One-sample t-tests confirmed listeners discriminated fine-grained differences within categories, with Δ reliably exceeding zero (left: M = 0.0335, t(270) = 8.89, p < .001; right: M = 0.0256, t(316) = 8.38, p < .001). Crucially, slope and response variability were weakly correlated in VAS (ρ = .27, p < .05) but strongly negatively correlated in 2AFC (ρ = -.67, p < .001). Moreover, response variability correlated significantly across tasks (ρ = .40, p < .001), while slopes did not. Conclusion: These findings provide the direct evidence for gradient perception at the suprasegmental level, further establishing VAS as a sensitive tool for uncovering the nature of speech categorization. The dissociation between task-dependent gradiency and stable response variability helps reconcile apparent conflicts in the categorical perception literature, suggesting that these conflicts may stem from methodological constraints rather than genuine theoretical disagreements.

  PublisherOA PDFDOI

• Robot-Assisted Language Learning: A Bibliometric Review and Visualization Analysis

  Preprints.org · 2025-10-27

  preprintOpen accessSenior author

  This study presents a comprehensive bibliometric review of robot-assisted language learning (RALL) from 2003 to 2025, analyzing 439 publications from Web of Science, Scopus, PubMed, and Dimensions. Using Biblioshiny and VOSviewer, we mapped publication patterns, citations, keyword networks, and thematic evolution. Findings revealed steady growth peaking at 71 publications in 2023 before a slight decline in 2024, with China, the Netherlands and the United States emerging as the leading contributors and most cited nations. Keyword clustering identified four themes: educational robot, artificial intelligence, human-robot interaction and children. Thematic evolution analysis revealed a shift from foundational research to a multidisciplinary domain integrating AI, VR, IoT, and LLMs, emphasizing learner-centered designs. However, research remains fragmented and technology-driven rather than grounded in pedagogical frameworks. This review calls for bridging the gap between innovation and theory-grounded robot design. Only through interdisciplinary collaboration and evidence-based practice can RALL fulfill its transformative potential in language education.

  PublisherOA PDFDOI

• Fake-in-Facext: Towards Fine-Grained Explainable DeepFake Analysis

  ArXiv.org · 2025-10-23

  preprintOpen access

  The advancement of Multimodal Large Language Models (MLLMs) has bridged the gap between vision and language tasks, enabling the implementation of Explainable DeepFake Analysis (XDFA). However, current methods suffer from a lack of fine-grained awareness: the description of artifacts in data annotation is unreliable and coarse-grained, and the models fail to support the output of connections between textual forgery explanations and the visual evidence of artifacts, as well as the input of queries for arbitrary facial regions. As a result, their responses are not sufficiently grounded in Face Visual Context (Facext). To address this limitation, we propose the Fake-in-Facext (FiFa) framework, with contributions focusing on data annotation and model construction. We first define a Facial Image Concept Tree (FICT) to divide facial images into fine-grained regional concepts, thereby obtaining a more reliable data annotation pipeline, FiFa-Annotator, for forgery explanation. Based on this dedicated data annotation, we introduce a novel Artifact-Grounding Explanation (AGE) task, which generates textual forgery explanations interleaved with segmentation masks of manipulated artifacts. We propose a unified multi-task learning architecture, FiFa-MLLM, to simultaneously support abundant multimodal inputs and outputs for fine-grained Explainable DeepFake Analysis. With multiple auxiliary supervision tasks, FiFa-MLLM can outperform strong baselines on the AGE task and achieve SOTA performance on existing XDFA datasets. The code and data will be made open-source at https://github.com/lxq1000/Fake-in-Facext.

  PublisherOA PDFDOI

Frequent coauthors

• Hongwei Ding

  Google (United States)

  81 shared

• Hua Shu

  Huazhong University of Science and Technology

  54 shared

• Linjun Zhang

  Zhejiang University

  49 shared

• Yu Li

  Chinese University of Hong Kong

  43 shared

• Yi Lin

  Google (United States)

  27 shared

• Minyue Zhang

  Shanghai Jiao Tong University

  27 shared

• Hao Zhang

  Shandong University

  27 shared

• Chieh Kao

  University of Minnesota

  26 shared

Awards & honors

• Honorable Mention for INFORMS Optimization Society Student P…
• Richard F. and Eleanor A. Towner Prize for Distinguished Aca…