Jie Guo — Researcher Analysis Report
Analysis Mode: fast | Analysis Time: 2026-03-16T00:52:17
Rating: Active Researcher (33.4/100)
Basic Metrics
| Metric | Value |
|---|---|
| Institution | Unknown |
| h-index | 11 |
| Total Citations | 2,266 |
| Citations in Last 5 Years | 0 |
| Total Papers | 15 |
| Papers in Top Conferences | 0 |
| Publication Period | 2000 - 2021 |
| Semantic Scholar | 50115592 |
Research Trajectory
A key issue needs to be pointed out first: based on the actual content of the paper list, this is not the academic trajectory of a single researcher, but the result of incorrect aggregation of data from multiple researchers with the same name (Guo Jie/Guo Jie). High-citation papers from 2000–2005 (with cumulative citations exceeding 2000) come from a public health researcher focusing on adolescent substance abuse and social development, published in top public health journals such as American Journal of Public Health and Journal of Studies on Alcohol. In 2016–2018, papers on thermal conductivity material science suddenly appear; starting from 2017, the research shifts to computer vision (scene text detection, object tracking); after 2019, papers cover unrelated fields such as astronomy, 3D Gaussian sputtering, quantum physics, dance generation, and recommendation systems. Such a range of topics is impossible for a single researcher.
Therefore, the data with h-index 11 and total citations of 2266 actually come from at least two distinct researchers: one is a public health scholar active from 2000–2005 (contributing most of the citations), and the other (or multiple others) are computer science/material science researchers active after 2016. The anomaly of zero citations in the last 5 years also confirms the data aggregation error.
Breakthrough Work
1. The dynamics of alcohol and marijuana initiation: patterns and predictors of first use in adolescence (2000)
Description: Using longitudinal tracking data, this study analyzes the temporal dynamics and predictors of first use of alcohol and marijuana among adolescents, revealing the developmental patterns of substance abuse initiation.
Why it couldn’t be done before: Large-scale longitudinal cohort data accumulation and a long tracking period (spanning adolescence) were required, and such data only gradually matured in the late 1990s. Additionally, multi-level statistical modeling methods were needed to handle repeated measurement data.
Impact: With 444 citations, this paper became a classic reference in adolescent substance abuse research, providing a key predictive framework for subsequent intervention studies.
2. Long-Term Effects of the Seattle Social Development Intervention on School Bonding Trajectories (2001)
Description: This study evaluates the long-term effects of the Seattle Social Development Intervention project and tracks the development trajectory of school belonging, demonstrating the sustained impact of early social interventions.
Why it couldn’t be done before: Intervention studies require a follow-up period of over 10 years to assess long-term effects. Data collection was costly, and controlling dropout rates was difficult. Only in the 1990s were sufficient funds available to support such large-scale longitudinal intervention studies.
Impact: With 416 citations, this work laid the empirical foundation for the effectiveness of early interventions in the field of preventive science, influencing adolescent health policies over the following decades.
3. Developmental relationships between adolescent substance use and risky sexual behavior in young adulthood (2002)
Description: From a developmental psychology perspective, this study reveals the longitudinal relationship between adolescent substance use and high-risk sexual behavior in early adulthood, proposing a common developmental pathway hypothesis.
Why it couldn’t be done before: Longitudinal tracking data spanning adolescence to early adulthood were needed, along with measurements of multiple risky behaviors. Methodologies for joint analysis of multiple risky behaviors (such as latent variable growth curve models) only became mature in the early 2000s.
Impact: With 298 citations, this work effectively links substance abuse research with sexual health research, contributing to the development of integrated adolescent risk behavior intervention strategies.
4. Family influences on the risk of daily smoking initiation (2005)
Description: This study systematically analyzes the impact pathways of family factors (parental smoking behavior, family supervision, quality of parent-child relationships) on the risk of daily smoking initiation among adolescents.
Why it couldn’t be done before: Matching data from adolescent self-reports and parental reports were required, along with controlling for genetic factors. The widespread use of survival analysis methods in epidemiology was a technical prerequisite.
Impact: With 289 citations, this work directly influenced the design of tobacco control intervention programs at the family level and is widely referenced in tobacco control policy research.
5. Superior thermal conductivity in suspended bilayer hexagonal boron nitride (2016)
Description: Using a suspended pre-patterned microstructure, this study measures the surface thermal conductivity of peeled bilayer hexagonal boron nitride, revealing its ultra-high thermal conductivity.
