About

I am a Professor in the Food and Resource Economics department at the University of Florida. My research mainly uses primary data from surveys and lab/field experiments as well as secondary data to enhance the understanding of the factors that affect individual behavior related to food choice and agriculture technology. Most of my research focuses on strategies and policies that promote sustainable food consumption and sustainable technology adoption among farmers.

Research topics

• Business
• Economics
• Computer Science
• Medicine
• Marketing
• Geography
• Political Science
• Artificial Intelligence
• Engineering
• Econometrics
• Psychology
• Agricultural economics
• Machine Learning
• Microeconomics
• Operations research
• Mathematics
• Actuarial science
• Finance
• Advertising
• Environmental health
• Statistics
• Meteorology
• Data science
• World Wide Web

Selected publications

• NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning

  ArXiv.org · 2026-04-12

  articleOpen access

  Olfaction lies at the intersection of chemical structure, neural encoding, and linguistic perception, yet existing representation methods fail to fully capture this pathway. Current approaches typically model only isolated segments of the olfactory pathway, overlooking the complete chain from molecule to receptors to linguistic descriptions. Such fragmentation yields learned embeddings that lack both biological grounding and semantic interpretability. We propose NOSE (Neural Olfactory-Semantic Embedding), a representation learning framework that aligns three modalities along the olfactory pathway: molecular structure, receptor sequence, and natural language description. Rather than simply fusing these signals, we decouple their contributions via orthogonal constraints, preserving the unique encoded information of each modality. To address the sparsity of olfactory language, we introduce a weak positive sample strategy to calibrate semantic similarity, preventing erroneous repulsion of similar odors in the feature space. Extensive experiments demonstrate that NOSE achieves state-of-the-art (SOTA) performance and excellent zero-shot generalization, confirming the strong alignment between its representation space and human olfactory intuition.Code and data are available at https://github.com/Xianyusyy/NOSE

  PublisherOA PDF

• NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning

  arXiv (Cornell University) · 2026-04-12

  preprintOpen access

  Olfaction lies at the intersection of chemical structure, neural encoding, and linguistic perception, yet existing representation methods fail to fully capture this pathway. Current approaches typically model only isolated segments of the olfactory pathway, overlooking the complete chain from molecule to receptors to linguistic descriptions. Such fragmentation yields learned embeddings that lack both biological grounding and semantic interpretability. We propose NOSE (Neural Olfactory-Semantic Embedding), a representation learning framework that aligns three modalities along the olfactory pathway: molecular structure, receptor sequence, and natural language description. Rather than simply fusing these signals, we decouple their contributions via orthogonal constraints, preserving the unique encoded information of each modality. To address the sparsity of olfactory language, we introduce a weak positive sample strategy to calibrate semantic similarity, preventing erroneous repulsion of similar odors in the feature space. Extensive experiments demonstrate that NOSE achieves state-of-the-art (SOTA) performance and excellent zero-shot generalization, confirming the strong alignment between its representation space and human olfactory intuition.Code and data are available at https://github.com/Xianyusyy/NOSE

  PublisherDOI

• Prognostic Significance of Mild Exacerbations or 1 Moderate Exacerbation in COPD

  CHEST Journal · 2026-04-01

  article
  PublisherDOI

• Can Domestic Vanilla Compete? Sensory Evaluation and Willingness to Pay for Vanilla Flavorings

  Agribusiness · 2025-02-11 · 3 citations

  article

  ABSTRACT The U.S. is the largest importer of vanilla beans. Currently, there is no large‐scale domestic commercial production of vanilla beans. However, Florida's tropical climate is suitable for production, and researchers are exploring the viability of a Florida‐based domestic vanilla industry. To understand consumer preferences and valuations for vanilla with different flavor sources, we administered a blind sensory panel. Participants sampled four vanilla flavorings, including a vanilla extract made from vanilla beans grown in Florida, a commercially available vanilla extract made from vanilla beans grown in Papua New Guinea, a national‐brand vanilla extract made from vanilla beans grown in Madagascar, and a commonly available synthetic flavoring. Panelists were asked questions related to acceptability and contingent valuation. Mean separation analysis and regression analysis reveal that participants’ willingness to pay (WTP) for the three vanilla extracts are statistically indifferent, suggesting that the country of origin of the beans did not impact WTP for the extract. However, the synthetic flavoring received higher ratings and panelist indicated higher WTP for the synthetic flavoring than some of the vanilla extracts.

  PublisherDOI

• Are Authenticity Tests in Demand? Consumers' Preferences for Authenticity Tests in the Chinese Online Food Market

  Agribusiness · 2025-12-16 · 1 citations

  articleOpen accessSenior author

  ABSTRACT With the development of new technologies that can change food appearance and taste, food fraud has become an increasingly critical issue in the food market, especially in the online food market worldwide in recent years. This study examines 935 Chinese online beefsteak buyers' preferences for food authenticity test information (meat glue test and DNA test) and explores changes in consumer surplus when such tests are provided. Our findings indicate that Chinese consumers perceive a high risk of food fraud when buying beefsteak online and consistently prefer authenticity test information, such as meat glue tests, DNA tests, and authenticity clues like Halal food verification. We also find that consumers with high consumption levels are more likely to use price as a quality cue to avoid food fraud. Consumers with low consumption levels may receive more consumer surplus from authenticity testing. This study provides important insight for policymakers and food companies when evaluating the benefits of offering food authenticity test information and designing pricing strategies with consumption stratification in the online food market.

