Junzi Chen Email & Phone Number

Toronto, Ontario, Canada

- Developed and implemented SARIMA models to capture and predict seasonal patterns within respiratory virus transmission data, enabling accurate short-term forecasts that account for recurring fluctuations in virus spread.- Complemented this approach with logistic regression to analyze binary outcomes, specifically modeling the likelihood of severe disease occurrence and assessing how various risk factors contribute to increased transmission and health risks.-Applied Generalized Additive Models (GAMs) with weights and offsets to account for changes in the total number of tests, capturing complex, nonlinear relationships and providing a flexible framework to understand trends shaped by demographic and environmental variables.

- Provided weekly in-person and online office hours for student support on course content, ensuring that students are well-prepared for quizzes, midterms and final exams. Created a welcoming environment for questions, clarifying concepts, and guiding through problem-solving.- Monitored midterms and quizzes, ensuring a smooth and secure testing environment. Assisted in preparations, troubleshooting, and student queries to facilitate a fair assessment experience.

- Leading a scoping review titled Emerging Approaches of Mpox Image Analysis, focused on synthesizing advanced AI-based methodologies in dermatological image processing for Mpox skin lesions. This includes both traditional Convolutional Neural Networks (CNNs) and cutting-edge approaches like vision transformers, transfer learning, and Generative Adversarial Networks (GANs).- Providing a comprehensive overview of AI techniques to address challenges in data scarcity, with evidence-based recommendations for innovative methods that enhance diagnostic accuracy in settings with limited labeled data. This work is particularly relevant for healthcare domains facing data constraints.-Preparing findings for publication to advance academic and clinical development of Mpox image diagnosis. The report identifies current best practices, emerging methodologies, and future research directions, offering a strategic roadmap for advancing dermatological diagnostic techniques for scientists, epidemiologists, and clinicians.

Toronto, Ontario, Canada

- Developed and implemented automated processes by leveraging UFT to execute large-scale functional and regression test automation and reduced manual intervention in routine data management tasks, improving the accuracy and speed of data processing workflows and testing cycles.- Developed, designed, and visualized comprehensive reports aimed at improving operational efficiency and fostering data-driven decision-making. - Collaborated with cross-functional teams to deliver actionable insights and support strategic initiatives.- Engaged in various aspects of business analytics by extracting and processing data from multiple sources. Utilized IBM's Data Transfer software to gather, analyze, and interpret data to provide actionable insights for risk mitigation and operational improvements.- Leveraged advanced Excel functionalities to acquire, cleanse, validate, and transform large datasets. Ensured the integrity of data by filtering out inconsistencies, duplicates, and anomalies, and converting data into standardized formats for efficient storage and subsequent analysis.

Chengdu, Sichuan, China

- Designed and proposed innovative algorithms to identify and rectify errors within data, enhancing data accuracy and consistency.- Collaborated closely with the algorithm team to develop, test, and optimize machine learning models, contributing to the refinement of predictive analytics and data processing workflows.- Organized and consolidated data across the company’s main websites using Excel and data management tools, ensuring accessibility, consistency, and ease of future data retrieval for analytical and business intelligence purposes.- Assisted in the deployment and monitoring of machine learning models in production, identifying potential issues and opportunities for model optimization.- Contributed to comprehensive data documentation and reporting, detailing the algorithm’s functionality and data flow, providing clear references for future development and troubleshooting.

Master Of Science - Ms, Biostatistics

Bachelor Of Science - Bs, Mathematics And Statistics, 3.9