Course presentations
All graduate students are required to deliver a 15-min talk (10 min presentation + 5 min questions) on one of the following topics (secure yours before others do). You may suggest a topic outside of the pool too. Undergraduate students are encouraged to participate too with bonus 5 points towards the final score.
Topic pools
The topics are given by key words only. Please practice your ability of “educated” searches with google.
- Software key words: stan, bugs & jags, hadoop, spark, tensorflow, Scikit-Learn, Blas & Lapack
- Stastician key words: R. A. Fisher, Andrey Markov, Karl Pearson, Francis Galton, John Craig, George Box, David Cox, William Cochran, Gertrude Cox,
- Research areas: Causal Inference, Forensic Statistics, Bayesian Statistics, Approximate Bayesian Computation, Sequential Monte Carlo method, Variational Bayes, Spatial statistics, Precision Medicine
- Parallel computing: OpenCL, Cuda, SIMD (SSE + AVX)
- Other: Frequentist vs. Bayesian debate, Algorithms behind Machine Learning
Available dates
| Date | Topic | Presenter |
|---|---|---|
| Feb 4 | ||
| Feb 11 | ||
| Feb 18 | ||
| Feb 25 | ||
| Mar 4 | ||
| Mar 11 | ||
| Mar 18 | ||
| Mar 25 | ||
| April 8 | ||
| April 15 | ||
| April 22 | ||
| April 29 |