Dr. Yi Sun l Quantitative risk assessment | Best Researcher Award

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Dr. Yi Sun | Quantitative risk assessment | Best Researcher Award

👩‍⚕️ Dr. Yi Sun Institute for Occupational Safety and Health of the German Social Accident Insurance University, Germany

Dr. Yi Sun a distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

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🔬 Professional Profile

Occupational epidemiology expert with a focus on epidemiological methods, exposure assessment, and quantitative risk evaluation. Dr. Sun serves as a senior epidemiologist and consultant at the German Social Accident Insurance (DGUV), specializing in:

Regulatory risk assessment for work-related hazards Defining and recognizing occupational diseases based on evidence Evaluating research applications and final reports from various projects Peer-reviewing for esteemed international journals like OEM, European Journal of Epidemiology, International Archives of Occupational and Environmental Health, among others.

🔍 Research Projects

Dr. Sun has contributed to various epidemiological projects covering osteoarthritis, macular degeneration, breast cancer etiology, lung cancer screening among radon-exposed workers, respiratory health effects, and more. These studies span diverse worker groups, including those in the rubber industry, coal tar refineries, and workers exposed to silica dust and diesel exhaust.

👨‍💼 Employment History

Present: Applied Epidemiology at Institute of Occupational Safety and Health (BGIA), German Social Accident Insurance

University of MĂĽnster, Institute of Epidemiology and Social Medicine

University of Ulm, Department of Epidemiology

Beijing Quarantine Service, China

đź“š Education

University of Essen: Doctor of Medicine (MD)

Beijing University, Medical Division: Bachelor of Preventive Medicine (Public Health)

🗣️ Languages

Chinese: Native proficiency

German: Fluent (written and spoken)

English: Fluent (written and spoken)

📖 Publications  Top Note :

Development and Validation of a Practical Instrument for Injury Prevention: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT)   paper publication in June 2018

Exposure–response relationship and doubling risk doses—a systematic review of occupational workload and osteoarthritis of the hip     paper publication in 30 September 2019 cite by 4

Hip osteoarthritis and physical workload: Influence of study quality on risk estimations—a meta-analysis of epidemiological findings    paper publication in January 2019 cite by 2

Diesel exhaust exposure and the risk of lung cancer-a review of the epidemiological evidence  paper publication in 27 January 2014 cite by 26

Exposure-response analysis and risk assessment for lung cancer in relationship to silica exposure: A 44-year cohort study of 34,018workers    paper publication in September 2013 cite by 83

A comparative field study on dust measurements by different sampling methods with emphasis on estimating factors for recalculation from chinese ‘total dust’ measurements to respirable dust concentrations      paper publication in 2012 Jan 6  cite by 2

Long-term exposure to silica dust and risk of total and cause-specific mortality in Chinese workers: A cohort study

paper publication in 2012 Apr 17  cite by 192

 

Epidemiological evidence for work load as a risk factor for osteoarthritis of the hip: A systematic review      paper publication in 2012 feb 14  cite by 64

 

 

 

Monte Carlo simulation

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Monte Carlo simulation 

The International Conference on Statistical Methods for Analyzing Engineering Data (ICSMAED) serves as a prominent platform for experts, researchers, and practitioners in the field of engineering to converge and exchange insights on cutting-edge statistical methodologies and their applications in engineering data analysis. This conference facilitates the exploration of innovative techniques and solutions to address complex challenges in engineering through a statistical lens.

Bayesian Inference in Engineering Analysis

Delve into the utilization of Bayesian statistical methods for modeling uncertainties, reliability assessments, and decision-making in engineering systems.

Design of Experiments (DoE) in Engineering

Explore the application of DoE techniques to optimize product designs, enhance manufacturing processes, and improve product quality.

Time Series Analysis for Engineering Data

Discuss the use of time series models to analyze temporal data in engineering applications, such as predictive maintenance, quality control, and forecasting.

Reliability and Survival Analysis

Investigate statistical approaches to assess the reliability and lifetime of engineering systems and components, aiding in maintenance and risk management.

Machine Learning and Data Mining in Engineering: Examine the integration of machine learning and data mining techniques to extract valuable insights from large-scale engineering datasets, enabling data-driven decision-making.