  PublisherOA PDFDOI

• Exploring the Adoption of High Tunnel System among Specialty Crop Growers: Perceptions, Use Experiences, Willingness to Pay, and Influencing Factors

  HortScience · 2025-10-20

  articleOpen access

  High tunnels are a low-cost protected crop production system and can help mitigate specialty crop production risks from extreme weather, diseases, and pests. Understanding growers’ perspectives is essential in promoting the adoption of high tunnels. This study examined specialty crop growers’ perceptions, experiences, and willingness to adopt high tunnels in Florida. Our results indicate that both high tunnel users and nonusers have positive perceptions of high tunnels for crop production. Most high tunnel users grow multiple crops in the same season and use in-ground soil systems for crop production in high tunnels. While growers’ willingness to pay for high tunnels is not likely to be affected by most factors included in the analysis, their actual adoption behavior is positively correlated with their awareness of the US Department of Agriculture–Natural Resources Conservation Service high tunnel financial assistance program, land being owned by growers as a corporation, and race (e.g., white) but negatively correlated with their farm size. These findings provide crucial insights for researchers to develop targeted research agendas to address key challenges growers face in high tunnel specialty crop production. The results can also guide policymakers, extension services, and industry stakeholders in promoting high tunnel use by effectively implementing policies and programs to assist with high tunnel adoption.

  PublisherDOI

• Quality cue or price anchoring: The effect of price on consumer behavior in repeat experiments

  Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2025-01-26

  articleCorresponding

  Abstract Price is one of the most important factors affecting consumer purchase decisions. Consumers may use price as a quality cue or reference point to make the decisions. However, few studies have considered the quality cue by controlling the price anchoring and vice versa. We conduct four identical experiments weeks apart to estimate the effect of price on consumers' product quality evaluation and WTP. The results show that (1) the price has a significant impact on appearance rating and taste rating; (2) product quality mediates the price effect on consumer WTP only if consumers have incomplete quality information about the product; and (3) the marginal effect of price on consumer WTP differs over time. The results of this study provide deep insights into the role of price on consumers' quality assessment and valuation formation of products.

  PublisherDOI

• Unified Cross-Scale 3D Generation and Understanding via Autoregressive Modeling

  arXiv (Cornell University) · 2025-03-20 · 1 citations

  preprintOpen access

  3D structure modeling is essential across scales, enabling applications from fluid simulation and 3D reconstruction to protein folding and molecular docking. Yet, despite shared 3D spatial patterns, current approaches remain fragmented, with models narrowly specialized for specific domains and unable to generalize across tasks or scales. We propose Uni-3DAR, a unified autoregressive framework for cross-scale 3D generation and understanding. At its core is a coarse-to-fine tokenizer based on octree data structures, which compresses diverse 3D structures into compact 1D token sequences. We further propose a two-level subtree compression strategy, which reduces the octree token sequence by up to 8x. To address the challenge of dynamically varying token positions introduced by compression, we introduce a masked next-token prediction strategy that ensures accurate positional modeling, significantly boosting model performance. Extensive experiments across multiple 3D generation and understanding tasks, including small molecules, proteins, polymers, crystals, and macroscopic 3D objects, validate its effectiveness and versatility. Notably, Uni-3DAR surpasses previous state-of-the-art diffusion models by a substantial margin, achieving up to 256\% relative improvement while delivering inference speeds up to 21.8x faster.

  PublisherOA PDFDOI

• SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis

  2025-01-01 · 10 citations

  articleOpen access

  Hengxing Cai, Xiaochen Cai, Junhan Chang, Sihang Li, Lin Yao, Wang Changxin, Zhifeng Gao, Hongshuai Wang, Li Yongge, Mujie Lin, Shuwen Yang, Jiankun Wang, Mingjun Xu, Jin Huang, Xi Fang, Jiaxi Zhuang, Yuqi Yin, Yaqi Li, Changhong Chen, Zheng Cheng, Zifeng Zhao, Linfeng Zhang, Guolin Ke. Findings of the Association for Computational Linguistics: NAACL 2025. 2025.

  PublisherOA PDFDOI

• Consumer preference for fresh produce: Does the biological control influence their choices?

  Economic Analysis and Policy · 2025-02-27 · 4 citations

  article
  PublisherDOI

Frequent coauthors

• Lisa House

  University of Florida

  83 shared

• Xuqi Chen

  University of California, Los Angeles

  31 shared

• Xin Zhao

  30 shared

• Xiaohua Yu

  University of Göttingen

  20 shared

• Lijia Shi

  Dalian Minzu University

  19 shared

• Marilyn E. Swisher

  University of Florida

  18 shared

• Michael S. Jones

  University of Alaska Anchorage

  15 shared

• Francesco Di Gioia

  Pennsylvania State University

  14 shared

Education

• Ph.D., Computer Science

  University of Florida

  2005

• M.S., Computer Science

  University of Florida

  2002

• B.S., Computer Science

  University of Science and Technology of China

  1999