Jonathan Luu

Courses

My teaching and learning experience.

Courses I’ve Taught

During my time at Harvard, I have been a teaching assistant for three courses:

  • Applied Survival Analysis (BST223) - 3 years
  • Intro to Data Science (BST260) - 1 year
  • Survival Methods in Clinical Research (BST224) - 1 year

Being a teaching assistant involves teaching labs and lectures, maintaining the course website, holding weekly office hours, grading homeworks, and creating course material.

I also volunteer with the Biostatistics Student Consulting Center, which provides free consulting services for students and post-docs from Harvard School of Public Health and Harvard Medical School. We offer guidance on study design, analysis planning, and statistical programming for clients’ research projects, grant submissions, and dissertations.

Finally, I participate in the annual StatStart program, a summer program for high school students interested in data science and computing. Volunteers help teach programming in R and basic statistics in the form of lectures and lab, develop computational thinking and problem-solving skills, and guide students on a final project and presentation.

Courses I’ve Taken

Below are the courses I have taken during my time at the University of Southern California and Harvard University. Through these courses, collaborations, and personal projects, I have developed a strong base in statistical theory and programming.

Harvard University

Statistics Courses

  • Probability I (BST230)
  • Methods I (BST232)
  • Statistical Inference I (BST231)
  • Intro to Data Structures & Algorithms (BST234)
  • Analysis of Multivariate & Longitudinal Data (BST245)
  • Applied Survival Analysis (BST223)
  • Analysis of Failure Time Data (BST244)
  • Survival Methods in Clinical Research (BST224)
  • Adaptive Clinical Trials (BST254 II)
  • Topics in Clinical Trials (BST238)
  • Pharmacoepidemiology (EPI221)
  • Statistical & Quantitative Methods for Pharmaceutical Regulatory Science (BST217)
  • Responsible Conduct of Research (HPM548)
  • Bayesian Methodology (BST249)
  • Health Survey Samples (BST239)
  • Statistical Consultation (BST312)

Programming Courses

  • Cancer Genome Data Science (BST283)
  • Intro to Social & Biological Networks (BST267)
  • Advanced Regression & Statistical Learning (BST235)
  • Statistical Computing & Learning (STAT221)
  • Intro to Data Science (BST260)

University of Southern California

Statistics Courses

  • Principles of Biostatistics (PM510)
  • Principles of Epidemiology (PM512)
  • Data Analysis Pt. 1 (PM511A)
  • Data Analysis Pt. 2 (PM511B)
  • Statistical Methods for Epidemiology (PM518A)
  • Design of Clinical Studies (PM523)
  • Introduction to the Theory of Probability (PM522A)
  • Introduction to the Theory of Inference (PM522B)
  • Introduction to Probability and Statistics (EE364)
  • Experimental Designs (PM513)
  • Calculus II (MATH126)
  • Calculus III (MATH226)
  • Linear Algebra and Linear Differential Equations (MATH225)

Programming Courses

  • Introduction to Programming (CSCI103)
  • Data Structures and Object-Oriented Design (CSCI104)
  • Discrete Methods in Computer Science (CSCI170)
  • Principles of Software Development (CSCI201)
  • Introduction to Operating Systems (CSCI350)
  • Introduction to Algorithms and Theory of Computing (CSCI270)
  • Design and Construction of Large Software Systems (CSCI401)
  • Professional C++ (ITP435)
  • Programming Graphical User Interfaces (ITP368)
  • App Development for Phones and Tablets (ITP341)
  • Advanced Statistical Computing (PM520)
  • Statistical Programming in R (PM560)
  • Fundamentals of Digital Logic (EE154)
  • Introduction to Digital Circuits (EE254)
  • Parallel and Distributed Computation (EE451)
  • Introduction to Computer Networks (EE450)
  • Computer Systems Organization (EE457)
  • MOS VLSI Circuit Design (EE477)