Teaching Experiences
Instructor
| 2023 - Present | Advanced Confounding Adjustment Harvard T.H. Chan SChool of Public Health, Boston, MA Implementation of advanced g-methods for confounding adjustment (inverse probability weighting and the parametric g-formula) in the time-fixed and time-varying settings. |
| 2023 - Present | Target Trial Emulation Harvard T.H. Chan SChool of Public Health, Boston, MA Principles of target trial emulation and its applications via appropriate causal analyses of healthcare databases such as administrative claims and electronic health records. |
| 2023 - Present | EPI 289: Epidemiologic
Methods III - Models for Causal Inference Harvard T.H. Chan SChool of Public Health, Boston, MA Models for causal inference with time-fixed exposures; key concepts include bias, methods for confounding and selection bias adjustment, and instrumental variable estimation. |
| 2023 | Causal Inference Using Observational Data Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia Concepts and methods for causal inference and target trial emulation from observational data |
| 2021 - 2022 |
CI
722: Clinical Data Science - Comparative Effectiveness Research I Harvard Medical School, Boston, MA Causal inference for time-fixed exposures; key concepts include bias, methods for confounding adjustment, instrumental variable estimation, and target trial emulation. Course-related materials are available for standardization, instrumental variable estimation, and measurement bias. |
Assistant Director
| 2023 |
CI
722: Clinical Data Science - Comparative Effectiveness Research I Harvard Medical School, Boston, MA Causal inference for time-fixed exposures; key concepts include bias, methods for confounding adjustment, instrumental variable estimation, and target trial emulation. |
| 2022 - 2023 | CI 732: Clinical Data Science - Comparative Effectiveness Research II Harvard Medical School, Boston, MA Advanced topics in epidemiologic designs, confounding adjustment for time-varying treatment strategies and target trial emulation. Course-related materials are available for an introduction to time-varying treatment strategies, and inverse probability weighting for time-varying treatment strategies. |
Guest Lecturer
| 2023 | EPID 800: Advanced Methodological Theory in Epidemiology University of South Carolina Arnold School of Public Health, Columbia, SC Advanced epidemiologic methods in the design of epidemiologic studies, with emphasis on causal inference. Theories and frameworks of causation and interactions between causes and graphical visualization tools. Guest lectured on measurement bias and introduction to target trials. |
| 2023 | Gen Ed 1112: Prediction - The Past and Present of the Future Harvard College Program in General Education Cambridge, MA A coordinated investigation of the history and future of prediction, spanning from Ancient Mesopotamia to modern day computer simulations and AI. Guest lectured on applications of prediction modelling to health research. |
| 2022 | Target Trial Emulation Harvard T.H. Chan SChool of Public Health, Boston, MA Principles of target trial emulation and its applications via appropriate causal analyses of healthcare databases such as administrative claims and electronic health records. Guest lectured on instrumental variable estimation within the context of the target trial framework. |
| 2022, 2024 | CI 732: Clinical Data Science - Comparative Effectiveness Research II Harvard Medical School, Boston, MA Advanced topics in epidemiologic designs, confounding adjustment for time-varying treatment strategies and target trial emulation. Guest lectures included topics on time-varying treatment strategies and inverse probability weighting. |
| 2021 - 2022 | EPI 289: Epidemiologic
Methods III - Models for Causal Inference Harvard T.H. Chan SChool of Public Health, Boston, MA Models for causal inference with time-fixed exposures; guest lectures included topics on instrumental variable methods and g-estimation of nested structural models. |
| 2021 | PHS 6333: Epidemiological Methods The University of Texas Medical Branch, Galveston, TX Intermediate level course on epidemiologic methods in clinical and public health research. Guest lectures covered an introduction to directed acyclic graph (DAGs) and how to identify structural sources of bias (i.e., confounding, selection bias, information bias) using a DAG. Course-related materials are available here. |
Pedagogy Fellowship
| 2020 - 2021 |
Head Pedagogy Fellow Harvard T.H. Chan School of Public Health, Boston, MA Worked on a variety of education efforts, including the design or redesign of courses, organizing and leading teaching workshops, and providing ongoing support for teaching fellows. |
Content Developer and Discussion Moderator
| 2019 - 2021 |
Causal Diagrams: Draw Your Assumptions Before Your Conclusions HarvardX, Boston, MA Drawing causal diagrams under difference assumptions and using causal diagrams to identify structural sources of bias and guide data analysis. |
Head Teaching Fellow
| 2019 - 2020 | EPI 289: Epidemiologic
Methods III - Models for Causal Inference Harvard T.H. Chan SChool of Public Health, Boston, MA Models for causal inference with time-fixed exposures; guest lectures included topics on instrumental variable methods and g-estimation of nested structural models. |
Teaching Fellow
| 2019 - 2020 |
CI 722: Clinical Data Science - Comparative Effectiveness Research I Harvard Medical School, Boston, MA Causal inference for time-fixed exposures; key concepts include bias, methods for confounding adjustment, instrumental variable estimation, and target trial emulation. |
| 2018 - 2019 |
CI 701: Clinical Data Science - Design and Analytics I Harvard Medical School, Boston, MA An introduction to the three main objectives of clinical research: description (data types, study designs, and measures of frequency), prediction (measures of association and regression), and causal inference (via a counterfactual framework). |
| 2018 | EPI 289: Epidemiologic
Methods III - Models for Causal Inference Harvard T.H. Chan SChool of Public Health, Boston, MA Models for causal inference with time-fixed exposures; guest lectures included topics on instrumental variable methods and g-estimation of nested structural models. |
| 2018 | PHS 2000B: Quantitative Research Methods in Population Health II Harvard T.H. Chan SChool of Public Health, Boston, MA Scientific inference and causal reasoning in the population health sciences, with a focus on methods in causal inference (e.g., propensity score, time-varying treatments, mediation analysis) and econometrics (e.g., instrumental variables, regression discontinuity design, difference-in-difference). |
| 2017 - 2018 | EPI 201: Introduction to Epidemiology – Methods I Harvard T.H. Chan SChool of Public Health, Boston, MA An introduction to the design and analysis of epidemiologic studies for description and causal inference. |
| 2017 | EPI 202: Epidemiologic Methods II – Elements of Epidemiologic Research Harvard T.H. Chan SChool of Public Health, Boston, MA Statistical inference, data analysis methods and causal inference in epidemiologic research. |
Teaching Assistant
| 2014 |
EPI 801: Introduction to Epidemiology Queen's University, Kingston, Ontario, Canada An introduction to epidemiologic methods and concepts, including measures of frequency and association, study design, bias, critical appraisal, ethics, and the application of epidemiologic evidence in publish health decision-making. |
- Posted on:
- January 1, 1999
- Length:
- 5 minute read, 1011 words
- See Also: