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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Welcome
About me
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Posts
Future Blog Post
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Distributed Learning for Causal Inference
Published in , 1900
This paper provides privacy-preserving, communication-efficient, and robust estimation and inference for targeted average treatment effects in the presence of heterogeneity.
Semi-supervised Estimation of Average Survival
Published in , 1900
This paper develops semi-supervised, transfer learning methods to improve efficiency of pragmatic trials when the study endpoint is time-to-event and is captured using imperfect surrogates in electronic health records.
On the Evaluation of Surrogate Markers in Real World Data Settings
Published in In preparation; Winner of the 2021 ENAR Distinguished Student Paper Award, 2020
This paper provides doubly robust estimation and inference for the proportion of treatment effect on a true outcome that is explained by a surrogate marker in observational data settings.
talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Principles of Clinical Trials (BST 214)
Head Teaching Fellow, Harvard Biostatistics, 2021
I served as the head teaching fellow in Spring 2021 and a teaching fellow in Spring 2020 for this introductory course about topics in the design, analysis, and interpretation of clinical trials.
Advanced Topics in Clinical Trials (BST 238)
Head Teaching Fellow, Harvard Biostatistics, 2021
I served as the head teaching fellow in Spring 2021 for this doctoral course for biostatistics students on advanced topics in the design, analysis, and interpretation of clinical trials, including study design; choice of endpoints; interim analyses and group sequential methods; subgroup analyses; and meta-analyses. I served as a teaching fellow in Spring 2020.
Applied Survival Analysis (BST 223)
Teaching Fellow, Harvard Biostatistics, 2022
I served as a teaching fellow in Spring 2022 for the Harvard Biostatistics department’s course on applied survival analysis taught by Professor Sebastien Haneuse (class size: 100).
Design of Experimental and Non-experimental Studies (STAT 293)
Head Teaching Fellow, Harvard Statistics, 2022
I served as the head teaching fellow in Spring 2022 for this reading-based doctoral course on causal inference, taught by Professor Jose Zubizarreta (class size: 20).
Statistical Inference (BST 222)
Teaching Fellow, Harvard Biostatistics, 2022
I served as a TF in Fall 2022 for BST 222 taught by Rui Duan. I also TF’ed for this course in 2021, 2020, and 2019. I taught labs for this course in probability theory and statistical inference for masters students in biostatistics and doctoral students in epidemiology, environmental sciences, and other departments, using Casella and Berger.
Causal Inference with Applications (STAT 286)
Teaching Fellow, Harvard Statistics, 2022
I served as a teaching fellow in Fall 2022 for this doctoral course on causal inference, taught by Professor Kosuke Imai (class size: 60).
Methods for Observational Research 2 (HSCI 5151)
Instructor, Northeastern University Department of Health Sciences, 2024
This course examines advanced methods in conducting observational research across pharmacoepidemiology, emphasizing approaches used by the Observational Health Data Sciences and Informatics (OHDSI) community. Focuses on using open-source software and open-science principles to conduct and interpret a real-world evidence (RWE) study.