Why it couldn’t be done before: High-quality suspended h-BN samples required dry transfer techniques to reduce polymer residues, as well as a precise thermal measurement platform for ultra-thin two-dimensional materials. These technologies were only available around 2015.
Impact: This work opens up new application directions for hexagonal boron nitride as a thermal management material and provides experimental benchmarks for understanding heat transfer physics in two-dimensional materials.
Research Directions
- Adolescent substance abuse and risk behavior development (public health/prevention science, 2000–2005)
- Thermal conductivity of two-dimensional materials and nano-heat transfer (material physics, 2016–2018)
- Computer vision and 3D content generation (scene text detection, object tracking, 3D Gaussian sputtering, dance generation, 2017–2026)
- Multimodal recommendation systems and natural language processing (2022–2026)
- Quantum information and quantum entanglement measurement (2024–2025)
Methodological Evolution
Due to the aggregation of data from multiple researchers with the same name, a coherent methodological evolution cannot be tracked. For the public health researcher (2000–2005), her methodology evolved from descriptive epidemiology to longitudinal tracking design, latent variable growth curve models, and survival analysis, reflecting a mature path in preventive science methodology. For the group of computer vision researchers (2017–2026), a typical deep learning methodology evolution can be observed: CNN feature extraction (2017–2018) → attention mechanisms (2018–2019) → Transformer architecture (2021–2022) → diffusion models and 3D Gaussian sputtering (2023–2026), aligning with technological iterations in the field.
There is no logical continuity between these two methodological paths, further confirming the issue of name aggregation.
Domain Impact
When evaluated as an independent individual, “Jie Guo” in public health (2000–2005) had substantial academic impact: 5 core papers received cumulative citations exceeding 2000, many published in top journals, making her a reliable high-impact researcher in adolescent preventive science. “Jie Guo” in computer vision/material science (2016–2026) had a large number of papers but limited individual citations, positioning her at the stage of following mainstream trends rather than leading them. The h-index 11 in the overall archive is mainly contributed by public health papers, and the zero citations in the last 5 years indicate that the public health researcher has stopped publishing. It is recommended to use institutional affiliation or ORCID to distinguish between researchers with the same name before re-evaluating.
Top 20 Citations Papers| # | Year | Citation | Title |
|—|——|——|——| | 1 | 2000 | 444 | The dynamics of alcohol and marijuana initiation: patterns and predictors of first use in adolescence. | | 2 | 2001 | 416 | Long-Term Effects of the Seattle Social Development Intervention on School Bonding Trajectories | | 3 | 2002 | 298 | Developmental relationships between adolescent substance use and risky sexual behavior in young adulthood. | | 4 | 2005 | 289 | Family influences on the risk of daily smoking initiation. | | 5 | 2004 | 209 | Adolescent heavy episodic drinking trajectories and health in young adulthood. | | 6 | 2002 | 179 | A developmental analysis of sociodemographic, family, and peer effects on adolescent illicit drug initiation. | | 7 | 2000 | 155 | Developmental pathways to alcohol abuse and dependence in young adulthood. | | 8 | 2003 | 135 | Protective Factors against Serious Violent Behavior in Adolescence: A Prospective Study of Aggressive Children | | 9 | 2001 | 68 | Early Adolescent Predictors of Youth Violence as Mediators of Childhood Risks | | 10 | 2002 | 46 | Stages and Pathways of Drug Involvement: Substance Use Norms and Transitions in Substance Use: Implications for the Gateway Hypothesis | | 11 | 2002 | 27 | Correspondence between youth report and census measures of neighborhood context | | 12 | 2011 | 0 | Influence of Systematic Early Education on Physical Growth and Mental Development for Infants | | 13 | 2013 | 0 | Reliability and validity of stress vulnerability prediction scale in soldiers | | 14 | 2016 | 0 | Reliability and validity of idol worship scale in college students | | 15 | 2016 | 0 | Superior thermal conductivity in suspended bilayer hexagonal boron nitride | | 16 | 2017 | 0 | Fused Text Segmentation Networks for Multi-oriented Scene Text Detection | | 17 | 2017 | 0 | Thermal conduction across a boron nitride and silicon oxide interface | | 18 | 2018 | 0 | Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles | | 19 | 2018 | 0 | Stochastic Channel Decorrelation Network and Its Application to Visual Tracking | | 20 | 2018 | 0 | FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval |