Teaching of Frank Miller

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Teaching

I am teaching at Stockholm University, Department of Statistics

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My teaching at the University of Linköping, Department of Computer and Information Science

Oct 2023 - Jan 2024: Computational statistics
Mar-May 2023: Ph.D. course Advanced computational statistics

My teaching at the University of Stockholm, Department of Statistics

Jan 2023: One lecture about Computer based methods: randomization, bootstrap within the course Biological statistics III
Jan/Feb 2022: Computational statistics
Jan 2022: One lecture about Computer based methods: randomization, bootstrap within the course Biological statistics III
Nov 2021: Experimental design
May 2021: Two lectures about Active machine learning within the course Machine learning
Mar/Apr 2021: Ph.D. course Optimisation algorithms in statistics II
Jan/Feb 2021: Computational statistics
Jan 2021: One lecture about Computer based methods: randomization, bootstrap within the course Biological statistics III
Oct/Nov 2020: Ph.D. course Optimisation algorithms in statistics I
Sept 2020: Experimental design
Apr 2020: Statistical computations
Jan 2020: One lecture about Computer based methods: randomization, bootstrap within the course Biological statistics III
Oct 2019: Experimental design
Fall 2019: Självständigt arbete (bachelor theses)
May 2019: Finansiell statistik
Apr 2019: Statistical computations
Jan 2019: One lecture about Computer based methods: randomization, bootstrap within the course Biological statistics III
Dec 2018/Jan 2019: Finansiell statistik
Oct 2018: Experimental design
May 2018: Finansiell statistik
Apr 2018: Statistical computations
Dec 2017: Finansiell statistik
Oct 2017: Advanced methods for sample size determination within the course Statistical methods
Mar-May 2017: Statistical philosophy of science (Statistisk vetenskapsteori)
Spring 2017: Självständigt arbete (bachelor theses)
Oct 2016: Experimental design
Sept 2016: Advanced methods for sample size determination within the course Statistical methods
Fall 2016: Självständigt arbete (bachelor theses)
Mar-May 2016: Statistical philosophy of science (Statistisk vetenskapsteori)
Oct 2015: Experimental design
Sept 2015: Sample size determination in practice within the course Statistical methods
Mar-May 2015: Statistical philosophy of science (Statistisk vetenskapsteori)
Apr 2015: Statistical hypothesis testing within Basic Course in statistics for PhD students
Sept/Oct 2014: Grundläggande statistik för ekonomer
Sept/Oct 2014: Statistical philosophy of science (Statistisk vetenskapsteori)
Apr 2014: Sample size determination in practice within the course Statistical methods
Feb/Mar 2014: Grundläggande statistik för ekonomer
Nov/Dec 2013: Statistical methods
Apr 2013: Sample size determination within the course Statistical methods

My teaching at the University of Stockholm, Division of Mathematical Statistics

Jan-Mar 2013: Analysis of categorical data
Nov/Dec 2012: Teaching and support for learning group Longitudinal analysis

My teaching at the University of Karlsruhe (1998-2003)

Statistics for students of Biology, problem sessions
Statistics for students of Computer Science, problem sessions
Stochastics II for students of Mathematics, problem sessions
Course for Applied Statistics using SAS (Summer term 2002)

Supervision of bachelor and master's theses

Theses from 2023 were at the University of Linköping, Department of Computer and Information Science. Theses until 2020 were at the University of Stockholm, Department of Statistics (unless stated otherwise).

Year	Le-vel	Student(s)	Title	External collaborator
2023	M	Stylianos Sidiropoulos	Forecasting airline revenue across markets with machine learning	Acceleration Nordic
2020	M	Ganna Fagerberg	Random-effects meta-analyses of observational studiesof rare events: comparing frequentist and Bayesian approaches
2020	M	Martin Hyllienmark	Identifying minimax designs for clinical trials with a modified nested particle swarm optimization algorithm
2019	M	Tobias Löv	Optimizing marketing campagins with active machine learning
2018	M	Charlotte Pettersson	Using Supervised Learning to Predict COPD Exacerbations	IQVIA
2017	B	Johan Persson*	Restricted Region Exact Designs
2016	M	Moa Thyni	Comparison of the pooled test with other multiple test procedures in clinical trials
2016	M	Vasileios Manikas	A Bayesian Finite Mixture Model for Network-Telecommunication Data	Ericsson
2016	B	Hanna Pettersson	Workplace fatalities
2016	B	Merrisha Axelsson & Edvard Åberg	Non-response analysis of non-response bias in Swedish Work Environment Investigation 2015	Arbetsmiljö-verket
2015	B	Charlotta Löf Ryk & Anna Yang	Statistical methods for evaluating risk factors for urinary bladder cancer patients
2015	B	Britt-Inger Forsberg & Yuliya Leontyeva	Multiple comparisons - in search for significance
2015	B	Olli-Pekka Kinnunen & Karl Röcklinger	Extreme Car Insurance Claims and Their Seasonality	Insurance company
2015	M	Aaron Levine	Using Markov Models to Analyze Brand Switching Between Treatments of Chronic Respiratory Diseases	IMS Health
2015	M	Tommy Löfgren	Measuring survey mode effects using the principal stratification framework
2013	B	Laszlo Sipos & Selma Aydin	Comparison of analysis models of effect of treatment for preterm infants	Sobi
2010	B	Carolina Blomqvist**	Response adaptive optimal design in clinical trials - a simulation study motivated by a real data example	AstraZeneca

B=bachelor thesis, M=master's thesis
*Thesis at Department of Math. Statistics, University of Linköping
**Thesis at Department of Math. Statistics, University of Stockholm. I was co-supervisor; main supervisor: Ola Hössjer, Math. Statistics, Stockholm University